Do Manufacturers Need a New IIoT Platform?
Blog: Apriso Blog
Virtually everyone agrees that the Industrial Internet of Things, or IIoT, is poised to have a huge impact on manufacturing. It will transform everything: how you design, manufacture, distribute and support products from cradle to grave.
The challenge is if you run a global manufacturing enterprise, where do you start? The technology and choices can be overwhelming. Should you develop enterprise manufacturing intelligence capabilities first? How will you integrate disparate legacy systems? What about closing the loop between design and production? What is the best way to manage an IIoT – is another platform required for the shop floor?
To help provide guidance and a path forward, the first thing you should be thinking about is what sort of “ecosystem” do you want? With that vision, it will be easier to plot a course to achieve. At a high level, I would propose the Industrial Internet of Things is all about collecting data, automating responses, converting that data into intelligence and then using the knowledge that ensues to streamline decision support, support continuous process improvement to enable sustained operational excellence.
If that sounds like a good vision to you, then here are four steps to accomplish it.
Four Steps to be Ready for the IIoT
- Boost Data Acquisition. The most basic requirement for utilizing IIoT is to collect, process, and distribute data on manufacturing operations across the enterprise. This information can yield intelligence, help guide process improvement and support other enterprise operations, such as design and engineering, enterprise resource planning, and supply chain management. Data collection begins with making sure every part of your production process has a sufficient capacity to track every relevant performance metric. Then this data must be transferred to a central repository so it is visible for decision support and continuous improvement. Data trapped in silos won’t help – it must be readily available. Global Manufacturers are well-experienced with this type of data collection – the need has existed for over a decade.
- Design-Production Integration. Most of today’s products are designed in the virtual world, digitally prototyped and then actually built. As production continues to be digitized, manufacturers want to take advantage of linking design with production. The Digital Twin concept is a popular example. A digital “as-built” can be a great way to quickly tell if products were built to plan, but is only possible if enough data is collected, such as with the IIoT . Once again, this need is not for those manufacturers with established global enterprise manufacturing systems. The issue and need for interoperability across enterprise business systems (ERP, PLM and MES) began many, many years ago.
- Real-time Analytics. In the age of IIoT, applications will need to analyze and interact with manufacturing data constantly, in real time. This data then needs to be collected and aggregated in such a way it is readily accessible and visible to the rest of the organization – which means it will need to be stored somewhere. This type of capability can only occur when data is collected “clean,” so it can then be processed immediately. If data must always be normalized, then it won’t help improve decision making, automate responses, trigger alerts or support the voracious appetite process engineers (and others) now have for Descriptive, Diagnostic, Predictive and Prescriptive analytics. The driving force here is how to better harness the intelligence that can be gained from Predictive analytics. If equipment can predict when a future point-of-failure is most likely to occur, this information is very valuable to help plan accordingly to maximize uptime. Those manufacturers that gain access to accurate, predictive intelligence can really capitalize on this knowledge.
- Global Traceability. Tracking a product’s genealogy is really all about consistent data collection, and making sure that data is readily available whenever needed. Today, that requirement is now extended to across the enterprise and out to supply chain partners and others. This is a role the IIoT can fulfil, by providing data from the production process for not only your operations, but potentially those of your partners, customers and suppliers. Unleashing the power of traceability as an enterprise function could let companies quickly identify and contain problems as they occur to limit financial damage and preserve brand equity. It can also help drive continuous improvement on a global scale.
Interestingly, many manufacturers have been pursuing an IIoT strategy already without actually realizing it. It might be the perfect way to help future-proof your manufacturing operations and provide a path to manage today’s manufacturing transformation – without calling it explicitly “IIoT.” What this means is that if your company has, or is now deploying an enterprise Manufacturing Execution System (MES), you are already well on your way to leveraging the IIoT. You have key processes established, trained knowledge workers and years of experience in pursuing operational excellence – the perfect framework to address new opportunities of an IIoT world.
With a MES in place, you have already begun your IIoT journey. And, if you already have some sort of Manufacturing or Business Intelligence systems in place, you can simply expand and deepen what you already have into a global solution for Manufacturing Operations Management (MOM).
On the other hand, if you’re one of the shrinking numbers of manufacturers that hasn’t yet taken the plunge, perhaps now is a good time to start? Put together a plan to manage global manufacturing operations from a single platform. Then add intelligence gathering and analysis capabilities. I see a convergence coming – a seamless integration between the MOM platform (ideally, BPM-based at the core) and an emerging analytics platform (with a modeling and inference engine at the core). This will become the platform of the 4th industrial age for manufacturers. The potential to generate significant business value and ROI will be huge, and you’ll have an IIoT platform for whatever comes next.
I welcome your feedback. What do you think?
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