How to set up a smart factory with the Internet of Things (IoT)

The IoT (Internet of Things) is creating new opportunities for companies to enhance their services, gain business insights from accurate and timely data, improve business processes and differentiate their offerings. This white paper from Softweb Solutions describes IoT value propositions for manufacturing units and defines an ROI model for building a business case and tracking results related to IoT initiatives.

Mnet 173593 Softweb Smart Factory 784x392
US Toll Free Number: 1-866-345-7638 Email: info@softwebsolutions.com Website : www.softwebsolutions.com Table of contents 1. Executive Summary 2. Industrial Automation 3. The Value Proposition 4. Essential Components for IoT in Manufacturing 5. IoTConnect - Softweb's PaaS platform 6. Business Case of IoT in Manufacturing 7. Envisioning the Working of an IoT-Enabled Company 8. How to Start Creating a Smart Factory 9. Workshop Agenda 10. Conclusion 02 03 04 09 11 13 14 15 17 18 How to set up a smart factory with the Internet of Things (IoT) 02How to set up a smart factory with the Internet of Things (IoT) Manufacturing units today are under tremendous pressure from management and customers to deliver high quality products and services at low costs in a minimum amount of time. Any company that invests time and money in IoT will expect a favorable return on their investment. Today’s market leaders rightly believe that ROI is multidimensional and hence, they focus on customer satisfaction, collection of accurate data and converting it to the right information and brand differentiation, all of which can lead them to increased revenue. The IoT (Internet of Things) is creating new opportunities for companies to enhance their services, gain business insights from accurate and timely data, improve business processes and differentiate their offerings. In fact, connecting machines is bringing companies closer to their customers while delivering real ROI and payback. A research conducted by MarketsandMarkets reveals that IoT in the manufacturing market is on the rise and will end up increasing from $4.11 billion in 2015 to $13.49 billion by 2020. The compound annual growth rate (CAGR) is estimated to be around 26.9%. This white paper from Softweb Solutions describes IoT value propositions for manufacturing units and defines an ROI model for building a business case and tracking results related to IoT initiatives. The Internet of Things, also known as the fourth industrial revolution, has the potential to change the face of the manufacturing sector. If the advancement in technology is anything to go by, intelligent factories will go on to become the norm, rather than the exception, within a decade or even less. So what goes into making a smart factory, let’s find out. The Internet of Things The Internet of Things is the torchbearer of smart factories. It connects various ‘things’ to each other in order to facilitate the transfer of data. Multiple types of sensors with the ability to connect to the cloud are installed in the factory to gather data which helps in optimizing the factory. Data Data plays an important role in a smart factory. Gaining insights for streamlining the manufacturing process can only be carried out by collecting data. Moreover, it is now possible to transfer big data in real-time and multiple storage options are available to save it in a centralized location. Industry 4.0 Automation The sensors and other IoT-enabled things installed in the factory can work autonomously to drive the production in the manufacturing industry with minimal human intervention. These sensors are now capable of detecting faults on the basis of the data collected by them and independently take the decision to stop the faulty equipment, what we also know as predictive maintenance. Precision Those who are still apprehensive about the idea of setting up an autonomous unit run by a bunch of inanimate objects, would be relieved to know that these devices are highly reliable. These tiny gadgets are highly accurate and work with the utmost precision to get the work done. Executive Summary 03 The Internet of Things, also known as the fourth industrial revolution, has the potential to change the face of the manufacturing sector. If the advancement in technology is anything to go by, intelligent factories will go on to become the norm, rather than the exception, within a decade or even less. So what goes into making a smart factory, let’s find out. The Internet of Things The Internet of Things is the torchbearer of smart factories. It connects various ‘things’ to each other in order to facilitate the transfer of data. Multiple types of sensors with the ability to connect to the cloud are installed in the factory to gather data which helps in optimizing the factory. Data Data plays an important role in a smart factory. Gaining insights for streamlining the manufacturing process can only be carried out by collecting data. Moreover, it is now possible to transfer big data in real-time and multiple storage options are available to save it in a centralized location. The Internet of Things is ideal for increasing the level of industrial automation in today's factories. For manufacturing companies who have already installed sensors, actuators and other low-level devices in their existing industrial automation systems, upgrading and retrofitting IoT-enabled devices is a low hanging fruit. The companies can take advantage of the increase in network speeds, memory size, commercial off-the-shelf sensors and other hardware along with well-established cloud platforms. The technology today is robust enough to not hamper the design of the systems as was the case in the past. This will give plant managers new levels of control and insights regarding the production floor. The key to the success of industrial automation is making use of the data that is gathered. So the industrial automation networks that collect data also need to communicate this data either to the cloud or an internal datacenter where technologies such as Hadoop are implemented and data science techniques and predictive models are used on that data. Another reason for manufacturers to adopt IoT in their factories is the issue of obsolescence. Many of the industrial automation systems in factories today will outlive vendor support. By upgrading their systems with IoT systems, they can extend both the functionality and the lifespan of these systems. The decreasing costs of Internet bandwidth and storage means that companies can now store terabytes of data very cheaply compared to even a few years ago. Automation The sensors and other IoT-enabled things installed in the factory can work autonomously to drive the production in the manufacturing industry with minimal human intervention. These sensors are now capable of detecting faults on the basis of the data collected by them and independently take the decision to stop the faulty equipment, what we also know as predictive maintenance. Precision Those who are still apprehensive about the idea of setting up an autonomous unit run by a bunch of inanimate objects, would be relieved to know that these devices are highly reliable. These tiny gadgets are highly accurate and work with the utmost precision to get the work done. Industrial Automation The technology today is robust enough to not hamper the design of the systems as was the case in the past. The new age automation in industries is not limited to a machine carrying out a task without any involvement from humans. IoT has gone a step ahead to ensure that the sensors responsible for monitoring the working of equipment and sending data to cloud-based storage systems, are also capable of starting or stopping the operation of machines independently, if the need arises. For example, if a company has installed a vibration sensor on a machine, it will detect vibrations and send the data to the cloud for processing. All this is possible today because of the availability of robust M2M systems in the market. M2M means machine-to-machine. It covers a broad range of technologies that are used to enable networked devices to exchange data with each other and perform actions without human assistance. M2M technology has applications in almost every area of manufacturing including ensuring plant and personnel safety. For example, if during the production of certain goods the temperature of the immediate area increases beyond a certain predefined limit, the sensors will record this fact and it will trigger an immediate shutdown since the company’s safety engineers have decided that crossing this threshold is dangerous. If the company does not want to implement an automated shutdown system, it can also set up the sensors to transmit data to key personnel who have been given remote monitoring ability on their desktops, tablets and even mobile phones. These employees can then send shutdown instructions to the machine remotely, reduce its production rate or carry out any other function in order to take care of the safety issue. How to set up a smart factory with the Internet of Things (IoT) 04 The value proposition of IoT falls into several buckets of capabilities that differentiate your products, including remote monitoring, remote service, usage analysis, ERP/CRM integration, and value-added services. Core business processes like billing, field service, product registration, compliance, consumable management, recalls, and warranty management can all be improved with connected product data. And finally, the selling and marketing of connected products, which include new applications for end users, can deliver a competitive advantage and drive revenue growth. 1 Increased Product Revenue IoT enablement bears fruits through direct as well as in-direct revenue streams as described below with examples. Based on the value-added services that can be enabled by IoT, company ABC estimates that a connected product line could generate an additional revenue stream. Assuming customers will subscribe to these services within the first year of product ownership, here is a sample calculation of increased revenue: Step 1 : Determine the value of connected product services for each product unit assuming the average selling price of a connected application is $50 per year per user, and the average number of users per connected product is 20. Example : $50 x 20 users per product = $1,000 per product. Step 2 : Estimate the total product revenue increase. Assuming a 25 percent attach rate on a total product unit volume of 100,000, the increase in product revenue for the new connected application would be 100,000 units x 25% x $1,000 = $25,000,000 2 Saving on Labor Costs Example : ABC Company estimated that each field service technician deployed in the field has a capacity of ten on-site customer visits per week. The expected results for implementing remote service would be a reduction in total on-site visits by 30 percent. The burden rate for a field service technician is $100 per hour. Step 1 : Determine the number of visits per week, assuming that an average field-service visit at a customer location is four hours long. Example : 40 hours per week/4 hours per visit = 10 calls on average per field service technician per week Step 2 : Determine the man-hours saved by using IoT to remotely diagnose and repair 30 percent fewer issues without an on-site visit. Example : 10 calls x 30% x 4 hours = 12 man-hours saved per week Step 3 : Develop a quantifiable metric; subtract the amount of time required per workweek times the burden rate for a field service technician to determine labor cost savings. Example : 12 hours per week x $100 per hour = $1,200 in savings per workweek. Step 4 : Determine the impact across the entire field service organization. Example : Assuming 100 technicians x 50 workweeks x $1,200 per workweek = $6,000,000 annual savings 3 Business Benefits Product Tracking : The Internet of Things can help manufacturers easily track products such as raw materials, finished goods, parts and more. Sensors can be used to get real-time updates regarding them, allowing companies to optimize logistics to streamline and accelerate the process and cut unwanted costs. Tracking products in real time allows companies to maintain the quality of their finished goods, maintain inventory levels and even prevent thefts. Use Case : A manufacturing company required an advanced system for tracking their raw materials while they were being transported. Using RFID tags, the company was able to track the exact location of the materials, allowing them to start production immediately after they arrived at the location without wasting time. Real-time product tracking not only helps the company improve its efficiency, but also helps them save up on time and costs. Predictive Maintenance : Accurately predict the maintenance cycle of your devices, machines and their components by analyzing historical data. Analysis of connected product data will uncover patterns that are early indicators of failures. Rather than performing preventive maintenance on a calendar basis when it may not be needed, companies can track exactly how much a device has been used and if it’s time for service; thereby eliminating unnecessary preventive maintenance calls and premature repairs or component replacement. Service reps can also perform preventive maintenance during scheduled calls, reducing unplanned and planned downtime and customer interruption. This predictive maintenance knowledge can then feed increased revenues by providing increased uptime with premium SLA pricing. Use Case : A factory is turned into a smart unit by installing vibration and noise sensors on machines and other high-end assets. These sensors