Planning is essential for organizations and businesses: it helps establish appropriate goals, reveals weaknesses (and strengths), increases efficiency, reduces risks, and enhances decision-making. The complexity of planning and the need for re-planning have increased due to the exceptional circumstances we are experiencing, such as disruptions in the supply chain, the need to save energy consumption to minimize costs, ecological transition, and increasingly sophisticated manufacturing processes, among others. 

The initial situation of this factory in the aerospace machining sector, is characterized by a manual process, limitations in adaptability, and the inability to simulate scenarios. Additionally, issues related to delays in parts and non-productive hours posed challenges in production management and operational efficiency.

• Manual process: The factory relied heavily on human labour to carry out its operations. This influenced the speed, quality, and efficiency of production. 

• Classic algorithm: The factory used traditional methods for production scheduling and task assignment, which limited its flexibility and adaptability to respond to changes in demand or operational conditions. Data obtained over two months on the 35 production machines included: 

• 487 delayed pieces resulting from difficulties in meeting delivery deadlines or problems in production planning and execution. 
• 2736 non-productive hours or downtime in its machines or processes caused by maintenance issues, adjustments, unplanned downtime, and other factors. 

• Limitations in adaptability: The company had limited ability to modify its processes or equipment in an agile manner in response to changes in the environment or market needs, affecting its competitiveness. 
• Inability to simulate scenarios hindered the factory from conducting predictive analysis and testing different production strategies before implementation, making decision-making challenging.