Computer systems and software are, by definition, an integral part of MES since their mainstream inception in
the 1990s. Becoming increasingly sophisticated, we now assume that the adoption of IIoT technology is the next step forward with communication from the MES perspective. But understanding the true nature of IIoT tells us thatthis is actually far from the truth. And unless we address the true nature of the change that IIoT brings to MES, many current solutions will turn legacy very quickly.
The recent focus for MES has been data acquisition. When executed properly, data acquisition enables the software to make automated operational decisions. As such, IIoT is increasingly seen as the mechanism for the advancement of MES business goals.
But first, two issues must be addressed.
When developing software for any computer system, the old-school mindset of programming was to start with the data. All of the value from software comes from the manipulation and processing of data. Incomplete data means no value—garbage in, garbage out. This is very relevant for IIoT. As communication technology within manufacturing has developed, however, the industry still seems to be missing the point. Take the example of the mobile phone. Compared to previous forms of communication, mobile phone handsets made by many vendors all over the world are all compatible with each other. With any phone in my hand, I can reach out and talk instantly with anyone else, no matter where they are on the planet, no matter their cell service provider. Differences in the spoken language can be problematic, of course. A language other than your own will have a substantially reduced conversation opportunity.
The same is true of IIoT. We can now easily create the mechanism to send live data in real-time across the globe on-demand, but unless we have defined the language and the content of the data, it is of little more value empirically than sending the data by fax. Such a situation has been faced head-on by the IPC Connected Factory Exchange (CFX) committee, where 150 companies have realized that we must define technology and vendor-neutral data content (in addition to the data-transportation mechanism and encoding method) in order to create a true plug-and-play IIoT communication standard that will work for everyone. The content definition, to meet the needs of hundreds of different machine technologies, has been intense, representing more than 99% of the work done already to create the standard, which is expected to be finalized by the end of 2018. Without this work however, we would simply be delivering garbage faster than ever before. We should not be using our new cloud-based systems as data landfills.
The second issue is that, when it comes to data, industry tends to think that “It is all about me.” The focus is on data acquisition, not data exchange. The old-school view is that machines are given instructions to follow in the form of data prepared by production engineering and programming systems, Then the flow of data is outward, to make a record about what has been going on. Less discussed is machine vendors’ need for more information, especially run-time data. Machine vendors are also now realizing that they shouldn’t have to shoulder the burden of providing data in many different formats based on individual customer requests. Vendors should not be denied the opportunity of being an added-value part of the new smart factory or an Industry 4.0 solution. IIoT has a clear focus on omnidirectional data flow. This is a good thing.
Take a typical surface-mount machine in electronics manufacturing as an example. A digital-engineering product model is provided to the machine for each work-order. Machine-vendor software in the past environment would simply convert the data into an optimized machine program, and off it went. Today, however,machine software is also expected to:
- Group materials between sequential products to reduce changeover time, while also not compromising individual program efficiencies
- Detect differences in incoming material shapes and supply forms in advance to allow the machine to seamlessly transition a material change without the need for manual intervention for re-programming or program adjustment
- See the measured performance of placement deviations as measured by a down-stream inspection machine, which allows the placement machine to automatically adjust to compensate for operational variation and to recognize the need for maintenance, are increasingly expected.
Machine vendors can achieve boosted performance/quality by using data from other machines and processes, including transactional sources such as material logistics. Software can then be created to make machines work in flexible environments, by looking further at the schedule and optimizing themselves for any level of product mix. These functions are as essential to the realization of factory-level Industry 4.0 as any other part of MES.
Realizing real-time production optimization requires an intimate understanding of machine processes. In short, machine software and MES need to work together, rather than stick in the old “give me the data” mindset.
IIoT is an omnidirectional technology that delivers a step-change in the way that MES works. With a comprehensive data-content definition, IIoT in the form of CFX creates a sustainable business/technological platform that meets Industry 4.0 specifications. Those who think IIoT is just an enhancement for data gathering by old-school MES software may not be wrong. But they are certainly missing an opportunity. IIoT partnered with defined-data content is the revolution we have needed to make the leap forward to true digital-factory operations.
Michael Ford is European marketing director with Aegis Software.
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