effectively collect data regarding the working of the machines as well as their components. The data is analyzed in real-time to find out when a machine failure is likely to happen and also to predict the breakdown of a machine component or part. This helps the factory to carry out maintenance in advance to avoid downtime. Improved Product Design : The understanding gained from real end-user behavior and usage patterns also allows product managers and engineers to design better products and prioritize new features, as well as drive an increased market share by offering a superior product design. The company can utilize this data to define the next-generation of product requirements and ensure that they design a product that takes into consideration customer feedback. Use Case : A manufacturer of smart watches installed sensors to collect information in order to gain insights regarding consumer usage. It found that most consumers are rough users and end up damaging their watches pretty often. This insight prompted the company to change the material used to design their watches and make them capable of enduring rough usage. Identification of Quality Issues : By looking at the trends across multiple systems, you can reduce costs by identifying any quality issues or design flaws in parts supplied by third parties or within your own manufacturing processes, allowing you to understand what is causing downtime for customers. Understanding the relationships between problems and specific batches or production runs can identify a bad batch early on and streamline the recall process. It is also possible that the problems are of a more serious nature and are still part of the current manufacturing process. In this case, usage data may trigger the need to change the current manufacturing process. Use Case : A manufacturing unit ended up producing faulty goods and the fault went undetected in the testing stages. The first batch of product was delivered and the noise sensors attached to them sent out notifications to the company regarding the unwanted noise being produced. This data prompted the company to test the product again. It was then found that a certain component within the product was not working properly and hence, the company immediately recalled all of its batches. The fault was rectified in the manufacturing unit and the new batch was then delivered. Dynamic Route Planning Manufacturing units use a GPS-based vehicle tracking system to collect accurate location data of their delivery vehicles in real-time. This data is collected at a centralized location and can be analyzed for optimizing the routes by suggesting the best or an alternative route to the driver. Various factors such as traffic situation and the condition of the road can be taken into consideration before suggesting another route to ensure faster delivery of the consignment. Use Case : A company uses dynamic route planning to deliver their goods to the retailers as fast as possible. All the location data is collected on the cloud and is analyzed by a team to ensure that the stores that need to replenish their inventory immediately, receive the products before the ones which have some stock left. Moreover, the team also takes into consideration the traffic situation through reliable applications and suggests new routes to the vehicle drivers to save time and fuel. Keeping Energy Consumption in Check Keeping tabs on the energy consumption in a factory is a pre-requisite as it can help reduce the cost to a great extent. New age components are used to find out how much power or fuel is being used by a certain machine or equipment and the collected data can be analyzed to check if it is more than the required amount. Use Case : A company decided to use the smart power monitor system to detect how much power is used by every machine in the factory as well as incorrect wiring. An alarm goes off as soon as The Value Proposition Smart, connected products enable remote monitoring and remote service that drive both a reduction in the costs of services and an improvement in the level of service. Analysis of connected product data can improve business decisions, product design, and manufacturing processes. The new age automation in industries is not limited to a machine carrying out a task without any involvement from humans. IoT has gone a step ahead to ensure that the sensors responsible for monitoring the working of equipment and sending data to cloud-based storage systems, are also capable of starting or stopping the operation of machines independently, if the need arises. For example, if a company has installed a vibration sensor on a machine, it will detect vibrations and send the data to the cloud for processing. All this is possible today because of the availability of robust M2M systems in the market. M2M means machine-to-machine. It covers a broad range of technologies that are used to enable networked devices to exchange data with each other and perform actions without human assistance. M2M technology has applications in almost every area of manufacturing including ensuring plant and personnel safety. For example, if during the production of certain goods the temperature of the immediate area increases beyond a certain predefined limit, the sensors will record this fact and it will trigger an immediate shutdown since the company’s safety engineers have decided that crossing this threshold is dangerous. If the company does not want to implement an automated shutdown system, it can also set up the sensors to transmit data to key personnel who have been given remote monitoring ability on their desktops, tablets and even mobile phones. These employees can then send shutdown instructions to the machine remotely, reduce its production rate or carry out any other function in order to take care of the safety issue. these faults are identified, which is detected by the noise sensors. These sensors are programmed to send out alerts in order to keep power consumption in check. Warranty Management The Internet of Things can help manufacturers manage warranty costs efficiently by identifying if the machine failure is a manufacturing fault or something to do with the way the product was used. It has a huge potential for manufacturers supplying equipment to factories and can help companies save up on their maintenance expenditure and even generate revenue for their services. One of the main advantages of warranty management is that it helps avoid fraudulent claims. Use Case : A factory equipment manufacturer installed temperature and humidity sensors on its products to detect the conditions of the unit where they are being used. On receiving a call from its client for maintenance during the warranty period, the manufacturer checked the conditions using the data collected by the sensors and found that the company was not adhering to the parameters set in the warranty conditions. Due to this, the company informed the client that the warranty’s conditions were not met and repairs would mean an additional charge for the client. 4 OPTIMIZED BUSINESS PROCESSES The Value of Product Data Integration and Business Process Efficiency: Organizations, and particularly manufacturing units, who have now connected things/assets/entities over the Internet, are taking the advantage of IoT by pulling real time, accurate data into enterprise systems like CRM, ERP or data warehouses. IoT data from connected assets, in collaboration with other enterprise systems, can provide visible automation across the organization. Additionally, integration with quality assurance (QA) or, product lifecycle management (PLM) can help enhance product features based on real-world data that shows usage patterns or equipment issues—helping to improve customer satisfaction and streamlining beta programs. Measuring critical data points in a device allows for notifications to the service team if there is a risk of failure, and, simultaneously, the finance department can be informed when warranty guidelines are not being upheld. It optimizes critical business processes, reduces service call times, warranty claims etc. The real value delivered with this coherent unit is described in the table below. How to set up a smart factory with the Internet of Things (IoT) 05 The value proposition of IoT falls into several buckets of capabilities that differentiate your products, including remote monitoring, remote service, usage analysis, ERP/CRM integration, and value-added services. Core business processes like billing, field service, product registration, compliance, consumable management, recalls, and warranty management can all be improved with connected product data. And finally, the selling and marketing of connected products, which include new applications for end users, can deliver a competitive advantage and drive revenue growth. 1 Increased Product Revenue IoT enablement bears fruits through direct as well as in-direct revenue streams as described below with examples. Based on the value-added services that can be enabled by IoT, company ABC estimates that a connected product line could generate an additional revenue stream. Assuming customers will subscribe to these services within the first year of product ownership, here is a sample calculation of increased revenue: Step 1 : Determine the value of connected product services for each product unit assuming the average selling price of a connected application is $50 per year per user, and the average number of users per connected product is 20. Example : $50 x 20 users per product = $1,000 per product. Step 2 : Estimate the total product revenue increase. Assuming a 25 percent attach rate on a total product unit volume of 100,000, the increase in product revenue for the new connected application would be 100,000 units x 25% x $1,000 = $25,000,000 2 Saving on Labor Costs Example : ABC Company estimated that each field service technician deployed in the field has a capacity of ten on-site customer visits per week. The expected results for implementing remote service would be a reduction in total on-site visits by 30 percent. The burden rate for a field service technician is $100 per hour. Step 1 : Determine the number of visits per week, assuming that an average field-service visit at a customer location is four hours long. Example : 40 hours per week/4 hours per visit = 10 calls on average per field service technician per week Step 2 : Determine the man-hours saved by using IoT to remotely diagnose and repair 30 percent fewer issues without an on-site visit. Example : 10 calls x 30% x 4 hours = 12 man-hours saved per week Step 3 : Develop a quantifiable metric; subtract the amount of time required per workweek times the burden rate for a field service technician to determine labor cost savings. Example : 12 hours per week x $100 per hour = $1,200 in savings per workweek. Step 4 : Determine the impact across the entire field service organization. Example : Assuming 100 technicians x 50 workweeks x $1,200 per workweek = $6,000,000 annual savings 3 Business Benefits Product Tracking : The Internet of Things can help manufacturers easily track products such as raw materials, finished goods, parts and more. Sensors can be used to get real-time updates regarding them, allowing companies to optimize logistics to streamline and accelerate the process and cut unwanted costs. Tracking products in real time allows companies to maintain the quality of their finished goods, maintain inventory levels and even prevent thefts. Use Case : A manufacturing company required an advanced system for tracking their raw materials while they were being transported. Using RFID tags, the company was able to track the exact location of the materials, allowing them to start production immediately after they arrived at the location without wasting time. Real-time product tracking not only helps the company improve its efficiency, but also helps them save up on time and costs. Predictive Maintenance : Accurately predict the maintenance cycle of your devices, machines and their components by analyzing historical data. Analysis of connected product data will uncover patterns that are early indicators of failures. Rather than performing preventive maintenance on a calendar basis when it may not be needed, companies can track exactly how much a device has been used and if it’s time for service; thereby eliminating unnecessary preventive maintenance calls and premature repairs or component replacement. Service reps can also perform preventive maintenance during scheduled calls, reducing unplanned and planned downtime and customer interruption. This predictive maintenance knowledge can then feed increased revenues by providing increased uptime with premium SLA pricing. Use Case : A factory is turned into a smart unit by installing vibration and noise sensors on machines and other high-end assets. These sensors effectively collect data regarding the working of the machines as well as their components. The data is analyzed in real-time to find out when a machine failure is likely to happen and also to predict the breakdown of a machine component or part. This helps the factory to carry out maintenance in advance to avoid downtime. Improved Product Design : The understanding gained from real end-user behavior and usage patterns also allows product managers and engineers to design better products and prioritize new features, as well as drive an increased market share by offering a superior product design. The company can utilize this data to define the next-generation of product requirements and ensure that they design a product that takes into consideration customer feedback. Use Case : A manufacturer of smart watches installed sensors to collect information in