Increasing productivity by generating optimal cutting patterns in the rolling mill of Shahid Bahonar Copper Industries Corporation

Cutting stock material, such as paper rolls or sheet metal, into small pieces to fulfil customer orders, is defined as a cutting stock problem. The case study company has no optimal cutting plan that meets both customer demands and operational constraints. The cutting stock problem can be mathematically optimised in industrial applications to reduce production costs. The study's main objective was to maximise production time by minimising the number of setups resulting from changing machine blades. Furthermore, we want to minimise the difference between the amount produced, and the amount requested from each order. A mixed integer nonlinear model is proposed to reduce production costs by the company's requirements, then the model is linearised. A comparison was made between the model output and the current company method, revealing that the trim loss is more than 4% for the cutting patterns obtained from the proposed model. Furthermore, a 46.7% improvement in setup time can be seen in some sets of orders. As compared to the traditional method, the proposed model has reduced the solution time to a few seconds in some cases, while the traditional method requires a minimum of 20 minutes.