In recent years, managing a supply chain has become increasingly complicated, due to factors like globalization, geopolitical shifts, technological progress, and evolving consumer demands. This complexity necessitates the use of Artificial Intelligence (AI) and Machine Learning (ML) to effectively tackle modern supply chain challenges. Today, diverse elements influence the robustness of the supply chain network, from economic uncertainty to environmental, social, and governance (ESG) concerns.

Supply chain management, from a mathematical perspective, poses a dynamic and intricate challenge. Balancing numerous variables and constraints demands formidable optimization efforts. AI and ML algorithms excel in processing and analyzing the vast and multidimensional data involved, providing insights and solutions beyond human capabilities. Their real-time adaptability is especially noteworthy, ensuring supply chains remain agile and resilient in the face of unexpected disruptions, demand spikes, or market shifts.

Companies can no longer address supply chain challenges with manual or spreadsheet-based processes and the need for advanced optimization is now critical. Optimizing the supply chain successfully involves navigating a maze of mathematical complexities influenced by:

• External challenges comprise severe weather events, economic downturns, trade conflicts, global health crises, environmental shifts, cyber threats, acts of terrorism, and supplier insolvency, among others.
• Internal factors include limited visibility, fragmented collaboration, inflexibility, escalating intricacies, reliance on manual procedures, digital gaps, and conflicting business objectives (e.g., balancing sustainability with profitability).
  
  

Read the full e-book to gain deeper insights into how the Dassault Systèmes’ DELMIA solutions help address both external and internal complexities by using AI and ML that employ advanced mathematical and statistical methods such as various programming methods— like dynamic, linear, and mixed-integer—or machine learning algorithms like neural networks. Learn why these techniques facilitate effective optimization, data-driven decision-making, and real-time adaptation in supply chains.

Browse our website for more information on how Dassault Systèmes DELMIA solutions can help you successfully transition into an era of efficiency and adaptability, resulting in more agile and responsive supply chains, reduced downtime, and enhanced sustainability. Check out our extensive case study to read how Andea and one of the A&D industry leaders Sierra Nevada Corporation (SNC) partnered to create a Manufacturing Planning and Execution Platform to support the company’s different processes and address its diverse business needs in the fields of production, quality, warehouse, labor, and supply chain.