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Addressing Culture Change in IIoT and AI Projects

TRC-2018 Learning Zone 43:15
by Blair Fraser, Lakeside Controls

In the manufacturing and industrial world, Industry 4.0, Smart Industry and Industrial IoT have created a lot of buzz lately. Machine Learning, Artificial Intelligence and Big Data are at the top of the hype cycle. Digital transformation and the digital enterprise are on the top of the strategic initiatives list of every board room and C-suite. While Machine Learning and IIoT have the potential to transform entire supply chains, initial successful implementations are clearly emerging in maintenance and asset reliability. Predictive maintenance is being transformed to prescriptive maintenance by combining existing and new condition monitoring sensors with Machine Learning and Pattern Recognition. This new technology has the promise to solve problems never capable of being solved before, however, we have learned over the last five decades of implementing traditional condition monitoring technologies like vibration monitoring, the common pitfall is the adoption of new technology and work processes is the people. More so than ever, technology like machine learning and artificial intelligence will have a bigger impact on people as it can learn and adapt without humans in the loop. But can people still play a role in AI projects? Is subject matter expertise still required? This presentation will review how through implementing many IIOT and AI projects over the last two years, I learned how people play the biggest role in the success of these projects and tips to address the "who moved my cheese" culture changed required for projects to be successful.

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