Open AccessSupply chain integration within mass customization: Tactical procurement, production and distribution modeling
Author(s) -
Mouad Benbouja,
Achraf Touil,
Abdelwahed Echchatbi,
Abdelkabir Charkaoui
Publication year - 2021
Publication title -
journal of industrial engineering and management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.385
H-Index - 29
eISSN - 2013-8423
pISSN - 2013-0953
DOI - 10.3926/jiem.3182
Subject(s) - supply chain , mass customization , original equipment manufacturer , procurement , benchmark (surveying) , production (economics) , interdependence , computer science , supply chain management , personalization , modular design , automotive industry , operations research , process management , industrial engineering , systems engineering , engineering , business , marketing , geodesy , aerospace engineering , world wide web , economics , political science , law , macroeconomics , geography , operating system
Purpose: The actual market characteristic oriented toward customers’ requirements compels decision-makers to foresee customization abilities. Mass customization represents a valuable approach to combine customizable offers with mass production processes. From a supply chain standpoint, this paper attempts to develop an integrated procurement, production and distribution modeling to describe the generated framework structure formulation within tactical decision planning level.Design/methodology/approach: The paper provides a mixed integer linear programming model of a three echelon supply chain illustrated from the automotive industry with (a) customers: Original Equipment Manufacturers (OEMs) identified as leaders and (b) first-tier supplier: wiring harnesses manufacturer (c) second-tier supplier: raw material supplier, identified as followers. The model formulation is depicted through dyadic relationships between stakeholders considering the specific operation enablers of the environment such as make to order, modular approach in addition to the corresponding inventory management policy.Findings: The integrated model is solved by an exact method which illustrates the feasibility of the formulation in addition to the observance of the applied constraints. A sensitivity analysis is performed to highlight the interdependency across some key parameters to provide managerial insights within the studied framework while keeping the optimal solvability of the model.Research limitations/implications: The limitation of this study is the computational experiment study. An extensive experiment with a real-word case will outline the optimal solvability status of the exact method and the necessity for a performance benchmark through the approximate solving approaches.Originality/value: The present research aims to contribute as first studies toward mathematical modeling for supply chain decision planning endeavor operating within mass customization business model.