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Buy new or make do? It’s an age-old debate for manufacturers who are trying to decide how best to manage machine assets inside their manufacturing facilities. New machines are expensive, but so is operating existing machines at a comparative deficit.
It’s important to recognize that increased demand for machines is a good thing. The global economy demands more products at an ever-increasing rate, and that can certainly mean increasing the number of physical assets needed to produce those products. At the same time, manufacturers need to be much more flexible with current assets to deal with shortages. But most manufacturers don’t have nearly enough visibility into the granular machine data from those existing assets to be as nimble as they need to be—and they know it. So, they’re rightly asking if their current assets are enough to get them through or if they need to pivot now and buy new machines to keep up.
The 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. The goal should always be to buy more as manufacturing demand increases, while maximizing and constantly increasing the value of existing machines along the way.
Fundamentally, it’s about creating the healthiest hardware and software ecosystem possible within the organization. Because moving hardware is a slow game, investment decisions must be intentional and long-term. Software, on the other hand, moves fast and allows ramp up and down the right way while making the most of what you currently have. This is certainly true when looking across your workforce and overall process operations and intelligence. But it’s even more true when looking at machine assets, where massive amounts of capacity are still being left behind in nearly every factory in the world. Therefore manufacturers are starting to see some of the biggest upfront ROIs coming from adding dynamic machine capacity 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 estimated $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 projects and solutions are designed to contextualize manufacturing machine data for use in the manufacturing execution system (MES), and for good reason. No manufacturer needs further explanation about the value of modern MES systems. But when it comes to solving 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 problems that require all the machine data. Therefore 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 competitive in the immediate years ahead. This requires an entirely new category. Most importantly, it requires a near-perfect combination of domain experience and data expertise.
This article originally appeared in the April 2022 issue of SMT007 Magazine. Click here to continue reading.