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Reflection on the Pre-IoT Era

Some thoughts arising from the Smart Manufacturing Experience show.

Breanne 838cc05c38c0a6e5463d41a35eaf9f906baae66a3727cc65ff58be449642d9c9 Bre Hargreaves Head of Customer Success / May 9th, 2018

Industry 4.0 (IoT)

 

Some thoughts arising from the Smart Manufacturing Experience show.

Tradeshows are a fantastic way to get the vibe of an industry. We were recently at the Smart Manufacturing Experience in Boston, a show that just launched this year. This time around, it wasn’t robots that caught my attention, but IoT solutions for the manufacturing floor (i.e. sensors + cloud data collection analytic platform). 

Interestingly, several members of our team at Vention come from the first generation of IoT solutions, working at Pivotal, Cloud Foundry and GE (Predix). The topic of IoT solutions is heavily debated internally, with the overarching question being: Where is the value of those solutions really coming from? How does this proliferation of data translate to bottom-line impact for manufacturers?

 

This is best summarized in a few personal stories. In my previous life, I helped several companies increase manufacturing asset utilization. The question of “IoT software” to increase CNC utilization was often considered, but often an incorrect solution to the problem at hand. Most of the time, manufacturers that seek to boost CNC utilization would be better off opening a second production shift than subscribing to a machine analytics solution. This would, by default, boost asset utilization by 33%, a gain that is unlikely to be matched by any software solution. More interestingly, implementation can be done at zero cost within a two- to three--month window.

 

Another example is the one of inventory optimization. Since the early 2000s, it has been quite easy to have quasi real-time visibility on stock level, by connecting Microsoft Excel to the SQL databases of an ERP/MRP. Once connections were established, one could easily program stock level alarms or run various optimizing functions. From personal experience, a simple statistical regression could help increase inventory turns by 30% to 50% over a four- to eight-month period, once again, at zero cost.

 

All those pre-IoT methods forced users to understand their business from a data structure and operations standpoint. Most manufacturers have data to derive value from, but they don’t always have access to the talent to conduct the analyses and extract the insights. Needless to say, those skills are now a pre-requisite to compete.

 

To me, this is where IoT solutions create real value. It’s not so much in a specific software or product, but in the message they bring to the manufacturing floor: Understand your manufacturing data, or someone else will!

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