108 VIEWPOINT Manufacturers are using AI tools, IoT devices and cloud solutions to make data-informed decisions and improve their product lifecycle management ROCHELLE FLEMING: MICROSOFT Future-proof supply chains Manufacturers are facing a wide range of disruptions across the world. Supply chain shortages are caused by geopolitical issues, cyberattacks, consumer-demand swings and natural disasters. To meet this challenge, they are accelerating their digital transformations to improve their visibility throughout the supply chain and using artificial intelligence-powered analytics to streamline and innovate their daily operations and processes. By combining generative AI with advanced data analytics, businesses can make data-informed decisions, access valuable insights and optimise their operations to create robust distribution networks. Streamlining operations with AI There are four use cases in which the integration of AI will positively impact supply chain resilience: enterprise resource planning (ERP), manufacturing execution systems (MES), predictive maintenance and logistics management. ERP solutions are the backbone of industrial operations, a central hub for all information and processes. By incorporating business intelligence and AI with Microsoft Dynamics 365 Supply Chain Management, users gain cross-departmental insights faster. The solution also creates more efficient processes, improves cost savings, optimises operations and improves forecasting accuracy using insights gleaned from real-time data. For example, food company Nestlé implemented Dynamics 365 Supply Chain Management, Finance and Commerce with the help of Microsoft partner KPMG to improve its accounting and supply chain reporting across its 2,000 brands in 188 countries. Another applicable use case is for MES, which are systems designed to help manufacturers track and manage operations in ways that ERP and process control systems may not fully cover. An MES grants visibility into data to make decisions that will result in efficient and optimised production. For those with regulations to consider – such as pharmaceuticals, food and beverages, and medical devices – MES helps drive industrial automation and lowers the cost of production while ensuring regulatory compliance and operational visibility. Combined with generative AI, employees can surface information and raise alarms faster, as well as track and manage ‘lean’ inventories while still meeting customer demands and expectations. When AI is implemented within a firm’s maintenance cycles, it enables predictive maintenance. This allows them to proactively avoid unplanned downtime by predicting when maintenance work needs to be carried out on assets and then optimising those repairs by scheduling them at the least disruptive time for production. AI can also use captured data to provide a real-time view of operations on the plant floor and equipment. This additional visibility improves efficiency and productivity. In response to the global delivery disruptions experienced during recent crises, manufacturers integrating AI to help with logistics management. “ Digitally transforming the industrial process unlocks automation in the quality control process”
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