Title: Simulation-based cost optimisation of a risk mitigation strategy in an assembly job manufacturing process: a case study from the offshore wind industry

Authors: Adolfo Lamas-Rodríguez; Javier Pernas-Álvarez; Inés Taracido-López; Santiago-José Tutor-Roca

Addresses: Navantia, Ctra. de la Circunvalación s/n, Ferrol, 15403, Spain; Universidade da Coruña and UMI Navantia-UDC, Campus de Esteiro s/n, Ferrol, 15403, Spain ' University of A Coruña, Campus de Esteiro s/n, Ferrol, 15403, Spain; Simulation Team, Genoa University, via Opera Pia 15, 16145, Genoa, Italy ' Navantia, Ctra. de la Circunvalación s/n, Ferrol, 15403, Spain ' UMI Navantia-UDC, CIT Campus de Esteiro s/n, Ferrol, 15403, Spain

Abstract: Despite holding very high expectations regarding installed capacity and planned investments, offshore wind energy is currently facing important challenges to align itself with the levelised cost of energy of other renewable energies such as solar power or onshore wind. In this context, we aim at putting DES optimisation at offshore wind's disposal and leverage its advantages proved in other areas. To accomplish so, we have performed a DES-based optimisation of the routing strategy and the net income of an offshore wind foundations manufacturing project affected by very important delays due to covid-19 impact and material supply issues. The problem applies to a constraint-based multi-level assembly job shop where we use dispatching rules to model the routing decision. Overall, we have provided the company with an optimised schedule, due dates, expected penalties, expected net income and a detailed ongoing DES model to be used in further stages of the project.

Keywords: discrete-event simulation; DES; simulation-based optimisation; offshore wind; Industry 4.0; dispatching rules; assembly job-shop; constrained-based simulation.

DOI: 10.1504/IJSPM.2021.10044415

International Journal of Simulation and Process Modelling, 2021 Vol.17 No.2/3, pp.116 - 126

Received: 01 Feb 2021
Accepted: 10 Jun 2021

Published online: 24 Mar 2022 *

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