order to gain insights regarding consumer usage. It found that most consumers are rough users and end up damaging their watches pretty often. This insight prompted the company to change the material used to design their watches and make them capable of enduring rough usage. Identification of Quality Issues : By looking at the trends across multiple systems, you can reduce costs by identifying any quality issues or design flaws in parts supplied by third parties or within your own manufacturing processes, allowing you to understand what is causing downtime for customers. Understanding the relationships between problems and specific batches or production runs can identify a bad batch early on and streamline the recall process. It is also possible that the problems are of a more serious nature and are still part of the current manufacturing process. In this case, usage data may trigger the need to change the current manufacturing process. Use Case : A manufacturing unit ended up producing faulty goods and the fault went undetected in the testing stages. The first batch of product was delivered and the noise sensors attached to them sent out notifications to the company regarding the unwanted noise being produced. This data prompted the company to test the product again. It was then found that a certain component within the product was not working properly and hence, the company immediately recalled all of its batches. The fault was rectified in the manufacturing unit and the new batch was then delivered. Dynamic Route Planning Manufacturing units use a GPS-based vehicle tracking system to collect accurate location data of their delivery vehicles in real-time. This data is collected at a centralized location and can be analyzed for optimizing the routes by suggesting the best or an alternative route to the driver. Various factors such as traffic situation and the condition of the road can be taken into consideration before suggesting another route to ensure faster delivery of the consignment. Use Case : A company uses dynamic route planning to deliver their goods to the retailers as fast as possible. All the location data is collected on the cloud and is analyzed by a team to ensure that the stores that need to replenish their inventory immediately, receive the products before the ones which have some stock left. Moreover, the team also takes into consideration the traffic situation through reliable applications and suggests new routes to the vehicle drivers to save time and fuel. Keeping Energy Consumption in Check Keeping tabs on the energy consumption in a factory is a pre-requisite as it can help reduce the cost to a great extent. New age components are used to find out how much power or fuel is being used by a certain machine or equipment and the collected data can be analyzed to check if it is more than the required amount. Use Case : A company decided to use the smart power monitor system to detect how much power is used by every machine in the factory as well as incorrect wiring. An alarm goes off as soon as these faults are identified, which is detected by the noise sensors. These sensors are programmed to send out alerts in order to keep power consumption in check. Warranty Management The Internet of Things can help manufacturers manage warranty costs efficiently by identifying if the machine failure is a manufacturing fault or something to do with the way the product was used. It has a huge potential for manufacturers supplying equipment to factories and can help companies save up on their maintenance expenditure and even generate revenue for their services. One of the main advantages of warranty management is that it helps avoid fraudulent claims. Use Case : A factory equipment manufacturer installed temperature and humidity sensors on its products to detect the conditions of the unit where they are being used. On receiving a call from its client for maintenance during the warranty period, the manufacturer checked the conditions using the data collected by the sensors and found that the company was not adhering to the parameters set in the warranty conditions. Due to this, the company informed the client that the warranty’s conditions were not met and repairs would mean an additional charge for the client. 4 OPTIMIZED BUSINESS PROCESSES The Value of Product Data Integration and Business Process Efficiency: Organizations, and particularly manufacturing units, who have now connected things/assets/entities over the Internet, are taking the advantage of IoT by pulling real time, accurate data into enterprise systems like CRM, ERP or data warehouses. IoT data from connected assets, in collaboration with other enterprise systems, can provide visible automation across the organization. Additionally, integration with quality assurance (QA) or, product lifecycle management (PLM) can help enhance product features based on real-world data that shows usage patterns or equipment issues—helping to improve customer satisfaction and streamlining beta programs. Measuring critical data points in a device allows for notifications to the service team if there is a risk of failure, and, simultaneously, the finance department can be informed when warranty guidelines are not being upheld. It optimizes critical business processes, reduces service call times, warranty claims etc. The real value delivered with this coherent unit is described in the table below. How to set up a smart factory with the Internet of Things (IoT) 06 The value proposition of IoT falls into several buckets of capabilities that differentiate your products, including remote monitoring, remote service, usage analysis, ERP/CRM integration, and value-added services. Core business processes like billing, field service, product registration, compliance, consumable management, recalls, and warranty management can all be improved with connected product data. And finally, the selling and marketing of connected products, which include new applications for end users, can deliver a competitive advantage and drive revenue growth. 1 Increased Product Revenue IoT enablement bears fruits through direct as well as in-direct revenue streams as described below with examples. Based on the value-added services that can be enabled by IoT, company ABC estimates that a connected product line could generate an additional revenue stream. Assuming customers will subscribe to these services within the first year of product ownership, here is a sample calculation of increased revenue: Step 1 : Determine the value of connected product services for each product unit assuming the average selling price of a connected application is $50 per year per user, and the average number of users per connected product is 20. Example : $50 x 20 users per product = $1,000 per product. Step 2 : Estimate the total product revenue increase. Assuming a 25 percent attach rate on a total product unit volume of 100,000, the increase in product revenue for the new connected application would be 100,000 units x 25% x $1,000 = $25,000,000 2 Saving on Labor Costs Example : ABC Company estimated that each field service technician deployed in the field has a capacity of ten on-site customer visits per week. The expected results for implementing remote service would be a reduction in total on-site visits by 30 percent. The burden rate for a field service technician is $100 per hour. Step 1 : Determine the number of visits per week, assuming that an average field-service visit at a customer location is four hours long. Example : 40 hours per week/4 hours per visit = 10 calls on average per field service technician per week Step 2 : Determine the man-hours saved by using IoT to remotely diagnose and repair 30 percent fewer issues without an on-site visit. Example : 10 calls x 30% x 4 hours = 12 man-hours saved per week Step 3 : Develop a quantifiable metric; subtract the amount of time required per workweek times the burden rate for a field service technician to determine labor cost savings. Example : 12 hours per week x $100 per hour = $1,200 in savings per workweek. Step 4 : Determine the impact across the entire field service organization. Example : Assuming 100 technicians x 50 workweeks x $1,200 per workweek = $6,000,000 annual savings 3 Business Benefits Product Tracking : The Internet of Things can help manufacturers easily track products such as raw materials, finished goods, parts and more. Sensors can be used to get real-time updates regarding them, allowing companies to optimize logistics to streamline and accelerate the process and cut unwanted costs. Tracking products in real time allows companies to maintain the quality of their finished goods, maintain inventory levels and even prevent thefts. Use Case : A manufacturing company required an advanced system for tracking their raw materials while they were being transported. Using RFID tags, the company was able to track the exact location of the materials, allowing them to start production immediately after they arrived at the location without wasting time. Real-time product tracking not only helps the company improve its efficiency, but also helps them save up on time and costs. Predictive Maintenance : Accurately predict the maintenance cycle of your devices, machines and their components by analyzing historical data. Analysis of connected product data will uncover patterns that are early indicators of failures. Rather than performing preventive maintenance on a calendar basis when it may not be needed, companies can track exactly how much a device has been used and if it’s time for service; thereby eliminating unnecessary preventive maintenance calls and premature repairs or component replacement. Service reps can also perform preventive maintenance during scheduled calls, reducing unplanned and planned downtime and customer interruption. This predictive maintenance knowledge can then feed increased revenues by providing increased uptime with premium SLA pricing. Use Case : A factory is turned into a smart unit by installing vibration and noise sensors on machines and other high-end assets. These sensors effectively collect data regarding the working of the machines as well as their components. The data is analyzed in real-time to find out when a machine failure is likely to happen and also to predict the breakdown of a machine component or part. This helps the factory to carry out maintenance in advance to avoid downtime. Improved Product Design : The understanding gained from real end-user behavior and usage patterns also allows product managers and engineers to design better products and prioritize new features, as well as drive an increased market share by offering a superior product design. The company can utilize this data to define the next-generation of product requirements and ensure that they design a product that takes into consideration customer feedback. Use Case : A manufacturer of smart watches installed sensors to collect information in order to gain insights regarding consumer usage. It found that most consumers are rough users and end up damaging their watches pretty often. This insight prompted the company to change the material used to design their watches and make them capable of enduring rough usage. Identification of Quality Issues : By looking at the trends across multiple systems, you can reduce costs by identifying any quality issues or design flaws in parts supplied by third parties or within your own manufacturing processes, allowing you to understand what is causing downtime for customers. Understanding the relationships between problems and specific batches or production runs can identify a bad batch early on and streamline the recall process. It is also possible that the problems are of a more serious nature and are still part of the current manufacturing process. In this case, usage data may trigger the need to change the current manufacturing process. Use Case : A manufacturing unit ended up producing faulty goods and the fault went undetected in the testing stages. The first batch of product was delivered and the noise sensors attached to them sent out notifications to the company regarding the unwanted noise being produced. This data prompted the company to test the product again. It was then found that a certain component within the product was not working properly and hence, the company immediately recalled all of its batches. The fault was rectified in the manufacturing unit and the new batch was then delivered. Dynamic Route Planning Manufacturing units use a GPS-based vehicle tracking system to collect accurate location data of their delivery vehicles in real-time. This data is collected at a centralized location and can be analyzed for optimizing the routes by suggesting the best or an alternative route to the driver. Various factors such as traffic situation and the condition of the road can be taken into consideration before suggesting another route to ensure faster delivery of the consignment. Use Case : A company uses dynamic route planning to deliver their goods to the retailers as fast as possible. All the location data is collected on the cloud and is analyzed by a team to ensure that the stores that need to replenish their inventory immediately, receive the products before the ones which have some stock left. Moreover, the team also takes into consideration the traffic situation through reliable applications and suggests new routes to the vehicle drivers to save time and fuel. Keeping Energy Consumption in Check Keeping tabs on the energy consumption in a factory is a pre-requisite as it can help reduce the cost to a great extent. New age components are used to find out how much power or fuel is being used by a certain machine or equipment and the collected data can be analyzed to check if it is more than the required amount. Use Case : A company decided to use the smart power monitor system to detect how much power is used by every machine in the factory as well as incorrect wiring. An alarm goes off as soon as these faults are identified, which is detected by the noise sensors. These sensors are programmed to send out alerts in order to keep power consumption in check. Warranty Management The Internet of Things can help manufacturers manage warranty costs efficiently by identifying if the machine failure is a manufacturing fault or something to do with the way the product was used. It has a huge potential for manufacturers supplying equipment to factories and can help companies save up on their maintenance expenditure and even generate revenue for their services. One of the main advantages of warranty management is that it helps avoid fraudulent claims. Use Case : A factory equipment manufacturer installed temperature and humidity sensors on its products to detect the conditions of the unit where they are being used. On receiving a call from its client for maintenance during the warranty period, the manufacturer checked the conditions using the data collected by the sensors and found that the company was not adhering to the parameters set in the warranty conditions. Due to this, the company informed the client that the warranty’s conditions were not met and repairs would mean an additional charge for the client. 