Manufacturing cost reduction in a filling process of aerosol products

Abstract

This research focuses on the development of heuristics that help reduce the production cost of an aerosol filling process of a case study company, while satisfying all related constraints, including production capacity and due dates. The proposed heuristics are a two-phase one, where the initial solutions are first constructed based on simple dispatching rules, and, once completed, such solution is then iteratively improved by two different improvement heuristics, namely 2OPT and Node Shift. A tabu list is also embedded within such a framework to help reduce its computational time. We have assessed the performances of these heuristics based on 6 different data sets acquired from the case study company. When compared to the current practice, we find that the devised heuristics could help reduce makespan, labour cost, and delivery delay by 0.34%, 4.94%, and 24 days, respectively. In addition to these direct benefits, the devised heuristics could potentially reduce the workload of the planner by at most 20%.