DECEMBER 20209MANUFACTURING TECHNOLOGY INSIGHTSFirst, the factors I believe are driving the realization that the technology innovations are only a piece of digital transformation:No Silver Bullets Companies recognize that IoT and cloud are not magic. Those who still do not have reliable networking and basic electronic data collection, and many who have tried to short cut this step and stumbled are now making smart investments here first, while realizing benefits of improved manufacturing visibility.Impractical User Experiences and DependenciesAugmented reality currently relies on costly headgear or taking up an extra hand with a tablet. Advanced analytics, ML, and AI typically require large, pre-existing, and clean data sets for all but the most common of use cases. IIoT sensors and instrumentation still need a reliable and secure network to talk to the cloud and have not yet matured to measure enough manufacturing and process variables to displace traditional shop-floor instrumentation.Long-Term Platform LimitationsIIoT has spawned many companies offering niche applications that address specific and complex use cases with short ROI periods. However, once the benefit is realized, what do you do next? If a solution is bespoke to a limited set of operational challenges, you risk customizing it beyond its capabilities, or searching for other solutions for your next initiative. This could lead to maintenance costs of the individual solutions outweighing the ongoing benefit.Limited Out-Of-The-Box CapabilityOn the other end, platforms providing wide-open, build-your-own toolkits can lead to roadblocks. Although initial use cases can realize value quickly, scaling the platforms to the next use cases often requires more investment than the incremental enhancements that traditional platforms enable as part of standard features.These factors have led manufacturers to refocus on the second driver of the revival of MES: the recognition of the fundamental value of managing shop floor execution, and the benefits it offers long-term.· MES is defined for Manufacturing. MES solutions have proven value propositions and are often able to extend beyond initial intention to address broader operational challenges. MES platforms have gained a stigma of being heavy and overweight. While this may be true in cases, there are increasingly more nimble offerings with broader built-in capability challenging this paradigm.· MES enables analytics. MES Solutions inherently generate context. The more integrated the solution is with shop floor machine and process data, the better the associations. Machine learning models love context, so this step is an investment toward applying ML and AI.· MES feeds the digital transformation cycle. MES records production counts and waste, detects and categorizes asset deficiencies and downtimes, captures performance against schedule, integrates quality with production records--all effectively in real-time. These are all critical data points for understanding capacity and constraints. When integrated with the appropriate business systems, digitally connected supply chain strategies can finally become a reality.The manufacturing systems technology space has seen remarkable change. As manufacturers explored new technologies, some achieved success early, while others encountered challenges. A shift in perspective amongst manufacturers and vendors triggered a transition from hyped promise to practical value propositions. Organizations began to see cloud and IIoT as tools to increase the potential value of traditional MES and MOM software platforms rather than wholesale replace them. As manufacturers continue to pursue Industry 4.0 initiatives, there has been a refocus back to the fundamentals of shop-floor manufacturing execution systems because they not only solve operational challenges, they enable advanced analytics and supply chain management strategies. The next 10 years will likely bring additional changes at an even faster pace, but my bet is that MES will be there to keeping manufacturers going strong.
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