4 OPTIMIZED BUSINESS PROCESSES The Value of Product Data Integration and Business Process Efficiency: Organizations, and particularly manufacturing units, who have now connected things/assets/entities over the Internet, are taking the advantage of IoT by pulling real time, accurate data into enterprise systems like CRM, ERP or data warehouses. IoT data from connected assets, in collaboration with other enterprise systems, can provide visible automation across the organization. Additionally, integration with quality assurance (QA) or, product lifecycle management (PLM) can help enhance product features based on real-world data that shows usage patterns or equipment issues—helping to improve customer satisfaction and streamlining beta programs. Measuring critical data points in a device allows for notifications to the service team if there is a risk of failure, and, simultaneously, the finance department can be informed when warranty guidelines are not being upheld. It optimizes critical business processes, reduces service call times, warranty claims etc. The real value delivered with this coherent unit is described in the table below. How to set up a smart factory with the Internet of Things (IoT) 07 The value proposition of IoT falls into several buckets of capabilities that differentiate your products, including remote monitoring, remote service, usage analysis, ERP/CRM integration, and value-added services. Core business processes like billing, field service, product registration, compliance, consumable management, recalls, and warranty management can all be improved with connected product data. And finally, the selling and marketing of connected products, which include new applications for end users, can deliver a competitive advantage and drive revenue growth. 1 Increased Product Revenue IoT enablement bears fruits through direct as well as in-direct revenue streams as described below with examples. Based on the value-added services that can be enabled by IoT, company ABC estimates that a connected product line could generate an additional revenue stream. Assuming customers will subscribe to these services within the first year of product ownership, here is a sample calculation of increased revenue: Step 1 : Determine the value of connected product services for each product unit assuming the average selling price of a connected application is $50 per year per user, and the average number of users per connected product is 20. Example : $50 x 20 users per product = $1,000 per product. Step 2 : Estimate the total product revenue increase. Assuming a 25 percent attach rate on a total product unit volume of 100,000, the increase in product revenue for the new connected application would be 100,000 units x 25% x $1,000 = $25,000,000 2 Saving on Labor Costs Example : ABC Company estimated that each field service technician deployed in the field has a capacity of ten on-site customer visits per week. The expected results for implementing remote service would be a reduction in total on-site visits by 30 percent. The burden rate for a field service technician is $100 per hour. Step 1 : Determine the number of visits per week, assuming that an average field-service visit at a customer location is four hours long. Example : 40 hours per week/4 hours per visit = 10 calls on average per field service technician per week Step 2 : Determine the man-hours saved by using IoT to remotely diagnose and repair 30 percent fewer issues without an on-site visit. Example : 10 calls x 30% x 4 hours = 12 man-hours saved per week Step 3 : Develop a quantifiable metric; subtract the amount of time required per workweek times the burden rate for a field service technician to determine labor cost savings. Example : 12 hours per week x $100 per hour = $1,200 in savings per workweek. Step 4 : Determine the impact across the entire field service organization. Example : Assuming 100 technicians x 50 workweeks x $1,200 per workweek = $6,000,000 annual savings 3 Business Benefits Product Tracking : The Internet of Things can help manufacturers easily track products such as raw materials, finished goods, parts and more. Sensors can be used to get real-time updates regarding them, allowing companies to optimize logistics to streamline and accelerate the process and cut unwanted costs. Tracking products in real time allows companies to maintain the quality of their finished goods, maintain inventory levels and even prevent thefts. Use Case : A manufacturing company required an advanced system for tracking their raw materials while they were being transported. Using RFID tags, the company was able to track the exact location of the materials, allowing them to start production immediately after they arrived at the location without wasting time. Real-time product tracking not only helps the company improve its efficiency, but also helps them save up on time and costs. Predictive Maintenance : Accurately predict the maintenance cycle of your devices, machines and their components by analyzing historical data. Analysis of connected product data will uncover patterns that are early indicators of failures. Rather than performing preventive maintenance on a calendar basis when it may not be needed, companies can track exactly how much a device has been used and if it’s time for service; thereby eliminating unnecessary preventive maintenance calls and premature repairs or component replacement. Service reps can also perform preventive maintenance during scheduled calls, reducing unplanned and planned downtime and customer interruption. This predictive maintenance knowledge can then feed increased revenues by providing increased uptime with premium SLA pricing. Use Case : A factory is turned into a smart unit by installing vibration and noise sensors on machines and other high-end assets. These sensors effectively collect data regarding the working of the machines as well as their components. The data is analyzed in real-time to find out when a machine failure is likely to happen and also to predict the breakdown of a machine component or part. This helps the factory to carry out maintenance in advance to avoid downtime. Improved Product Design : The understanding gained from real end-user behavior and usage patterns also allows product managers and engineers to design better products and prioritize new features, as well as drive an increased market share by offering a superior product design. The company can utilize this data to define the next-generation of product requirements and ensure that they design a product that takes into consideration customer feedback. Use Case : A manufacturer of smart watches installed sensors to collect information in order to gain insights regarding consumer usage. It found that most consumers are rough users and end up damaging their watches pretty often. This insight prompted the company to change the material used to design their watches and make them capable of enduring rough usage. Identification of Quality Issues : By looking at the trends across multiple systems, you can reduce costs by identifying any quality issues or design flaws in parts supplied by third parties or within your own manufacturing processes, allowing you to understand what is causing downtime for customers. Understanding the relationships between problems and specific batches or production runs can identify a bad batch early on and streamline the recall process. It is also possible that the problems are of a more serious nature and are still part of the current manufacturing process. In this case, usage data may trigger the need to change the current manufacturing process. Use Case : A manufacturing unit ended up producing faulty goods and the fault went undetected in the testing stages. The first batch of product was delivered and the noise sensors attached to them sent out notifications to the company regarding the unwanted noise being produced. This data prompted the company to test the product again. It was then found that a certain component within the product was not working properly and hence, the company immediately recalled all of its batches. The fault was rectified in the manufacturing unit and the new batch was then delivered. Dynamic Route Planning Manufacturing units use a GPS-based vehicle tracking system to collect accurate location data of their delivery vehicles in real-time. This data is collected at a centralized location and can be analyzed for optimizing the routes by suggesting the best or an alternative route to the driver. Various factors such as traffic situation and the condition of the road can be taken into consideration before suggesting another route to ensure faster delivery of the consignment. Use Case : A company uses dynamic route planning to deliver their goods to the retailers as fast as possible. All the location data is collected on the cloud and is analyzed by a team to ensure that the stores that need to replenish their inventory immediately, receive the products before the ones which have some stock left. Moreover, the team also takes into consideration the traffic situation through reliable applications and suggests new routes to the vehicle drivers to save time and fuel. Keeping Energy Consumption in Check Keeping tabs on the energy consumption in a factory is a pre-requisite as it can help reduce the cost to a great extent. New age components are used to find out how much power or fuel is being used by a certain machine or equipment and the collected data can be analyzed to check if it is more than the required amount. Use Case : A company decided to use the smart power monitor system to detect how much power is used by every machine in the factory as well as incorrect wiring. An alarm goes off as soon as these faults are identified, which is detected by the noise sensors. These sensors are programmed to send out alerts in order to keep power consumption in check. Warranty Management The Internet of Things can help manufacturers manage warranty costs efficiently by identifying if the machine failure is a manufacturing fault or something to do with the way the product was used. It has a huge potential for manufacturers supplying equipment to factories and can help companies save up on their maintenance expenditure and even generate revenue for their services. One of the main advantages of warranty management is that it helps avoid fraudulent claims. Use Case : A factory equipment manufacturer installed temperature and humidity sensors on its products to detect the conditions of the unit where they are being used. On receiving a call from its client for maintenance during the warranty period, the manufacturer checked the conditions using the data collected by the sensors and found that the company was not adhering to the parameters set in the warranty conditions. Due to this, the company informed the client that the warranty’s conditions were not met and repairs would mean an additional charge for the client. 4 OPTIMIZED BUSINESS PROCESSES The Value of Product Data Integration and Business Process Efficiency: Organizations, and particularly manufacturing units, who have now connected things/assets/entities over the Internet, are taking the advantage of IoT by pulling real time, accurate data into enterprise systems like CRM, ERP or data warehouses. IoT data from connected assets, in collaboration with other enterprise systems, can provide visible automation across the organization. Additionally, integration with quality assurance (QA) or, product lifecycle management (PLM) can help enhance product features based on real-world data that shows usage patterns or equipment issues—helping to improve customer satisfaction and streamlining beta programs. Measuring critical data points in a device allows for notifications to the service team if there is a risk of failure, and, simultaneously, the finance department can be informed when warranty guidelines are not being upheld. It optimizes critical business processes, reduces service call times, warranty claims etc. The real value delivered with this coherent unit is described in the table below. How to set up a smart factory with the Internet of Things (IoT) 08 The value proposition of IoT falls into several buckets of capabilities that differentiate your products, including remote monitoring, remote service, usage analysis, ERP/CRM integration, and value-added services. Core business processes like billing, field service, product registration, compliance, consumable management, recalls, and warranty management can all be improved with connected product data. And finally, the selling and marketing of connected products, which include new applications for end users, can deliver a competitive advantage and drive revenue growth. 