The Three Ms for Industrial Success in 2015

As we look at staying competitive in an ever-changing global market, the value of connectivity - connected people, processes and technology - cannot be underestimated. Manufacturers must implement a fully connected framework for top asset performance and strategic data analysis.

In 2014, the Industrial Internet of Things (IIoT), Machine to Machine (M2M) and Big Data became more than buzz words and were widely adopted. Connected machines began driving more data than ever before and Gartner even forecasts there will be nearly five billion connected devices by the end of 2015 and 25 billion by the end of 2020, with incremental revenue exceeding $300 billion.

The industry poised to benefit the most from this digital revolution is manufacturing — that is if manufacturers can take the necessary steps to optimize their assets and the data being generated from them every second.

While only 13 percent of manufacturers said they used smart manufacturing within their organization in a 2013 survey by the American Society for Quality (ASQ), most manufacturers today have adopted strategies to maintain asset health by monitoring and collecting data from advanced automated systems. These processes and technologies, however, operate in silos across the organization, undermining the value proposition of the IIoT.

As we look at staying competitive in an ever-changing global market, the value of connectivity — connected people, processes and technology — cannot be underestimated. Manufacturers must implement a fully connected framework for top asset performance and strategic data analysis, and this framework includes three important processes: measure, monitor and manage.

1. Measure: The first step, measurement, is critical to asset strategies because every asset in industrial organizations is essential for successful operations. Today’s advanced sensors and hardware measure asset health in real-time to prevent costly failure and disruption to business operations. When engineers identify abnormalities such as a sudden vibration increase in a compressor or high temperature trends, they must determine the root cause of the problem before a machine trips or equipment fails. This is particularly critical to ensure asset availability until a planned shutdown. Regular audits and automated measuring allow manufacturers to detect problems early before they become more severe and costly.

2. Monitor: While measurement is the first step for asset performance management, machines must be continuously monitored for valuable insights. Software tools today identify root cause failure through data analysis and initiate proactive maintenance to protect assets and reduce downtime. Once the problem is detected through regular measurements, close monitoring provides the information needed to effectively identify, evaluate and respond to events while keeping assets online for continued operation. Further, automated monitoring and response to these conditions frees up resources to perform additional activities to enhance overall productivity. The next and final step, management, harnesses the power of the data gathered through software systems for more strategic decisions across the organization.

3. Manage: Organizations need to operationalize big data to reduce costs and improve efficiency. Asset performance management provides structured processes and analytics to identify critical assets and failure modes, calculate equipment reliability and determine downtime impacts. Executives and operators need the end-to-end picture of operations to drive impactful change. Being able to leverage information from equipment and asset strategies as well as methodologies such as risk based inspection (RBI) adds clarity and stimulates cross functional ‘integrity’ team building and exchange of best practices. The approach is very practical, easy to apply and transparent. The full integrated framework allows for seamless analysis, consistency of approach and synergy with other strategy assessment methodologies including reliability-centered maintenance (RCM) and RBI.

Furthermore, it isn’t enough to compare an asset’s performance against another in the same facility or even across the enterprise. Assets must be compared against each other across organizations worldwide. Advanced comparative analytics software helps executives and operators to understand what is working well and what isn’t working on an individual asset level and structurally for the organization as a whole. Without the full framework, industrial organizations cannot compete in today’s global market.

Adding context to data from measurement and monitoring tools yields meaningful, actionable information. This unified approach provides an enterprise view of assets for planners, maintenance personnel and reliability engineers, who can know — with confidence — the current health and condition of their assets.  Consolidating data sources and analyzing information facilitates failure diagnosis and enables more informed decisions concerning maintenance activities, planning, investment and resource management, both short and long-term. The framework further empowers capital and operational planners to make informed decisions based on production loss analysis and asset health and risk, categorized by asset class, location and other data points to help identify and isolate business-critical areas of focus. 

While there are many tools and software solutions available for manufactures, this framework must be unified to simplify the M2M dialogue and give engineers, operators and c-suite the transparency and predictive models necessary to profit. Communication gaps hurt production. With all three capabilities connected in one source, organizations can identify weaknesses, ensure assets are performing optimally and enact process improvements where needed.  This integration also offsets the aging workforce risk with tools that capture knowledge and processes, creating an easier transition for new engineers.

Asset-intensive manufacturing businesses are under pressure to achieve profits that satisfy stakeholders while maintaining top safety performance. The majority of companies have embraced new technology but they are still reacting to issues rather than staying ahead of them. Manufacturers should consider transitioning from reactive to proactive maintenance with this framework that collects the right data and uses risk-based approaches to apply maintenance, inspection and engineering resources exactly where they are needed.

John Renick is Director of Partner Solutions at Meridium.

More in Home