Abstract

A literature review and gap analysis indentifies key limitations of industry best practice when modelling of supply chains. To address these limitations the paper reports on the conception and development of an integrated modelling methodology designed to underpin the analytical design of complex supply chains. The methodology is based upon a systematic deployment of EM, CLD, and SM techniques; the integration of which is achieved via common modelling concepts and decomposition principles. Thereby the methodology facilitates: (i) graphical representation and description of key “processing”, “resourcing” and “work flow” properties of supply chain configurations; (ii) behavioural exploration of currently configured supply chains, to facilitate reasoning about uncertain demand impacts on supply, make, delivery, and return processes; (iii) predictive quantification about relative performances of alternative complex supply chain configurations, including risk assessments. Guidelines for the application of each step of the methodology are described. Also described are recommended data collection methods and expected modelling outcomes for each step. The methodology is being extensively case tested to quantify potential benefits & costs relative to current best industry practice. The paper reflects on preliminary benefits gained during industry based case study modelling and identifies areas of potential improvement.

Highlights

  • The capabilities envisaged for this methodology were as follows

  • Previous existing integrated modelling methodologies were reviewed that were previously designed to integrate the use of different modelling techniques in other manufacturing system domains

  • Analysis of the reviewed work showed that no integrated methodology suitable for modelling complex supply chains which can fulfil the set of capabilities required to analytically design complex supply chains

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Summary

Introduction

With reference to manufacturing enterprises MEs and their supply chains, the term complexity has been defined in different ways. Kambil 2 states that complexity is related to the amount of variety at and across processes, while Snowden 3 defines complexity in terms of visibility and order in casual relationships 4. Greater emphasis is often being placed on redesigning products and processes, so that the negative impacts of product variety due to product proliferation and thence increased system complexity can be partially overcome 6. This kind of phenomenon has led modern organizations to implement new supply chain paradigms and adopt new techniques to support rapid design, analysis, and implementation of these new paradigms 7

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