Traditional supply chain systems have promised end-to-end visibility and self-service analytics for years, but the experience ...

In planning, machine learning synthesizes real-time market trends and external factors to drive forecast accuracy ...

Less than a year ago, it seemed like that day when generative AI would bring about a new era of supply chain autonomy—one where AI could adeptly make all the inventory and logistics decisions—was ...

Each year when MD+DI editors sit down to discuss Medtech Company of the Year prospects, the companies that rise to the top for us tend to be those that have had a transformational year either through ...

The 15-year effort by Japan is a model for countries now scrambling to reduce their dependence on Beijing’s critical metals. Sojitz, a Japanese conglomerate, turned to Lynas, an Australian mining ...

The pandemic didn't just disrupt global supply chains — it exposed a fundamental truth about the medical device industry: fragmented, reactive supply chain management is no longer viable in an era of ...

Under the new quality productive forces, enterprise supply chain management is confronted with novel challenges and opportunities, necessitating a re-evaluation of optimization strategies. Supply ...

Abstract: In the complex supply chain logistics environment, enterprises face core challenges such as multi-commodity transportation, multi-trip distribution planning, and supply chain stability ...

GM is using AI technologies to help monitor its supply chain. The company is able to get ahead of production-halting events with mapping, news scanning, and data-sourcing. This article is part of "How ...