Many manufacturing industries are trying to figure out how to employ Brilliant Factory technologies to their existing operations in the hopes of maximizing their production output and streamlining costs.
While there is no set way to accomplish this, Katie Moore, industry marketing manager at GE Digital, says starting small is a good approach to get the process rolling. By modernizing plant operations in a food production facility, operators can identify potential issues impacting production, streamline costs, extend the usefulness of existing equipment and empower them to make better business decisions.
Food Manufacturing recently corresponded with Katie to discuss these topics and more.
Q: What are the key benefits to employing brilliant factory technologies to existing operations in the food manufacturing industry?
A: The bottom line is it’s about employing a digital thread — seamlessly tying the flow of information from design through manufacturing to end consumers, including the full life cycle of the product. It’s about answering the question: how do we look at manufacturing and introduce data and analytics like never before? Manufacturing digitization is not a new concept, but the data today is stuck in silos. Brilliant manufacturing technologies enable food manufacturers to make better decisions using the aggregated information and data from existing equipment and systems. Ideally, the future is moving from reactive gut-based decisions to predictive data-driven decisions.
Q: If food manufacturers do not want to implement all-new technology and change current processes (or are deterred by the costs), what is the best approach?
A: Start with a data collection strategy. Link it to the primary key outcomes or benefits that you are trying to drive within your food and beverage manufacturing — like improving production efficiency, ensuring product quality or driving out utility costs. Ensure the key stakeholders are involved including operations, IT, quality and maintenance functions. Digitization is a critical start, but it still doesn’t optimize — so the future must be kept in mind. Many companies ask us why manufacturers are slow to start. Many try to embark upon big bang projects that don’t flex with business changes and/or they invest in local initiatives with little ability to scale. Manufacturers should look at more off-the-shelf solutions; that way, they can begin to eat the elephant one bite at a time. Quickly get insight about basic plant information, start to see value, then get more information. Start simple and add incremental capabilities to the platform as needed. Ultimately, manufacturers will need to partner with technology firms that have open, scalable platforms to be able to build and grow with them.
Q: How does consumer demand (like the growing interest in sustainability and all-natural ingredients) affect changes in the food manufacturing plants? How can manufacturers determine how to best accomplish what changes need to occur?
A: Having a data storage and aggregation strategy is of primary importance. Again, it’s about extracting the data, aggregating it and then gaining additional insight, in context, to make better decisions. Manufacturers may begin to collect data today that at first, may offer them little perceived value. But what’s interesting is that as consumers’ needs and demands change, manufacturers can begin to model the data that’s already been collected to understand how these changes may affect operations and existing processes. You don’t know what you don’t know. By starting to collect data, manufacturers can begin to draw inferences and correlations that they never knew were possible before.
Q: How is data-as-a-service a key component to brilliant manufacturing in the food industry? What are the benefits?
A: Data-as-a-service is beneficial for manufacturers who don’t want or have the capability to manage the software and infrastructure. One benefit of data-as-a-service is that the software and systems are monitored and upgraded on their behalf, for example upgrade security settings as needed. In addition, another benefit is that it helps with speed of deployment and scalability. If manufacturers aren’t ready for cloud, there are on premise offerings available.
Q: How can food manufacturers modernize older machines to produce valuable data?
A: Ultimately, determining what critical data must be pulled from machines is a first step and delineating the must-have data from the nice-to-have data would be next. Typically, equipment is broken up into three categories: network enabled, network ready, and no network capabilities. With the former two, connection to those pieces of equipment is fairly straightforward. With the equipment with no network capabilities — this is where the determination of what data is initially critical determines how to go forward. Retrofits, modifications and/or sensors may be necessary in order to get at the critical equipment.
Q: What are the benefits of moving from a reactive to a predictive field service management model?
A: As mentioned, moving to data-driven decisions that are predictive versus reactive, improves product quality, reduces production inefficiencies and potentially can lead to substantial savings to the bottom line. It’s really about “preventing” versus “treating” — sort of like healthcare — wouldn’t it be more cost effective and more ideal to prevent a disease versus treat one?
Q: What processes are best suited for brilliant factory updating and are there other processes that are not good candidates or otherwise shouldn’t be updated?
A: Brilliant manufacturing technologies can be hosted onsite or in the internal or external cloud, depending on the manufacturer’s preference and existing infrastructure. That being said, if cloud is the choice, the manufacturer should ask their operations and engineering teams if the application requires feedback to the PLC, is hosting in the cloud really the right strategy? There will always be some need for on premise applications — think real-time transactions versus near-real time.