1 Increased Product Revenue IoT enablement bears fruits through direct as well as in-direct revenue streams as described below with examples. Based on the value-added services that can be enabled by IoT, company ABC estimates that a connected product line could generate an additional revenue stream. Assuming customers will subscribe to these services within the first year of product ownership, here is a sample calculation of increased revenue: Step 1 : Determine the value of connected product services for each product unit assuming the average selling price of a connected application is $50 per year per user, and the average number of users per connected product is 20. Example : $50 x 20 users per product = $1,000 per product. Step 2 : Estimate the total product revenue increase. Assuming a 25 percent attach rate on a total product unit volume of 100,000, the increase in product revenue for the new connected application would be 100,000 units x 25% x $1,000 = $25,000,000 2 Saving on Labor Costs Example : ABC Company estimated that each field service technician deployed in the field has a capacity of ten on-site customer visits per week. The expected results for implementing remote service would be a reduction in total on-site visits by 30 percent. The burden rate for a field service technician is $100 per hour. Step 1 : Determine the number of visits per week, assuming that an average field-service visit at a customer location is four hours long. Example : 40 hours per week/4 hours per visit = 10 calls on average per field service technician per week Step 2 : Determine the man-hours saved by using IoT to remotely diagnose and repair 30 percent fewer issues without an on-site visit. Example : 10 calls x 30% x 4 hours = 12 man-hours saved per week Step 3 : Develop a quantifiable metric; subtract the amount of time required per workweek times the burden rate for a field service technician to determine labor cost savings. Example : 12 hours per week x $100 per hour = $1,200 in savings per workweek. Step 4 : Determine the impact across the entire field service organization. Example : Assuming 100 technicians x 50 workweeks x $1,200 per workweek = $6,000,000 annual savings 3 Business Benefits Product Tracking : The Internet of Things can help manufacturers easily track products such as raw materials, finished goods, parts and more. Sensors can be used to get real-time updates regarding them, allowing companies to optimize logistics to streamline and accelerate the process and cut unwanted costs. Tracking products in real time allows companies to maintain the quality of their finished goods, maintain inventory levels and even prevent thefts. Use Case : A manufacturing company required an advanced system for tracking their raw materials while they were being transported. Using RFID tags, the company was able to track the exact location of the materials, allowing them to start production immediately after they arrived at the location without wasting time. Real-time product tracking not only helps the company improve its efficiency, but also helps them save up on time and costs. Predictive Maintenance : Accurately predict the maintenance cycle of your devices, machines and their components by analyzing historical data. Analysis of connected product data will uncover patterns that are early indicators of failures. Rather than performing preventive maintenance on a calendar basis when it may not be needed, companies can track exactly how much a device has been used and if it’s time for service; thereby eliminating unnecessary preventive maintenance calls and premature repairs or component replacement. Service reps can also perform preventive maintenance during scheduled calls, reducing unplanned and planned downtime and customer interruption. This predictive maintenance knowledge can then feed increased revenues by providing increased uptime with premium SLA pricing. Use Case : A factory is turned into a smart unit by installing vibration and noise sensors on machines and other high-end assets. These sensors effectively collect data regarding the working of the machines as well as their components. The data is analyzed in real-time to find out when a machine failure is likely to happen and also to predict the breakdown of a machine component or part. This helps the factory to carry out maintenance in advance to avoid downtime. Improved Product Design : The understanding gained from real end-user behavior and usage patterns also allows product managers and engineers to design better products and prioritize new features, as well as drive an increased market share by offering a superior product design. The company can utilize this data to define the next-generation of product requirements and ensure that they design a product that takes into consideration customer feedback. Use Case : A manufacturer of smart watches installed sensors to collect information in order to gain insights regarding consumer usage. It found that most consumers are rough users and end up damaging their watches pretty often. This insight prompted the company to change the material used to design their watches and make them capable of enduring rough usage. Identification of Quality Issues : By looking at the trends across multiple systems, you can reduce costs by identifying any quality issues or design flaws in parts supplied by third parties or within your own manufacturing processes, allowing you to understand what is causing downtime for customers. Understanding the relationships between problems and specific batches or production runs can identify a bad batch early on and streamline the recall process. It is also possible that the problems are of a more serious nature and are still part of the current manufacturing process. In this case, usage data may trigger the need to change the current manufacturing process. Use Case : A manufacturing unit ended up producing faulty goods and the fault went undetected in the testing stages. The first batch of product was delivered and the noise sensors attached to them sent out notifications to the company regarding the unwanted noise being produced. This data prompted the company to test the product again. It was then found that a certain component within the product was not working properly and hence, the company immediately recalled all of its batches. The fault was rectified in the manufacturing unit and the new batch was then delivered. Dynamic Route Planning Manufacturing units use a GPS-based vehicle tracking system to collect accurate location data of their delivery vehicles in real-time. This data is collected at a centralized location and can be analyzed for optimizing the routes by suggesting the best or an alternative route to the driver. Various factors such as traffic situation and the condition of the road can be taken into consideration before suggesting another route to ensure faster delivery of the consignment. Use Case : A company uses dynamic route planning to deliver their goods to the retailers as fast as possible. All the location data is collected on the cloud and is analyzed by a team to ensure that the stores that need to replenish their inventory immediately, receive the products before the ones which have some stock left. Moreover, the team also takes into consideration the traffic situation through reliable applications and suggests new routes to the vehicle drivers to save time and fuel. Keeping Energy Consumption in Check Keeping tabs on the energy consumption in a factory is a pre-requisite as it can help reduce the cost to a great extent. New age components are used to find out how much power or fuel is being used by a certain machine or equipment and the collected data can be analyzed to check if it is more than the required amount. Use Case : A company decided to use the smart power monitor system to detect how much power is used by every machine in the factory as well as incorrect wiring. An alarm goes off as soon as these faults are identified, which is detected by the noise sensors. These sensors are programmed to send out alerts in order to keep power consumption in check. Warranty Management The Internet of Things can help manufacturers manage warranty costs efficiently by identifying if the machine failure is a manufacturing fault or something to do with the way the product was used. It has a huge potential for manufacturers supplying equipment to factories and can help companies save up on their maintenance expenditure and even generate revenue for their services. One of the main advantages of warranty management is that it helps avoid fraudulent claims. Use Case : A factory equipment manufacturer installed temperature and humidity sensors on its products to detect the conditions of the unit where they are being used. On receiving a call from its client for maintenance during the warranty period, the manufacturer checked the conditions using the data collected by the sensors and found that the company was not adhering to the parameters set in the warranty conditions. Due to this, the company informed the client that the warranty’s conditions were not met and repairs would mean an additional charge for the client. 4 OPTIMIZED BUSINESS PROCESSES The Value of Product Data Integration and Business Process Efficiency: Organizations, and particularly manufacturing units, who have now connected things/assets/entities over the Internet, are taking the advantage of IoT by pulling real time, accurate data into enterprise systems like CRM, ERP or data warehouses. IoT data from connected assets, in collaboration with other enterprise systems, can provide visible automation across the organization. Additionally, integration with quality assurance (QA) or, product lifecycle management (PLM) can help enhance product features based on real-world data that shows usage patterns or equipment issues—helping to improve customer satisfaction and streamlining beta programs. Measuring critical data points in a device allows for notifications to the service team if there is a risk of failure, and, simultaneously, the finance department can be informed when warranty guidelines are not being upheld. It optimizes critical business processes, reduces service call times, warranty claims etc. The real value delivered with this coherent unit is described in the table below. How to set up a smart factory with the Internet of Things (IoT) The value proposition of IoT falls into several buckets of capabilities that differentiate your products, including remote monitoring, remote service, usage analysis, ERP/CRM integration, and value-added services. Core business processes like billing, field service, product registration, compliance, consumable management, recalls, and warranty management can all be improved with connected product data. And finally, the selling and marketing of connected products, which include new applications for end users, can deliver a competitive advantage and drive revenue growth. Benefits Effective troubleshooting and CRM efficiency increased Reduction in warranty claims and warranty service costs More efficient recalls with accurate data of which machine/product needs to be recalled Increase in sale of consumables More efficient auditing of interactions with machines, humans and decreased compliance cost Accurate data about installed equipment and configuration Proactive creation of field service request with accurate data and health status Measure Length & Frequency of support calls Number of warranty services, warranty costs Support cases of recalled products Consumable Revenue Cost of compliance Cost of configuration management Time to Resolution Business Process Customer Service Warranty Management Recall Management Consumable Management Compliance Configuration Management Field Service 1 Increased Product Revenue IoT enablement bears fruits through direct as well as in-direct revenue streams as described below with examples. Based on the value-added services that can be enabled by IoT, company ABC estimates that a connected product line could generate an additional revenue stream. Assuming customers will subscribe to these services within the first year of product ownership, here is a sample calculation of increased revenue: Step 1 : Determine the value of connected product services for each product unit assuming the average selling price of a connected application is $50 per year per user, and the average number of users per connected product is 20. Example : $50 x 20 users per product = $1,000 per product. Step 2 : Estimate the total product revenue increase. Assuming a 25 percent attach rate on a total product unit volume of 100,000, the increase in product revenue for the new connected application would be 100,000 units x 25% x $1,000 = $25,000,000 2 Saving on Labor Costs Example : ABC Company estimated that each field service technician deployed in the field has a capacity of ten on-site customer visits per week. The expected results for implementing remote service would be a reduction in total on-site visits by 30 percent. The burden rate for a field service technician is $100 per hour. Step 1 : Determine the number of visits per week, assuming that an average field-service visit at a customer location is four hours long. Example : 40 hours per week/4 hours per visit = 10 calls on average per field service technician per week Step 2 : Determine the man-hours saved by using IoT to remotely diagnose and repair 30 percent fewer issues without an on-site visit. Example : 10 calls x 30% x 4 hours = 12 man-hours saved per week Step 3 : Develop a quantifiable metric; subtract the amount of time required per workweek times the burden rate for a field service technician to determine labor cost savings. Example : 12 hours per week x $100 per hour = $1,200 in savings per workweek. Step 4 : Determine the impact across the entire field service organization. Example : Assuming 100 technicians x 50 workweeks x $1,200 per workweek = $6,000,000 annual savings 3 Business Benefits Product Tracking : The Internet of Things can help manufacturers easily track products such as raw materials, finished goods, parts and more. Sensors can be used to get real-time updates regarding them, allowing companies to optimize logistics to streamline and accelerate the process and cut unwanted costs. Tracking products in real time allows companies to maintain the quality of their finished goods, maintain inventory levels and even prevent thefts. Use Case : A manufacturing company required an advanced system for tracking their raw materials while they were being transported. Using RFID tags, the company was able to track the exact location of the materials, allowing them to start production immediately after they arrived at the location without wasting time. Real-time product tracking not only helps the company improve its efficiency, but also helps them save up on time and costs. Predictive Maintenance : Accurately predict the maintenance cycle of your devices, machines and their components by analyzing historical data. Analysis of connected product data will uncover patterns that are early indicators of failures. Rather than performing preventive maintenance on a calendar basis when it may not be needed, companies can track exactly how much a device has been used and if it’s time for service; thereby eliminating unnecessary preventive maintenance calls and premature repairs or component replacement. Service reps can also perform preventive maintenance during scheduled calls, reducing unplanned and planned downtime and customer interruption. This predictive maintenance knowledge can then feed increased revenues by providing increased uptime with premium SLA pricing. Use Case : A factory is turned into a smart unit by installing vibration and noise sensors on machines and other high-end assets. These sensors effectively collect data regarding the working of the machines as well as their components. The data is analyzed in real-time to find out when a machine failure is likely to happen and also to predict the breakdown of a machine component or part. This helps the factory to carry out maintenance in advance to avoid downtime. Improved Product Design : The understanding gained from real end-user behavior and usage patterns also allows product managers and engineers to design better products and prioritize new features, as well as drive an increased market share by offering a superior product design. The company can utilize this data to define the next-generation of product requirements and ensure that they design a product that takes into consideration customer feedback. Use Case : A manufacturer of smart watches installed sensors to collect information in order to gain insights regarding consumer usage. It found that most consumers are rough users and end up damaging their watches pretty often. This insight prompted the company to change the material used to design their watches and make them capable of enduring rough usage. Identification of Quality Issues : By looking at the trends across multiple systems, you can reduce costs by identifying any quality issues or design flaws in parts supplied by third parties or within your own manufacturing processes, allowing you to understand what is causing downtime for customers. Understanding the relationships between problems and specific batches or production runs can identify a bad batch early on and streamline the recall process. It is also possible that the problems are of a more serious nature and are still part of the current manufacturing process. In this case, usage data may trigger the need to change the current manufacturing process. Use Case : A manufacturing unit ended up producing faulty goods and the fault went undetected in the testing stages. The first batch of product was delivered and the noise sensors attached to them sent out notifications to the company regarding the unwanted noise being produced. This data prompted the company to test the product again. It was then found that a certain component within the product was not working properly and hence, the company immediately recalled all of its batches. The fault was rectified in the manufacturing unit and the new batch was then delivered. Dynamic Route Planning Manufacturing units use a GPS-based vehicle tracking system to collect accurate location data of their delivery vehicles in real-time. This data is collected at a centralized location and can be analyzed for optimizing the routes by suggesting the best or an alternative route to the driver. Various factors such as traffic situation and the condition of the road can be taken into consideration before suggesting another route to ensure faster delivery of the consignment. Use Case : A company uses dynamic route planning to deliver their goods to the retailers as fast as possible. All the location data is collected on the cloud and is analyzed by a team to ensure that the stores that need to replenish their inventory immediately, receive the products before the ones which have some stock left. Moreover, the team also takes into consideration the traffic situation through reliable applications and suggests new routes to the vehicle drivers to save time and fuel. Keeping Energy Consumption in Check Keeping tabs on the energy consumption in a factory is a pre-requisite as it can help reduce the cost to a great extent. New age components are used to find out how much power or fuel is being used by a certain machine or equipment and the collected data can be analyzed to check if it is more than the required amount. Use Case : A company decided to use the smart power monitor system to detect how much power is used by every machine in the factory as well as incorrect wiring. An alarm goes off as soon as 09 35% 35% of manufacturers in the US have started utilizing data collected by smart sensors to streamline the manufacturing process 38% About 38% of them have already installed sensors in their goods to allow users to gather sensor-generated data Source: PwC 34% 34% of manufacturers currently believe that it is critical to adopt the Internet of Things to optimize operations these faults are identified, which is detected by the noise sensors. These sensors are programmed to send out alerts in order to keep power consumption in check. Warranty Management The Internet of Things can help manufacturers manage warranty costs efficiently by identifying if the machine failure is a manufacturing fault or something to do with the way the product was used. It has a huge potential for manufacturers supplying equipment to factories and can help companies save up on their maintenance expenditure and even generate revenue for their services. One of the main advantages of warranty management is that it helps avoid fraudulent claims. Use Case : A factory equipment manufacturer installed temperature and humidity sensors on its products to detect the conditions of the unit where they are being used. On receiving a call from its client for maintenance during the warranty period, the manufacturer checked the conditions using the data collected by the sensors and found that the company was not adhering to the parameters set in the warranty conditions. Due to this, the company informed the client that the warranty’s conditions were not met and repairs would mean an additional charge for the client. 4 OPTIMIZED BUSINESS PROCESSES The Value of Product Data Integration and Business Process Efficiency: Organizations, and particularly manufacturing units, who have now connected things/assets/entities over the Internet, are taking the advantage of IoT by pulling real time, accurate data into enterprise systems like CRM, ERP or data warehouses. IoT data from connected assets, in collaboration with other enterprise systems, can provide visible automation across the organization. Additionally, integration with quality assurance (QA) or, product lifecycle management (PLM) can help enhance product features based on real-world data that shows usage patterns or equipment issues—helping to improve customer satisfaction and streamlining beta programs. Measuring critical data points in a device allows for notifications to the service team if there is a risk of failure, and, simultaneously, the finance department can be informed when warranty guidelines are not being upheld. It optimizes critical business processes, reduces service call times, warranty claims etc. The real value delivered with this coherent unit is described in the table below. How to set up a smart factory with the Internet of Things (IoT) 10 While machine to machine communication has been around for a while now and a number of manufacturers have leveraged it, the IoT remains a new concept due to the components it uses. With the advancement in technology, the industry is growing at an exponential rate and offering the essential components at relatively low costs, making it easy for all types of manufacturers to adopt it. Sensors Sensors are basically the driving force behind the Internet of Things ecosystem in manufacturing. They consolidate data in real time and have the ability to integrate with direct database systems, legacy ERP systems or data warehouses. Network Connectivity Unlike a few years ago, Internet connectivity is reliable and affordable, allowing manufacturers to deploy it in their units. Existing standards such as Bluetooth, Wi-Fi, BLE, RFID, ZigBee, Z-wave and IPv6 are now widely used in IoT enabled factories. Other emerging standards are 6LoWPAN, Weightless and 802.11ah which are being promoted by some device manufacturers. Companies interested in implementing IoT in their factories have a whole range of network standards to choose from and deciding which one is right for you depends upon several factors such as existing infrastructure, your IT team’s expertise with the above mentioned standards and device compatibility. IoT Platform An IoT platform is the most important part of a smart factory. Before directly jumping on to the IoT bandwagon, it is very important to ensure that you have a favorable, open architecture in place. For businesses, a security breach and lack of connectivity can be critical flaws, which can be prevented by taking a strategic approach for IoT initiatives. Choosing an appropriate IoT platform is an integral step in an IoT strategy, as it will facilitate monitoring as well as controlling different data points from a variety of sensors. It’s also important for building machine-to-machine (M2M) applications to meet digital business requirements. An IoT platform will connect access points and data networks to end-user applications, which allows companies to automate their processes and analyze data. In other words, IoT platforms act as middleware solutions that connect the data collected at the edge and the user-facing SaaS or mobile app. An IoT solution will involve many functions, which include: Sensors and controllers A gateway device to collect data and send them back to the server A communication network to transmit data Data analytics and data visualization software A user facing application IoTConnect is a Platform as a Service (PaaS) from Softweb Solutions. This horizontal IoT platform allows for device communication and management, data storage, app creation and enablement, robust security protocols and implementation of data science methodologies. It is a multi-purpose middleware platform developed on open source technologies. IoTConnect gives factories the following capabilities Manage multiple connected devices Set up cross-device connectivity Data visualization reports Perform remote device provisioning and configuration Perform real-time device monitoring Distribute over-the-air firmware updates Create cloud services for smart products Collect and analyze sensor data Analyze user behavior and deliver targeted notifications Data Analytics Data analytics is the science of analyzing large amounts of data that has been gathered in order to uncover patterns and other insights that are overlooked by humans. The concept of analyzing big data is not new, but the availability of cloud based storage and analytics tools such as Microsoft Azure and Amazon Web Services among others means that even medium sized manufacturers can now take advantage of data analytics. Data Visualizations The data that has been gathered needs to be converted into easy to understand graphs and reports. This is where data visualizations come into the picture. There are plenty of data visualization tools available in the market today such as Tableau, D3.js, Power BI, R and Python which are used by companies to identify new patterns by explaining concepts clearly and deeply. With interactive visualizations you can conceptualize future business strategies by drilling down into charts and graphs. Essential Components for IoT in Manufacturing Tableau is a very effective tool to create interactive data visualizations quickly. It is simple and user-friendly, and can be used by anyone as this tool is designed to be used by developers as well as non-developers. Companies