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863. Optimizing Shoe Injection Machine Utilization: A Heuristic Approach

Invited abstract in session MC-49: Lot-sizing with industrial applications I, stream Lot Sizing, Lot Scheduling and Production Planning.

Monday, 12:30-14:00
Room: M1 (building: 101)

Authors (first author is the speaker)

1. Rui Borges Lopes
Dep. of Economics, Management and Industrial Engineering, CIDMA / University of Aveiro
2. Adelaide Cerveira
Mathematics Department, UTAD & LIAAD/INESC-TEC
3. Eliana Costa e Silva
CIICESI, ESTG, Instituto Politécnico do Porto
4. Norberto Jorge Gonçalves
Physics Department, University of Trás-os-Montes e Alto Douro
5. Conceição Nogueira
Matemática, Instituto Politécnico de Leiria

Abstract

In the 174th European Study Group with Industry, a footwear company put forward a challenge that consisted of optimizing the utilization of one of its shoe injection machines. This machine, capable of high cadence, has the versatility to produce various types of shoes in different colors and sizes. In order to increase its utilization, the company wanted to reduce setup times associated with mold and color changes, as it had a significant impact. To this end, it was to be determined the production sequence that would lead to the highest throughput in the given planning horizon.

To tackle this problem, new constructive and improvement methods were developed and incorporated into a metaheuristic, specifically the Greedy Randomized Adaptive Search Procedure (GRASP). The GRASP was tested using both an academic and a real-world instance. For the academic instance, results were compared with an exact approach, while for the real-world instance a comparison was made with the actual planning of the company. This presentation will discuss the obtained results and will address some of the managerial insights gained from this study.

Keywords

Status: accepted

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