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Assessing Supply Chain Risk Adopting Reliability Tools
Linköping University, Department of Management and Engineering, Production Economics. Linköping University, The Institute of Technology.
Department of Mechanical and Industrial Engineering, University of Brescia, Italy.
Linköping University, Department of Management and Engineering, Production Economics. Linköping University, The Institute of Technology.
(English)Manuscript (preprint) (Other academic)
Abstract [en]

The gradual expansion of supply chains has developed its own risk. A single disruption at any element or flow will eventually affect the whole system. It can be observed now that there has been an increase in awareness of the risks involved with supply chain disruption. Many have shown concern over the significance of reliable systems which can identify risk prior to the event, assess the consequences of risk events, and, at the same time, be capable of controlling and managing the events that lead to disruption risk throughout supply chain.

However, risk issue has not been thoroughly evaluated from the perspective of supply chain performance measures. This is possibly due to the lack of detailed and specific measurement tools for systematically identifying and evaluating supply chain risks. In this study, reviews conducted on relevant journals have guided our search to identify significant components in developing supply chain risk analysis models i.e., risk identification, estimation and evaluation. We explore each component and highlight the respective requirements.

Acknowledging the well-developed risk analysis methods in the Reliability Engineering field, we consider the possibility of adopting the same approaches in the field of Supply Chain Risk Management. Thus we evaluate the advantages and disadvantages of several risk analysis methods applied in Reliability Engineering field, for example, Failure Modes and Effect Analysis (FMEA), Fault Tree Analysis (FTA), Event Tree Analysis (ETA), Hazards and Operability Analysis (HAZOP), Cause and Effect Diagram (CAED) and Analytical Hierarchy Process (AHP).

We analyse the similarities and gaps between the two fields with the aim to propose a tool that is suitable for supply chain risk analysis. We find that the use of a stand-alone tool of FMEA or a hybrid application of FTA and AHP is potentially most appropriate in Supply Chain Risk Management.

Keyword [en]
Supply Chain, Risk Management, Risk Analysis, Risk Assessment, Reliability
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-78757OAI: oai:DiVA.org:liu-78757DiVA: diva2:535608
Available from: 2012-06-20 Created: 2012-06-20 Last updated: 2012-06-20Bibliographically approved
In thesis
1. Supply Chain Risk Management: Identification, Evaluation and Mitigation Techniques
Open this publication in new window or tab >>Supply Chain Risk Management: Identification, Evaluation and Mitigation Techniques
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Supply chains have expanded rapidly over the decades, with the aim to increase productivity, lower costs and fulfil demands in emerging markets. The increasing complexity in a supply chain hinders visibility and consequently reduces one’s control over the process. Cases of disruption such as the ones faced by Ericsson and Enron, have shown that a risk event occurring at one point of the supply chain can greatly affect other members, when the disruption is not properly controlled. Supply chain management thus faces a pressing need to maintain the expected yields of the system in risk situations. To achieve that, we need to both identify potential risks and evaluate their impacts, and at the same time design risk mitigation policies to locate and relocate resources to deal with risk events.

This dissertation aims to analyse how supply chain risks could be effectively managed. This is done firstly by positioning the research agenda in supply chain risk management (SCRM). Then, methods for effective management of supply chain risk are identified and analysed. In order to find these, we develop a research framework in which the supply chain system is divided into subsystems based on the operations of make, source and deliver; as well as on material, financial and information flows. Furthermore, research questions are raised in order to understand the impact of risks on supply chains, to identify the performance measures for monitoring supply chains, and to determine risk mitigation strategies for improving system performances.

This dissertation includes a bibliometric analysis of relevant literature of SCRM published in recent years. Based on the co-citation analysis, we identify the changing interest in SCRM, from performance-focused individual issues in the early years to integrated system issues with management perspective in recent years. We also identify the growing importance of information issues in SCRM. However, there is a relative lack of research into risk mitigation focusing on information flows in the literature.

This dissertation also develops a conceptual model for analysing supply chain risk. The adoption of tools from the established field of reliability engineering provides a systematic yet robust process for risk analysis in supply chains. We have found that the potential use of a stand-alone tool of Failure Modes and Effect Analysis (FMEA) or a hybrid application of Fault Tree Analysis (FTA) and Analytical Hierarchy Process (AHP), will be most appropriate in SCRM.

Apart from above mentioned studies, this dissertation then includes three manuscripts respectively investigating the risk mitigation policies in SCRM. First, we suggest a dynamic pricing policy when facing supply yield risk, such as price postponement, where price is determined only after receiving the delivery information. This postponed pricing, can improve the balance between supply and demand, especially when the delivery quantity is small, demand has a low uncertainty and there is a wide range when demand is sensible to price change. In another paper, a system dynamics model is developed to investigate the dispersion of disruption on the supply chain operation as well as along the network. Based on this simulation model, policies are tested to observe their influence to the performance of the supply chain. The study results support the benefit of a dual-sourcing strategy. Furthermore, information sharing, appropriate order splitting and time to react would further improve the supply chain performance when disruption strikes. In the last paper, we study how capacity should be expanded when a new product is introduced into the market. The major risk here is due to a quick capacity expansion with large investments which could be difficult to recover. Using the Bass diffusion model to describe demand development, we study how capacity expansion, together with sales plan could affect the economics of the system. Using sales information for the forecast, delaying the sales and adding initial inventories, should create a better scheme of cash flows.

This dissertation contributes in several ways to the research field of SCRM. It plots research advancements which provide further directions of research in SCRM. In conjunction with the conceptual model, simulations and mathematical modelling, we have also provided suggestions for how a better and more robust supply chain could be designed and managed. The diversified modelling approaches and risk issues should also enrich the literature and stimulate future study in SCRM.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2012. 57 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1459
Keyword
Supply chain risk management, risk analysis, risk control, co-citation, system dynamics, modelling
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-78763 (URN)978-91-7519-866-8 (ISBN)
Public defence
2012-06-15, ACAS, Hus A, Campus Valla, Linköpings universitet, Linköping, 10:15 (English)
Opponent
Supervisors
Available from: 2012-06-20 Created: 2012-06-20 Last updated: 2012-06-20Bibliographically approved

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