Production Optimization of a PVC Pipe Manufacturing Industry

Production capacity is not always used to its full potential due to various bottlenecks arising within the production line. Identifying and rectifying the bottlenecks can thus facilitate an optimal production output, which will eventually maximize the total profit. We identified two important bottlenecks within the production line by the application of the theory of constraints (TOC). The first bottleneck was associated with the machine capacity, causing a mismatch in demand and supply, and this constraint has been elevated by a financial investment decision. The TOC methodology is again applied to find and solve the next bottleneck. The random job-machine assignment was found to be the second bottleneck. A potential decrease in the makespan has been observed by applying two mixed integer linear programming models (MILP models). Job is not splittable in model 1, whereas job is splittable in model 2, and the setup time is independent of any sequences. The MILP model is executed using Python. The results will give the job-machine assignment which potentially marked a reduction in the makespan. The results are then compared with the original makespan. Potential reduction in makespan will meet the demand in time as well as the industry can now manufacture more products within the given time. The production operation has been improved compared to the current operation by a reduction in makespan. Suitable suggestions and recommendations are given at the end based on the results of the study.