can use Tableau to explore and find quick patterns with various combinations. D3.js is a JavaScript library that is used for data visualization. To convert unstructured data collected from sources like government sources, social networking, eCommerce portals, etc. into some usable form or some sort of productive or understandable form, D3.js is a very convenient tool. Power BI allows developers to create visualizations and display data in a very accurate way. It can be done with minimal efforts and using existing skills. The Power BI Desktop has a large variety of standard visualizations that include a range of reports that companies usually need. R is a widely popular statistical language that is used by data scientists to perform statistical analysis and predictive analytics. This includes statistical tests, time-series analysis, linear and nonlinear modeling, classification, clustering, etc. It can be used with Power BI as well as Tableau. How to set up a smart factory with the Internet of Things (IoT) 11 While machine to machine communication has been around for a while now and a number of manufacturers have leveraged it, the IoT remains a new concept due to the components it uses. With the advancement in technology, the industry is growing at an exponential rate and offering the essential components at relatively low costs, making it easy for all types of manufacturers to adopt it. Sensors Sensors are basically the driving force behind the Internet of Things ecosystem in manufacturing. They consolidate data in real time and have the ability to integrate with direct database systems, legacy ERP systems or data warehouses. Network Connectivity Unlike a few years ago, Internet connectivity is reliable and affordable, allowing manufacturers to deploy it in their units. Existing standards such as Bluetooth, Wi-Fi, BLE, RFID, ZigBee, Z-wave and IPv6 are now widely used in IoT enabled factories. Other emerging standards are 6LoWPAN, Weightless and 802.11ah which are being promoted by some device manufacturers. Companies interested in implementing IoT in their factories have a whole range of network standards to choose from and deciding which one is right for you depends upon several factors such as existing infrastructure, your IT team’s expertise with the above mentioned standards and device compatibility. IoT Platform An IoT platform is the most important part of a smart factory. Before directly jumping on to the IoT bandwagon, it is very important to ensure that you have a favorable, open architecture in place. For businesses, a security breach and lack of connectivity can be critical flaws, which can be prevented by taking a strategic approach for IoT initiatives. Choosing an appropriate IoT platform is an integral step in an IoT strategy, as it will facilitate monitoring as well as controlling different data points from a variety of sensors. It’s also important for building machine-to-machine (M2M) applications to meet digital business requirements. An IoT platform will connect access points and data networks to end-user applications, which allows companies to automate their processes and analyze data. In other words, IoT platforms act as middleware solutions that connect the data collected at the edge and the user-facing SaaS or mobile app. An IoT solution will involve many functions, which include: Sensors and controllers A gateway device to collect data and send them back to the server A communication network to transmit data Data analytics and data visualization software A user facing application IoTConnect is a Platform as a Service (PaaS) from Softweb Solutions. This horizontal IoT platform allows for device communication and management, data storage, app creation and enablement, robust security protocols and implementation of data science methodologies. It is a multi-purpose middleware platform developed on open source technologies. IoTConnect gives factories the following capabilities Manage multiple connected devices Set up cross-device connectivity Data visualization reports Perform remote device provisioning and configuration Perform real-time device monitoring Distribute over-the-air firmware updates Create cloud services for smart products Collect and analyze sensor data Analyze user behavior and deliver targeted notifications Data Analytics Data analytics is the science of analyzing large amounts of data that has been gathered in order to uncover patterns and other insights that are overlooked by humans. The concept of analyzing big data is not new, but the availability of cloud based storage and analytics tools such as Microsoft Azure and Amazon Web Services among others means that even medium sized manufacturers can now take advantage of data analytics. Data Visualizations The data that has been gathered needs to be converted into easy to understand graphs and reports. This is where data visualizations come into the picture. There are plenty of data visualization tools available in the market today such as Tableau, D3.js, Power BI, R and Python which are used by companies to identify new patterns by explaining concepts clearly and deeply. With interactive visualizations you can conceptualize future business strategies by drilling down into charts and graphs. Tableau is a very effective tool to create interactive data visualizations quickly. It is simple and user-friendly, and can be used by anyone as this tool is designed to be used by developers as well as non-developers. Companies can use Tableau to explore and find quick patterns with various combinations. D3.js is a JavaScript library that is used for data visualization. To convert unstructured data collected from sources like government sources, social networking, eCommerce portals, etc. into some usable form or some sort of productive or understandable form, D3.js is a very convenient tool. Power BI allows developers to create visualizations and display data in a very accurate way. It can be done with minimal efforts and using existing skills. The Power BI Desktop has a large variety of standard visualizations that include a range of reports that companies usually need. R is a widely popular statistical language that is used by data scientists to perform statistical analysis and predictive analytics. This includes statistical tests, time-series analysis, linear and nonlinear modeling, classification, clustering, etc. It can be used with Power BI as well as Tableau. How to set up a smart factory with the Internet of Things (IoT) 12 While machine to machine communication has been around for a while now and a number of manufacturers have leveraged it, the IoT remains a new concept due to the components it uses. With the advancement in technology, the industry is growing at an exponential rate and offering the essential components at relatively low costs, making it easy for all types of manufacturers to adopt it. Sensors Sensors are basically the driving force behind the Internet of Things ecosystem in manufacturing. They consolidate data in real time and have the ability to integrate with direct database systems, legacy ERP systems or data warehouses. Network Connectivity Unlike a few years ago, Internet connectivity is reliable and affordable, allowing manufacturers to deploy it in their units. Existing standards such as Bluetooth, Wi-Fi, BLE, RFID, ZigBee, Z-wave and IPv6 are now widely used in IoT enabled factories. Other emerging standards are 6LoWPAN, Weightless and 802.11ah which are being promoted by some device manufacturers. Companies interested in implementing IoT in their factories have a whole range of network standards to choose from and deciding which one is right for you depends upon several factors such as existing infrastructure, your IT team’s expertise with the above mentioned standards and device compatibility. IoT Platform An IoT platform is the most important part of a smart factory. Before directly jumping on to the IoT bandwagon, it is very important to ensure that you have a favorable, open architecture in place. For businesses, a security breach and lack of connectivity can be critical flaws, which can be prevented by taking a strategic approach for IoT initiatives. Choosing an appropriate IoT platform is an integral step in an IoT strategy, as it will facilitate monitoring as well as controlling different data points from a variety of sensors. It’s also important for building machine-to-machine (M2M) applications to meet digital business requirements. An IoT platform will connect access points and data networks to end-user applications, which allows companies to automate their processes and analyze data. In other words, IoT platforms act as middleware solutions that connect the data collected at the edge and the user-facing SaaS or mobile app. An IoT solution will involve many functions, which include: Sensors and controllers A gateway device to collect data and send them back to the server A communication network to transmit data Data analytics and data visualization software A user facing application IoTConnect is a Platform as a Service (PaaS) from Softweb Solutions. This horizontal IoT platform allows for device communication and management, data storage, app creation and enablement, robust security protocols and implementation of data science methodologies. It is a multi-purpose middleware platform developed on open source technologies. IoTConnect gives factories the following capabilities Manage multiple connected devices Set up cross-device connectivity Data visualization reports Perform remote device provisioning and configuration Perform real-time device monitoring Distribute over-the-air firmware updates Create cloud services for smart products Collect and analyze sensor data Analyze user behavior and deliver targeted notifications Data Analytics Data analytics is the science of analyzing large amounts of data that has been gathered in order to uncover patterns and other insights that are overlooked by humans. The concept of analyzing big data is not new, but the availability of cloud based storage and analytics tools such as Microsoft Azure and Amazon Web Services among others means that even medium sized manufacturers can now take advantage of data analytics. Data Visualizations The data that has been gathered needs to be converted into easy to understand graphs and reports. This is where data visualizations come into the picture. There are plenty of data visualization tools available in the market today such as Tableau, D3.js, Power BI, R and Python which are used by companies to identify new patterns by explaining concepts clearly and deeply. With interactive visualizations you can conceptualize future business strategies by drilling down into charts and graphs. Tableau is a very effective tool to create interactive data visualizations quickly. It is simple and user-friendly, and can be used by anyone as this tool is designed to be used by developers as well as non-developers. Companies can use Tableau to explore and find quick patterns with various combinations. D3.js is a JavaScript library that is used for data visualization. To convert unstructured data collected from sources like government sources, social networking, eCommerce portals, etc. into some usable form or some sort of productive or understandable form, D3.js is a very convenient tool. Power BI allows developers to create visualizations and display data in a very accurate way. It can be done with minimal efforts and using existing skills. The Power BI Desktop has a large variety of standard visualizations that include a range of reports that companies usually need. R is a widely popular statistical language that is used by data scientists to perform statistical analysis and predictive analytics. This includes statistical tests, time-series analysis, linear and nonlinear modeling, classification, clustering, etc. It can be used with Power BI as well as Tableau. How to set up a smart factory with the Internet of Things (IoT) 13 Every manufacturing company operates various production lines that consist of many critical processes. Here we identify a few common processes to present our case of an IoT enabled manufacturing unit. Manufacturing controls require continuous measurement of environment variables like temperature and pressure. Compliance regulations also make it necessary for the company to provide safe working conditions for its employees such as noise level of the workshop, quality of the water etc. In this case we are describing all the components, processes and the final outcome of the IoT implementation involved in this manufacturing unit. Types of Sensors Sensors monitor critical processes environmental variables throughout the production unit, parameters that affect product quality and working conditions of the employees. Temperature sensors (Manufacturing process) Carbon emission sensors (Manufacturing process, environmental emission) Humidity sensors (Storage/Warehouse conditions) Noise sensors (Worker conditions, compliance) Vibration sensors (Machine monitoring) Micro sensors & equipment tags (Manufacturing process, machine monitoring) Occupancy sensors (Resource management, workers‘ safety) Types of Occupancy Sensors Passive infrared sensors (PIR) Ultrasonic sensors Microwave sensors Motion sensors (Workers’ safety) Fire and smoke sensors (Workers’ safety, machine monitoring) Choosing the right IoT platform The gap between the device sensors and data networks is bridged using an IoT platform with the help of backend apps to manage the data generated by hundreds of sensors. But choosing the right platform is not easy since there are many device clouds in the market today which are often classified as IoT platforms. To know more, read our article on the eight questions that