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What Role Will Big Data Analytics and AI Play in the Future of Lean Manufacturing?


The 2011 McKinsey study supplied a solid forecast of how evolving technologies would impact retail, supply chains, healthcare and manufacturing, while highlighting the difference between “lights out” manufacturing operations versus those that rely on AI. In “lights out” instances, machines run with no human interaction, while in AI operations, machines can actually teach themselves how to optimize their performance as they can run through various scenarios at lightning speeds, identify the best processes and train themselves to achieve a desired outcome. It’s likely that AI will ultimately be the real game changer in factories once new ERP platforms are in place, but this may still be a decade or more away.

So, if your business is among the leaders in achieving this kind of breakthrough, what would that be worth to you in terms of increased market share, low costs, perfect service, operating margin, shareholder value? Can any of this technology be applied in current standard factory operations (i.e. on the shop floor)? How can manufacturing leaders apply this thinking and application on a practical basis?

Corporations continue to invest heavily in ERP systems that still rely mostly on traditional thinking and reporting. But report formatting isn’t structured to produce actionable, real-time reporting. Why can’t the ERP system simply be linked to the machine’s PLC and provide data in real time? Or must we always have a secondary system, often not integrated with anything else, to have what shop floor people need to more effectively manage the business minute by minute, hour by hour?

Historical reporting is of no value on the shop floor. So, what will the next generation of ERP systems design look and act like? Now is the time for all C-Suite leaders to follow these technologies carefully, partner up with thought leaders in this area, and strategize how to be among the companies who get up to speed early and commit to new technology. Some recognizable manufacturing names like Rockwell, GE and Siemens are already out front, but software companies need manufacturing practitioners’ input to maximize the potential of the technology.

While the potential for using Big Data and AI for innovation is enormous, it will only be fully realized when the software writers of ERP systems catch up with current thinking. Why? Because using this slick new access tool to tap into the wrongly designed ERP system data will simply give manufacturing the same wrong information at the speed of light. These programs must be redesigned in concert with these new technologies if manufacturers want to extinguish long-standing paradigms and catch up with state-of-the-art manufacturing needs.

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