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Industry 4.0 remains a hot topic in the manufacturing industry, and this blog will dive a little deeper and explain how new business paradigms are supported.


Where We Are

I recently had the opportunity to attend ARC’s 2016 European Industry Forum. The focus of this year’s event was on the state of play around Industry 4.0 technology adoption, breaking down the barriers between traditional information technology (IT) and operations technology (OT) environments, prioritization of investments, roll-out of new business models, etc. When it comes to asset monitoring, predictive (condition-based) maintenance and the performance-based support contracts that it enables, I thought I was pretty much up-to-speed with more than a decade’s worth of experience on exactly that topic in the aerospace industry.

Boy was I wrong!

The scale of the obsolescence management challenge and installed base of legacy systems is immense, especially in the process manufacturing industry. With plants designed for a thirty to forty-year lifespan and running for years before being shut down for maintenance, the ability to apply Industry 4.0 technologies in these heavily regulated environments is not easy. The problem is exacerbated by the fact that even today, new plants are delivered by EPC contractors to the operators with literally truckloads of engineering drawings and other paper-based asset information.

Hope for The Future

What I also saw were a lot of examples where sensors were being used and machine learning applied in proofs of concept for assets such as pumps, fans, filters, valves, etc. This trend is contributing the rise in industrial Internet of Things (something we’re encouraging more of our customers to embrace). It’s one thing to collate all this information, but value is only realized when that data is effectively acted upon.

Examples from the event suggested that the manufacturing industry is not yet as advanced as the aerospace industry. Take the F-35 Joint Strike Fighter for example. Fault isolation takes place at the systems level, based on physics-based models. A model is available for a given functional area; i.e. propulsion, mission systems, vehicle systems, etc. When these lower-level systems fail to isolate a fault, an air vehicle model will reason across all the individual areas.

It will take quite some time for the manufacturing industry to catch up to this level of analytics. At the moment, process manufacturing and discrete manufacturing are similar in their approach to maintenance in that both target individual assets. The good news is that all manufacturers of equipment have products tested and are ready to roll out the new technology to their customers. Siemens, Rockwell, Honeywell and Mitsubishi Electric, all have testbed factories and are ready to help their customers’ Industry 4.0 capabilities.

This is good news for companies with opportunities to implement these new capabilities, but what about the large number of plants that haven’t come quite as far?

Even without all these new and instrumented machines, a lot can be done. 90% of data captured by historians is not analyzed. Manufacturing data historians, or plant information management systems (PIMS), collect critical data required to monitor a production process. This data can be used as a starting point for the performance analysis of (parts of) a production process.

What Does This All Mean?

We have the capability today to deal with the big data that is generated by a production process. Put a process operator together with a data scientist and watch the future unfold. We will be able to extract performance models, identify trends and predict events, enabling us to make manufacturing processes more efficient.

This, however, is not all there is to Industry 4.0.

We also need to look at the impact that mass customization will have on the frequency, volume and change rate of production orders and finally, faced with an ageing population (at least in Western Europe), we need to be able to capture and structure knowledge as part of our new systems.

IFS Will Play Its Part

Today IFS already supports different manufacturing methods such as engineer-to-order / configure, make, assemble-to-order / make-to-project / batch manufacturing and repetitive manufacturing.

In addition, managing new cyber physical systems and other equipment such as CNCs and 3D printers, which play a key role in an Industry 4.0 setting, is possible as part of our enterprise asset management capabilities.

Dynamic scheduling and advanced analytics are also available with IFS Business Intelligence and IFS Enterprise Operational Intelligence and so now, we are focusing on connecting IT business systems to the operational technology systems.

We are ready for Industry 4.0 when you are—not fiction but demonstrable fact.

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