Date on Master's Thesis/Doctoral Dissertation

5-2014

Document Type

Doctoral Dissertation

Degree Name

Ph. D.

Department

Industrial Engineering

Committee Chair

Alexander, Suraj Mammen

Committee Co-Chair (if applicable)

Evans, Gerald

Committee Member

Evans, Gerald

Committee Member

Biles, William

Committee Member

Usher, John

Committee Member

Gupta, Mahesh C.

Subject

Business logistics; Industrial efficiency; Industrial management

Abstract

Lean supply chains with cost optimized production and logistics processes in the automotive industry have become a benchmark for other industries. Short delivery times, low inventories and high availability are parameters which assume a robust supply chain. In industrial practice we see, however, that in the After Sales business particularly related to the supply of automotive spare parts, that there are always unforeseen delays in delivery. In order to avoid service level losses on the focal firm level due to missing parts it is necessary to understand the risk structure on the supplier side. For this reason, a risk model for the After Sales inbound SC is developed through this work. Based on an extensive analysis of delivery data a central risk size was derived. Comprehensively researched SC risks are supplemented by After Sales specific risks derived through an empirical supplier survey. A reference network, which is methodologically based on the Bayesian theorem, to control the dynamic relationships was developed. The developed risk model allows for the identification of proactive and reactive measures by top-down and bottom-up analyzes to make lean supply chains for after sales requirements in the best cases robust and resilient. A big advantage of the developed model is not only the ability to quantify the cause and effect of supply chain risks but also to describe the constantly changing risk environment of the supply chain through continuous belief updates within the model. The risk analysis in the developed model potentially reduces the delivery delay of spare parts by 65 percent and diminishes the buffer stock value by 50 percent. To achieve such improvements in the real world organizations must be able to implement measures in explicit SC risk clusters for sustainable supply chain performance and inventory management. Improvements in the internal supplier processes, due to risks like prioritized series supply, or inappropriate after sales supply strategies are necessary. Utilizing the developed After Sales Risk Management Model (ASRIM) organizations will be able to implement proactive risk mitigation strategies, facilitating agile SC performance, while simultaneously reducing buffer stocks.

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