you need to ask your IoT platform provider. Web & Mobile Application This is the part of the system which is directly visible to you. It is an intelligent dashboard that makes information very handy for you. Mobile apps give you quick, real time updates by means of alerts and notifications. With smart sensors you can send commands back to the devices to remotely operate them. This makes it extremely easy for you to maintain your policies and compliance standards. Analytics will be plotted on graphs and the historical data presented will be very intuitive. Business Case of IoT in Manufacturing How to set up a smart factory with the Internet of Things (IoT) 14 Let’s take a look at the working of a factory featuring all the advanced components of the Internet of Things. ABC Inc. leverages the Internet of Things and has installed multiple sensors around its premises. Sensors to detect temperature, humidity, noise, light, vibrations and volatile organic compounds are installed in the factory. Apart from these, the factory also has specialized sensors to track the working of all of its machines and equipment, to identify the location of vehicles which carry raw materials and finished goods as well as to manage the supply chain. All of the aforementioned sensors collect information and forward it to a cloud-based storage system. Principles of data science are applied to this data in order to gain deeper insights into it. These insights are then visualized and presented in the form of interactive reports and charts. Managers and other employees have been authorized to access these data visualizations from the cloud to supervise and manage the working of their respective departments. This information is used to maintain the right temperature, humidity, light and noise levels in the manufacturing unit, along with ensuring compliance with safety standards. It is easier to keep a check on the machinery and schedule maintenance if faults are detected. The Internet of Things and data science also ensure that defects are detected in the early stages and downtime can be prevented. Vehicles of ABC Inc. are monitored in real-time to ensure that the finished goods are delivered to distributors and retailers on time. Employees also ensure that they are aware of the arrival of the raw materials well in advance and are prepared to start production right away in order to avoid wasting time. New or alternative routes are suggested to drivers in order to ensure that they reach their destination without wasting time and fuel. Every manufacturing company operates various production lines that consist of many critical processes. Here we identify a few common processes to present our case of an IoT enabled manufacturing unit. Manufacturing controls require continuous measurement of environment variables like temperature and pressure. Compliance regulations also make it necessary for the company to provide safe working conditions for its employees such as noise level of the workshop, quality of the water etc. In this case we are describing all the components, processes and the final outcome of the IoT implementation involved in this manufacturing unit. Types of Sensors Sensors monitor critical processes environmental variables throughout the production unit, parameters that affect product quality and working conditions of the employees. Temperature sensors (Manufacturing process) Carbon emission sensors (Manufacturing process, environmental emission) Humidity sensors (Storage/Warehouse conditions) Noise sensors (Worker conditions, compliance) Vibration sensors (Machine monitoring) Micro sensors & equipment tags (Manufacturing process, machine monitoring) Occupancy sensors (Resource management, workers‘ safety) Types of Occupancy Sensors Passive infrared sensors (PIR) Ultrasonic sensors Microwave sensors Motion sensors (Workers’ safety) Fire and smoke sensors (Workers’ safety, machine monitoring) Choosing the right IoT platform The gap between the device sensors and data networks is bridged using an IoT platform with the help of backend apps to manage the data generated by hundreds of sensors. But choosing the right platform is not easy since there are many device clouds in the market today which are often classified as IoT platforms. To know more, read our article on the eight questions that you need to ask your IoT platform provider. Web & Mobile Application This is the part of the system which is directly visible to you. It is an intelligent dashboard that makes information very handy for you. Mobile apps give you quick, real time updates by means of alerts and notifications. With smart sensors you can send commands back to the devices to remotely operate them. This makes it extremely easy for you to maintain your policies and compliance standards. Analytics will be plotted on graphs and the historical data presented will be very intuitive. Envisioning the Working of an IoT-Enabled Company Managing the inventory is a piece of cake for the manufacturer as it knows exactly when to order the required raw material and avoid additional costs for storing extra goods. A reminder is triggered by sensors for the concerned employees to replenish the stock and avoid delays in the production of goods. The Internet of Things also efficiently connects the factory to warehouses, distribution centers, retailers, suppliers and customers to facilitate supply chain management by allowing real-time information sharing. ABC Inc. successfully saves up on costs by avoiding fuel and power wastage and scheduled maintenance. It supplies goods to distributors and retailers who are out of stock, thereby increasing sales and receives raw materials on time. Downtime is decreased to a great extent, allowing uninterrupted production in the manufacturing unit. Moreover, sensors installed on the finished goods help identify faults in products, so that they can be rectified as soon as they are detected to decrease losses and offer good quality products and services to consumers. Warranty management is another cost-saving advantage of the Internet of things for ABC Inc. How to set up a smart factory with the Internet of Things (IoT) 15 Let’s take a look at the working of a factory featuring all the advanced components of the Internet of Things. ABC Inc. leverages the Internet of Things and has installed multiple sensors around its premises. Sensors to detect temperature, humidity, noise, light, vibrations and volatile organic compounds are installed in the factory. Apart from these, the factory also has specialized sensors to track the working of all of its machines and equipment, to identify the location of vehicles which carry raw materials and finished goods as well as to manage the supply chain. All of the aforementioned sensors collect information and forward it to a cloud-based storage system. Principles of data science are applied to this data in order to gain deeper insights into it. These insights are then visualized and presented in the form of interactive reports and charts. Managers and other employees have been authorized to access these data visualizations from the cloud to supervise and manage the working of their respective departments. This information is used to maintain the right temperature, humidity, light and noise levels in the manufacturing unit, along with ensuring compliance with safety standards. It is easier to keep a check on the machinery and schedule maintenance if faults are detected. The Internet of Things and data science also ensure that defects are detected in the early stages and downtime can be prevented. Vehicles of ABC Inc. are monitored in real-time to ensure that the finished goods are delivered to distributors and retailers on time. Employees also ensure that they are aware of the arrival of the raw materials well in advance and are prepared to start production right away in order to avoid wasting time. New or alternative routes are suggested to drivers in order to ensure that they reach their destination without wasting time and fuel. At Softweb Solutions Inc., we understand that becoming an IoT enabled company is not an easy decision to make. Hence we have laid down a very systematic and gradual implementation plan to help you convert your existing factory setup into a smart factory. To jumpstart this process an exclusive workshop has been designed. It’s a joint brainstorming exercise for us to - Understand your business vision and core processes Understand critical junctures and transitions within the organization Learn your existing infrastructure and setup Identify and locate critical parameters, its permissible values, implications in overall systems on violations Understand your business rules, policies, standards to comply with Know about existing legacy systems (ERP, CRM etc.) and how data flows between various departments Now our experts will churn every detail in the IoT spectrum that will bring Identification of entities and processes that can be improved & automated through IoT How to control the critical parameters in a permissible range and at the same time giving control through hand held devices such as mobile, tablets and so on How rules, policies and compliance standards can be improved What infrastructure changes can be brought in to keep overall costs to the minimum How legacy systems can be more efficient and seamless by directly passing data from sensors to systems How to Start Creating a Smart Factory Managing the inventory is a piece of cake for the manufacturer as it knows exactly when to order the required raw material and avoid additional costs for storing extra goods. A reminder is triggered by sensors for the concerned employees to replenish the stock and avoid delays in the production of goods. The Internet of Things also efficiently connects the factory to warehouses, distribution centers, retailers, suppliers and customers to facilitate supply chain management by allowing real-time information sharing. ABC Inc. successfully saves up on costs by avoiding fuel and power wastage and scheduled maintenance. It supplies goods to distributors and retailers who are out of stock, thereby increasing sales and receives raw materials on time. Downtime is decreased to a great extent, allowing uninterrupted production in the manufacturing unit. Moreover, sensors installed on the finished goods help identify faults in products, so that they can be rectified as soon as they are detected to decrease losses and offer good quality products and services to consumers. Warranty management is another cost-saving advantage of the Internet of things for ABC Inc. How to set up a smart factory with the Internet of Things (IoT) 16 6 Reasons Why Factories Need the IoTConnect Platform Flawless Integration Enterprise grade integration mechanisms ensure easy adaptation of existing workflows, business processes and information systems. Faster Development Create new processes with ease and add business applications through common interfaces for faster development. Optimum Security Secure data received from all sources of your IoT ecosystem with state-of-the-art data security systems. Automation Operate and maintain device and data tasks by automating business processes and save management costs. Interoperability Accelerate time to market, reduce cost deployment and maintenance costs of IoT solutions by utilizing interoperable technologies. Centralized Access Single point for adapting protocols and data models for gathering the information and managing the communications. How to set up a smart factory with the Internet of Things (IoT) 17 Workshop Agenda Topic : Introduction to IoT & the verticals it serves Outcome : Awareness of IoT among your employees and benefits for your vertical 09:00 - 09:30 & Topic : IoT in specific vertical (i.e. manufacturing) Outcome : Understanding of IoT ecosystem in your manufacturing system with its advantages 09:30 – 10:00 Topic : Understanding sensors, cloud, big data and analytics Outcome : Technical understanding of the components & infrastructure of IoT 10:00 – 11:00 Topic : Evaluating your business needs processes. Understanding of the existing setup with legacy systems in place Outcome : Identification of processes, critical parameters and scope of IoT implementation in the existing setup 11:00 – 12:00 Lunch / Open discussion 12:00 – 01:00 How to set up a smart factory with the Internet of Things (IoT) The Internet of Things is the driving force for manufacturers today. Softweb Solutions Inc., can be your technology partner and help you stay ahead of your competition in this fourth industrial revolution. With advancement in smart sensors and cloud technologies, companies will enjoy more intelligent services at a cheaper cost. The time is now to make your company smarter and more efficient than before. Enroll for Our IoT Workshop About Softweb Solutions Softweb Solutions Inc. is a Chicago based tech consulting and development company working with organizations across the world to implement the best-of-breed solutions and processes to help them meet their business challenges. Over a decade of experience with the world’s leading companies has given us the expertise to offer strategy, design, engineering solutions and R&D services to companies in every industry. Our clients are able to stay ahead of the curve by leveraging our expertise in all the tech areas – from IoT systems to data science projects and mission critical apps, we never fail to deliver. US Toll Free Number: 1-866-345-7638 | Email: info@softwebsolutions.com | Website : www.softwebsolutions.com 400+ Full-Time Engineers 10+ Years Software Development Experience 1000+ Successfull Projects Delivered 500+ Satisfied Clients & Growing Conclusion
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