Complaint management model of manufacturing products using text mining and potential failure identification
ISSN: 1754-2731
Article publication date: 2 November 2021
Issue publication date: 29 November 2022
Abstract
Purpose
This paper aims to propose a framework on complaint management system for quality management by applying the text mining method and potential failure identification that can support organization learning (OL). Customer complaints in the form of email text is the input of the framework, while the most frequent complaints are visualized using a Pareto diagram. The company can learn from this Pareto diagram and take action to improve their process.
Design/methodology/approach
The first main part of the framework is creating a defect database from potential failure identification, which is the initial part of the failure mode and effect analysis technique. The second main part is the text mining of customer email complaints. The last part of the framework is matching the result of text mining with the defect database and presenting in the form of a Pareto diagram. After the framework is proposed, a case study is conducted to illustrate the applicability of the proposed method.
Findings
By using the defect database, the framework can interpret the customer email complaints into the list of most defect complained by customer using a Pareto diagram. The results of the Pareto diagram, based on the results of text mining of consumer complaints via email, can be used by a company to learn from complaint and to analyze the potential failure mode. This analysis helps company to take anticipatory action for avoiding potential failure mode happening in the future.
Originality/value
The framework on complaint management system for quality management by applying the text mining method and potential failure identification is proposed for the first time in this paper.
Keywords
Acknowledgements
The authors thank the editor and the anonymous referees for their valuable comments and suggestions to improve the presentation of this paper. This work is partially funded by Lembaga Penelitian dan Pengabdian pada Masyarakat, Universitas Atma Jaya Yogyakarta.
Citation
Astanti, R.D., Sutanto, I.C. and Ai, T.J. (2022), "Complaint management model of manufacturing products using text mining and potential failure identification", The TQM Journal, Vol. 34 No. 6, pp. 2056-2068. https://doi.org/10.1108/TQM-05-2021-0145
Publisher
:Emerald Publishing Limited
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