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64 SMT007 MAGAZINE I APRIL 2022 e answer is both. Increasing dynamic machine utilization meets two critical needs for manufacturers. It allows for fewer machines to do more but also allows more machines to do even more dynamically. It's not simply a zero- sum game of whether you buy more machines. e goal should always be to buy more as man- ufacturing demand increases, while maximiz- ing and constantly increasing the value of exist- ing machines along the way. Fundamentally, it's about creating the health- iest hardware and soware ecosystem possible within the organization. Because moving hard- ware is a slow game, investment decisions must be intentional and long-term. Soware, on the other hand, moves fast and allows ramp up and down the right way while making the most of what you currently have. is is certainly true when looking across your workforce and over- all process operations and intelligence. But it's even more true when looking at machine assets, where massive amounts of capacity are still being le behind in nearly every factory in the world. erefore manufacturers are start- ing to see some of the biggest upfront ROIs coming from adding dynamic machine capac- ity to their overall plan. More than 50% of all potential capacity is untapped. Nearly every industry expert agrees, with some arguing for numbers much higher. Today, there are trillions of dollars of purchased machine capacity across the global manufacturing footprint. Within electronics circuit board assembly alone, there is an esti- mated $100 to $200 billion. It's easy to see why manufacturers are now jumping at the chance to unlock even a tiny fraction, let alone 40–60% of that hidden capacity. But the "how" of doing this is where most manufacturers are stuck. Most data proj- ects and solutions are designed to contextu- alize manufacturing machine data for use in the manufacturing execution system (MES), and for good reason. No manufacturer needs further explanation about the value of mod- ern MES systems. But when it comes to solv- ing problems like utilization, attrition, even OEE, the MES and the data structured to feed it, fundamentally solve a different problem. Nor are they designed to solve those prob- lems that require all the machine data. ere- fore so many manufacturers are fundamentally blocked and haven't been delivered solutions that provide clarity into these new insights— those they desperately need to stay competi- tive in the immediate years ahead. is requires an entirely new category. Most importantly, it requires a near-perfect combination of domain experience and data expertise. To obtain the data necessary to claim the untapped value in existing machines, it's crit- ical that it's architected in such a way that it's available instantly and that all of it—yes, all of it—is stored indefinitely. Executing this crucial step without a specialized library of machine connectors will leave manufacturers stuck in "data project purgatory" indefinitely. is is key to making the data useful and available near-instantly. Importantly, this step is incom- plete if the data—again, all of it—is not stored for future and historical analysis. ere is lit- tle chance of predicting what you may need from the data in two years. But it's impossible to meet those needs in two years If you're not getting it and storing it correctly today. With the data connected, flowing in, and stored correctly, manufacturers now have, for the first time, truly unified data from all machine types and vendors across their entire organization. is allows regional experts to Fundamentally, it's about creating the healthiest hardware and software ecosystem possible within the organization.

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