A MILP for multi-machine injection moulding sequencing in the scope of C2NET Project

Authors

  • Beatriz Andres Universitat Politècnica de València
  • Raquel Sanchis Universitat Politècnica de València
  • Raúl Poler Universitat Politècnica de València
  • Manuel Díaz-Madroñero Universitat Politècnica de València
  • Josefa Mula Universitat Politècnica de València

DOI:

https://doi.org/10.4995/ijpme.2018.8913

Keywords:

MILP, sequencing, injection, moulds, multi-machine, automotive

Abstract

The goal of C2NET European H2020 Funded Project is the creation of cloud-enabled tools for supporting the SMEs supply network optimization of manufacturing and logistic assets based on collaborative demand, production and delivery plans. In the scope of C2NET Project, and particularly in the Optimisation module (C2NET OPT), this paper proposes a novel holistic mixed integer linear programing (MILP) model to optimise the injection sequencing in a multi-machine case. The results of the MILP will support the production planner decision-making process in the calculation of (i) moulds setup in certain machines, and (ii) the amount of products to produce in order to minimise the setup, inventory, and backorders costs. The designed MILP takes part of the algorithms repository created in C2NET European Funded Project to solve realistic industry planning problems. The MILP is verified in realistic data considering three data sets with different sizes, in order to test it’s the computation efficiency.

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Author Biographies

Beatriz Andres, Universitat Politècnica de València

Research Centre on Production Management and Engineering (CIGIP)

Raquel Sanchis, Universitat Politècnica de València

Research Centre on Production Management and Engineering (CIGIP),

Raúl Poler, Universitat Politècnica de València

Research Centre on Production Management and Engineering (CIGIP)

Manuel Díaz-Madroñero, Universitat Politècnica de València

Research Centre on Production Management and Engineering (CIGIP)

Josefa Mula, Universitat Politècnica de València

Research Centre on Production Management and Engineering (CIGIP)

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Published

2018-01-31

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Papers