Universiti Teknologi Malaysia Institutional Repository

Clustering of maintenance work data for failure mode discrimination

Abdullah, Abdul Rani Achmed and A. Jalil, Siti Zura and Nik Mohamed, Nik Nadzirah (2021) Clustering of maintenance work data for failure mode discrimination. In: 1st Indian International Conference on Industrial Engineering and Operations Management, IEOM 2021, 16 - 18 August 2021, Virtual, Online.

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Official URL: https://www.ieomsociety.org/proceedings/2021india/...


A fast and efficient method to discriminate failure modes from maintenance work orders will facilitate and motivate proactive maintenance development. This paper aims to propose a faster and as efficient clustering methodology that differs from previous text mining attempts. Text mining attempts are very dependent on correctly classifying text but the method proposed here is text independent. It is based on time to repair (TTR), time before failure (TBF) and other available identifiers. Using K-means as the clustering algorithm, the processing speed was greatly reduced. Singularity of discriminated failure modes were as good as previous text mining attempts.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:Clustering, Failure mode, K-means
Subjects:T Technology > T Technology (General)
Divisions:Razak School of Engineering and Advanced Technology
ID Code:96684
Deposited By: Widya Wahid
Deposited On:17 Aug 2022 14:48
Last Modified:17 Aug 2022 14:48

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