Title: Discrete-event simulation and data analysis for process flow improvements in a cabinet manufacturing facility

Authors: Osama Mohsen; Sina Abdollahnejad; Narges Sajadfar; Yasser Mohamed; Simaan AbouRizk

Addresses: Civil and Environmental Engineering Department, University of Alberta, 9211 – 116 Street NW, Edmonton, Alberta, Canada ' Civil and Environmental Engineering Department, University of Alberta, 9211 – 116 Street NW, Edmonton, Alberta, Canada ' Civil and Environmental Engineering Department, University of Alberta, 9211 – 116 Street NW, Edmonton, Alberta, Canada ' Civil and Environmental Engineering Department, University of Alberta, 9211 – 116 Street NW, Edmonton, Alberta, Canada ' Civil and Environmental Engineering Department, University of Alberta, 9211 – 116 Street NW, Edmonton, Alberta, Canada

Abstract: Project uniqueness and high degrees of customisation have always been challenging characteristics of construction projects and many related operations. This paper describes the simulation of a production line in a cabinet manufacturing facility carried out with the aim of better understanding and improving the production processes particularly associated with mass customisation. Discrete-event simulation (DES) using Simphony.NET, a simulation modelling tool developed at the University of Alberta, is used to investigate and analyse processes in an existing facility. The purpose is to optimise productivity, reduce work-in-progress, and decrease idle time. The cabinet manufacturing factory in the presented study operates multiple production lines, produces different product types, and uses varying materials and finishings. In this specific case study, the simulation model is used to explore the challenges associated with increasing production to satisfy the rising demand of customised products. The result of the simulation study provides valuable information to achieve this goal.

Keywords: discrete-event simulation; DES; cabinet manufacturing; mass customisation; construction manufacturing; workflow improvement; modelling; simulation; data analysis.

DOI: 10.1504/IJSPM.2021.113075

International Journal of Simulation and Process Modelling, 2021 Vol.16 No.1, pp.57 - 65

Received: 06 Apr 2019
Accepted: 27 Jun 2020
Published online: 17 Feb 2021 *

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