Machine Learning to Improve Performance in Asset Management, Reliability, and Supply Chain
BoK Content Type:
Presentation Slides
Video
Presentation Paper
BoK Content Source:
MainTrain 2021
Original date:
Thursday, June 3, 2021
Is your company struggling to forecast, and have parts arrive on time to perform preventive maintenance, or know when downtime should occur that would be least disruptive? Would your company benefit from more accurate cost predictions and a decrease in last minute emergency breakdowns? Or perhaps you cannot depend on what the system has for inventory or how many staff are required on site at a given time – there are somehow too many or not enough at any given time. These are common issues faced by many large manufacturers from Marine, to Mining to Oil & Gas, and many others. This session will provide an overview of how basic Machine Learning techniques can be applied to Supply Chain, Reliability, and Asset Management to gain increased insight, and better overall performance. But what is Machine Learning? It is a subset of Artificial Intelligence, where algorithms improve through experience (new data sets). The algorithms constantly evolve as more and more data is run through it. Machine Learning is useful for finding unknown patterns and relationships in data, such as sales, plants, store, or forecasting. It is an effective tool to gain insight and efficiency in day to day operations, while also providing a future forward view.