Nicolas Anich1 and Manuel Mateo1

1 Universitat Politècnica de Catalunya, ETSEIB, Diagonal 647, 08028 Barcelona, Spain.,

Abstract. Nowadays, some companies have several plants as a result of acquisitions or mergers, i.e. horizontal integration. Another similar situation occurs for groups of companies which maintain the original brands but have centralized the manufacturing decisions. This leads to manufacturing the same, or nearly the same, product under different brands. Moreover, the set of suppliers becomes common to all the plants of the company or the pool of companies. It is necessary to analyse whether there is a better scenario in terms of minimum costs, according to the used resources. A methodology is applied to synergistic manufacturing in the chains. The considered case study is located in the automotive sector, using data from a group of companies with several brands.

Keywords: supply chain risk management, synergies, manufacturing.

1. Introduction

Supply Chain Management (SCM) involves all activities to meet the needs of the chain customers, considering processes such as procurement, manufacturing, warehousing, distribution and reverse logistics. Previously, all the links in a supply chain (SC) concerning those companies directly or indirectly involved in satisfying a customer request had to be defined. This is part of a broader concept called supply chain configuration or design ([1]).

However, the design of these chains must be subject to the definitions of each business. This will influence the strategies, configuration typologies and associated risks, as well as their evaluation in terms of efficiency and effectiveness [2]. A network must adapt not only to changes in demand but also to a set of governmental, meteorological and geological situations. This results in a set of risks.

The great dilemma that arises is how to reach the optimal trade-off in the capacity necessary to maintain a sustainable advantage, without having a high degree of complexity. Moreover, the different agents in a chain must be aligned with the objectives and there must be a high degree of collaboration between them [3].

Complexity, both in static and dynamic terms, implies structure, topology and links. It must provide enough flexibility in case of risks. One solution that can be developed in the chain is a synergistic configuration, to mitigate risks and operate efficiently. This has been of great interest in the Supply Chain Risk Management (SCRM), whose purpose is to improve efficiency and effectiveness ([4]).

Most of the works on supply chain design, especially those related to risks, confront problems in a single chain. However, there is little research on the impact of risks in multi-business chains and, especially, in synergistic chains and their configurations.

2. Methodology for Synergic Supply Chains considering manufacture. Application in the car manufacturing

A general methodology for the redesign of SC risk management, composed of 7 steps, is described in [5]. To determine the degree of synergies, 9 types of decisions relating to the three main levels of decision (strategic, tactical and operational) are established: At the operational level: procurement, manufacturing input, manufacturing output, inbound distribution centre, outbound distribution centre and transport to the customer. At the tactical level: planning should be evaluated. At the strategic level: strategy and dealing with risk are included.

The SC to be evaluated corresponds to a set of different car manufacturers managed by an international manufacturing corporation. This group sells cars under different brand names. Given the demand of a set of m vehicle models Di (i=1,…,m) which are sold under b different brands (h=1,…,b), a set of n manufacturing plants (j=1,…,n) and a total of p lines among all the plants (l=1,…,p). There are lj assembly lines in the plant j. Initially, each line in a plant j is manufacturing a car model i. Therefore, mpi,j (mpi,j ∈ {0,1}) takes value 1 if model i is manufactured in the plant j and 0, otherwise. A model i requires a certain single resource r from a set of q kinds of resources (r=1,…,q). Therefore, the parameter mri,j (mri,r ∈ {0,1}) takes value 1 if model i requires resource j to be manufactured and 0, otherwise. ).

In this case, the evaluation has led to the following results: Procurement. Score=1. Manufacturing input. Score=0.62. Manufacturing output. Score=0.73. Transport, inbound and outbound distribution. Independent at this stage. Score=0. Planning. Score=0.42 (mean of both values). Strategy. Score=0.91. Risk. Score=0.92. If we add the seven values, the result is 4.60 out of 9.


  1. Klibi, W., Martel, A., Guitouni, A. The design of robust value-creating supply chain networks: A critical review. European Journal of Operational Research 203(2), 283–293(2010).
  2. Lee, H. L. The Triple-A Supply Chain. Harvard Business Review, 1–12. (2004)
  3. Chopra, S., Meindl, P. Supply Chain Management: Strategy, Planning, and Operation. (2016).
  4. Nagurney, A., Qiang, Q. Fragile networks: identifying vulnerabilities and synergies in an uncertain age. International Transactions in Operational Research 19(1–2), 123–160 (2012).
  5. Anich, N., Mateo, M. Development of a methodology for the management of risk in a supply chain. Application to the pharmaceutical sector. 13th International Conference on Industrial Engineering and Industrial Management (2019).


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Proceedings of the 15th International Conference on Industrial Engineering and Industrial Management and XXV Congreso de Ingeniería de Organización Copyright © by (Eds.) José Manuel Galán; Silvia Díaz-de la Fuente; Carlos Alonso de Armiño Pérez; Roberto Alcalde Delgado; Juan José Lavios Villahoz; Álvaro Herrero Cosío; Miguel Ángel Manzanedo del Campo; and Ricardo del Olmo Martínez is licensed under a Creative Commons Attribution 4.0 International License, except where otherwise noted.

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