Design of inventory pools in spare part support operation systems

Abstract

The objective of a spare part support operation is to fulfill the part request order with different service contracts in the agreed response time. With this objective to achieve different service targets for multiple service contracts and the considerations of inventory investment, it is not only important to determine the inventory policy but also to design the structure of inventory pools and the order fulfilment strategies. In this research, we focused on two types of inventory pools: multiple inventory pool (MIP) and consolidated inventory pool (CIP). The idea of MIP is to maintain separated inventory pools based on the types of service contract, while CIP solely maintains a single inventory pool regardless of service contract. Our research aims to design the inventory pool analytically and propose reserve strategies to manage the order fulfilment risks in CIP. Mathematical models and simulation experiments would be applied for analysis and evaluation.

Keywords:

• spare part
• logistics system
• inventory control
• service contract
• response time
• service fill rate

Acknowledgements

The authors would like to thank the Research Grants Council of Hong Kong for supporting the research through RGC 620609, and the two reviewers for their suggestions in this paper.

Additional information

Notes on contributors

Daniel Y. Mo

Daniel Y. Mo received a BEng (2003) degree and an MPhil (2005) degree in Industrial Engineering and Engineering Management from the Hong Kong University of Science and Technology. He was awarded the Sir Edward Youde Memorial Fellowship twice, and exchanged to Georgia Institute of Technology during his study. Before his further pursuing a PhD, he worked in NetApp as a regional logistics planner for several years to manage the spare part inventories in Asia Pacific region. He has also conducted a number of consultant projects with Stanford University and international companies in USA, Hong Kong and Mainland China. His research interests include supply chain management, logistics network optimization and system design. He now works as a Lead Analyst in Emerson.

Mitchell M. Tseng

Mitchell M. Tseng is the Associate Vice-President for Research & Innovation for Office of the Vice-President for Research & Graduate Studies, a Professor of Industrial Engineering and Logistics Management, and the Director of Advanced Manufacturing Institute at the Hong Kong University of Science and Technology. He holds a BS degree in Nuclear Engineering from the National Tsing Hua University in Taiwan, an MSc degree and a PhD in Industrial Engineering from Purdue University. He joined the Hong Kong University of Science and Technology as the founding department head of Industrial Engineering in 1993 after holding executive positions at Xerox and Digital Equipment Corporation for almost two decades. He previously held faculty positions at the University of Illinois at Champaign Urbana and Massachusetts Institute of Technology. His research interests include product design, mass customization, information systems applications, and business process design.

Raymond K. Cheung

Raymond K. Cheung received a BS (1984) degree in Applied Computational and Mathematical Science and an MA (1985) degree in Applied Mathematics from York University, Canada, and the MA (1989) degree and PhD (1993) degree in Civil Engineering and Operations Research from Princeton University. After winning the George Dantzig prize for the best dissertation in Operations Research and Management Sciences internationally, and a Career Award from the National Science Foundation of America while teaching in the United States, he returned to Hong Kong to initiate the logistics research and teaching programs in 1996. At Hong Kong University of Science and Technology, he was the founding director of the HKUST Logistics and Supply Chain Forum and helped to establish the first Engineering Degree in Logistics Management in Hong Kong and a computational laboratory for transportation and logistics. His research interests include transportation systems management, logistics and distribution planning, network modeling and optimization, and stochastic and dynamic optimization.