AI for the
factory Making data actionable with factory operations management. By Richard Lebovitz
T
he pandemic has given companies the opportunity to reset their priorities around resilience and operational excellence to ensure that their supply chain runs smoothly no matter what challenges the world throws their way. AIpowered and machine learning (ML) technologies have the power to transform daily processes and decisions, and play a key role in helping manufacturers grow market share and stay competitive in a global playing field. Terms such as ‘Industry 4.0’ and ‘smart manufacturing’ describe the adoption of AI to address problems that it would be unthinkable to automate in the past. Implementing an AI approach to factory operations management focuses on ways to streamline procurement, planning, and performance management by taking into consideration the data, processes, workflow, and people. For example, a number of AI applications can recognize and categorize specific patterns to improve manufacturing quality, cost, and delivery. AI is being leveraged to quickly
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pinpoint issues in the supply chain, prioritize the necessary actions, and drive automated workflows to execute the optimal action in their business systems. According to a 2020 study by PWC, only about nine percent of manufacturing organizations are leveraging AI today. And a 2021 survey by IBM reported that 65 percent of manufacturing decision-makers were working towards adoption, implementation, or use of AI and ML. These two statistics alone show the tidal wave of change brought by the global pandemic and supply chain challenges have been almost instantly transformative.
AI for Predictive Analytics
AI systems enable predictive analytics, helping tackle operational challenges and disruptions to supply chains. By aggregating data from different ERP systems, SIOP tools, BI tools, homegrown tools, and more, companies can use AI to not only analyze but prescribe and