Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/32837
Title: Development of a process mining system for supporting knowledge discovery in a supply chain network
Authors: Lau, HCW
Ho, GTS
Zhao, Y
Chung, NSH
Keywords: Business intelligence
Customer satisfaction
Supply chain network
Issue Date: 2009
Publisher: Elsevier
Source: International journal of production economics, 2009, v. 122, no. 1, p. 176-187 How to cite?
Journal: International journal of production economics 
Abstract: In today's competitive environment, business organizations are forced to maintain their competitive advantage by their ability to cut costs, increase revenue and uncover hidden issues. In order to enhance the visibility and transparency of value added information in a supply chain network, a process mining system is proposed for discovering a set of fuzzy association rules based on the daily captured logistics operation data, within the network. The proposed methodology provides all levels of employees with the ability to enhance their knowledge and understanding of the current business environment. Once interesting association rules have been extracted, organizations can identify the root-causes of quality problems in a supply chain and improve performance by fine-tuning the configuration of process parameters in specified processes. The application of the proposed methodology in a case company has also been studied. The prototype system has been developed and evaluated after performing a spatial analysis. The results obtained indicate that the system is capable of extracting high-quality and actionable information in the case company.
URI: http://hdl.handle.net/10397/32837
ISSN: 0925-5273
DOI: 10.1016/j.ijpe.2009.05.014
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