Ara Surinam, VP Product Management at Plex which is now a Rockwell Automation company (one of the ways Rockwell moved into the cloud), talked with me recently about using AI/ML (artificial intelligence as machine learning) in an industrial software setting. Ara was part of the development of Cloud Command Center in 2007.

He noted that the goal is to improve business outcomes for customers. One way involves compensating for the fact that few companies employ lots of data scientists. Another is to help them leverage technology as a way of forecasting demand.

With all the disruptions to the supply chain we have witnessed over the past few years, Plex leveraged ML to evaluate project information in a way that does not require data scientists. Another part of AI is neural nets, and Plex leverages that technology with “deep AI” toward structuring data for enhanced customer supply chain decision making.

Here are a few additional bullet points of information:

  • Make it repeatable, spreadsheets are prone to error.
  • Focus on anomalies.
  • Balance growth, cost, inventory, and production with real-time plant floor data to effectively forecast—and deliver on—customer demands.
  • Gain higher forecast accuracy and meet customer expectations with reliable delivery dates based on current resources and capacity.
  • Make production planning trade-off decisions considering rough-cut capacity constraints, inventory and customer service levels.
  • Utilize advanced production planning options to level-load manufacturing across multiple plants.
  • Reduce supply chain costs with a more realistic master production schedule that drives material, production, and resources allocations.
  • Gather data from across departments, plants, and supply chain channels, for a single-version of supply chain plan.
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