A new approach for product reliability prediction by considering the production factory lifecycle information

Shashi Bhushan Gunjan, D.S. Srinivasu and Ramesh Babu N

Reliability Engineering and System Safety, 2025, vol. 258, issue C

Abstract: Product reliability prediction is essential for OEMs to plan product maintenance and design improvement. Traditional approaches rely on 'product' lifecycle data for reliability prediction, often not capturing the uncertainties in OEMs' decision-making. To address this, the present work focuses on 'factory' lifecycle information in reliability prediction by introducing the concept of 'factory age,' i.e., cumulative interval for the observed factory lifecycle. The failure times for each product, in each factory age interval, were used to estimate the Weibull parameters, creating temporal data. A combination of grey- and support vector machine (SVM)-models, which complement each other in capturing global and local trends, and handling uncertainty from limited temporal data, was proposed to forecast the Weibull parameters accurately in the future factory age interval. The proposed approach was validated on two failure modes in a factory-producing turning centers, using data from the first 11 factory age intervals for model development. Reliability predictions for the last three intervals achieved root mean square errors (RMSEs) of 0.67 % and 1.48 % for failure modes I and II. Comparatively, individual grey (4.37 %, 5.11 %) and SVM (8.03 %, 10.60 %) models yielded higher RMSEs, while other reported models in literature showed in the range of 1.63 %–34.07 %, demonstrating the proposed approach's efficacy.

Keywords: Factory lifecycle; Grey prediction model; Weibull distribution; SVM; Factory age (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832025001188
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:258:y:2025:i:c:s0951832025001188

DOI: 10.1016/j.ress.2025.110915

Access Statistics for this article

Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares

More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().