Like most everything in 2020, global supply chains were thrown into disarray during the pandemic. Demand plans and equipment maintenance schedules went out the window with U.S. e-commerce volume growing 44% as consumers stayed home to buy everything they needed to sustain life. In response, many supply chain managers increased safety stocks to hedge against increased volatility. Now, as we begin to emerge from lockdown, everyone is looking for ways to boost supply chain velocity and efficiency. Artificial intelligence (AI) and machine learning (ML) technologies seem a natural fit for helping wring out greater efficiency and better decision-making in this area. Steve Banker, vice president of supply chain services at ARC Advisory Group, wrote recently about a host of AI-driven supply chain use cases, ranging from those that are still hype-stage to those with established return on investment. Banker cites, in order from most hypothetical to most mature: blockchain, autonomous trucking, ML for warehouse management, robotic shuttle optimization, ML for transportation, ML for demand planning, real-time location services, and IoT for transportation.
With the continued growth and evolution of Advanced Manufacturing International, Inc. (AMI), the