Full metadata record
|dc.contributor||Department of Computing||en_US|
|dc.contributor.advisor||Liu, James N. K. (COMP)||-|
|dc.publisher||Hong Kong Polytechnic University||-|
|dc.rights||All rights reserved||en_US|
|dc.title||Quantitative spare parts modelling for supply chain management||en_US|
|dcterms.abstract||With the rapid technological development in the 21st century, more and more different kinds of electronic products are evolving in people’s daily life. These electronic products are all connected with human purpose. When people use and enjoy conveniences that electronic products give them, it triggers the need for a huge after sales service system to support these electronic products in the meantime. This system has been playing more and more important role for large-scale manufacturers. It can improve the image of the manufacturer in the market that is full of competition; however it also has brought many problems in supply chain system, which means the quantization of spare parts is becoming the most concerned problem in this field. Not to mention the system cost that could be declining with quantified spare parts. To achieve the accuracy and integrity in quantization of spare parts, we will need scientific methods and algorithms to work out. This dissertation will provide an original new method which gives an exploration way to execution of system and help management to make decision or strategy in supply chain processing. The dissertation will focus on the processing of spare parts as below: Firstly, starting from the electronic products life cycle and failure mechanism of electronic components to demonstrate its distribution and periodization frequency, there isn’t having such organized rule that can indicate how the failure appears. The failure appears randomly and abiogenesis. We won’t talk about the failure of a certain single product, because from the perspective of a whole spare parts supply chain, it makes no sense if the failure appears only in a single product. We will look into a collection of the whole failure data to conduct analysis, and find the similarity and any correlation from that. Secondly, introducing the SPCC method (spare parts covering configuration method), analyze its application and feasibility. This method will depend on the statistical failure data to show how the spare parts run in the supply chain system and perform in simulation. The extension of this method finds the way to quantify spare parts under the following dimensionality: time dimension, failure dimension and replenishment dimension. Based on that, the dissertation gives a new model that can change the traditional pattern of supply chain system from passive to active and to optimize the dynamic value of spare parts preparation. Finally, introducing and discussing this method to modern supply chain system of Internet of Things (IOT). We will provide some idea to improve the supply chain system using this method. In conclusion, the study has a huge added value behind the spare parts configuration, this dissertation presents a new way to improve spare parts configuration. This study will give innovative rooms for future application in spare parts supply chain management.||en_US|
|dcterms.extent||x , 68 pages : color illustrations||en_US|
|dcterms.LCSH||Electronic apparatus and appliances.||en_US|
|dcterms.LCSH||Hong Kong Polytechnic University -- Dissertations||en_US|
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|b28251994.pdf||For All Users (off-campus access for PolyU Staff & Students only)||1.97 MB||Adobe PDF||View/Open|
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