Discrete Random Renewable Replacements after the Expiration of Collaborative Preventive Maintenance Warranty

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dc.citation.issue18
dc.citation.volume12
dc.contributor.authorChen H
dc.contributor.authorChen J
dc.contributor.authorLai Y
dc.contributor.authorYu X
dc.contributor.authorShang L
dc.contributor.authorPeng R
dc.contributor.authorLiu B
dc.contributor.editorFerreira MAM
dc.date.accessioned2024-11-12T01:38:29Z
dc.date.available2024-11-12T01:38:29Z
dc.date.issued2024-09-13
dc.description.abstractWith advanced digital technologies as the key support, many scholars and researchers have proposed various random warranty models by integrating mission cycles into the warranty stage. However, these existing warranty models are designed only from the manufacturer’s subjective perspective, ignoring certain consumer requirements. For instance, they overlook a wide range of warranty coverage, the pursuit of reliability improvement rather than mere minimal repair, and the need to limit the delay in repair. To address these consumer requirements, this paper proposes a novel random collaborative preventive maintenance warranty with repair-time threshold (RCPMW-RTT). This model incorporates terms that are jointly designed by manufacturers and consumers to meet specific consumer needs, thereby overcoming the limitations of existing warranty models. The introduction of a repair-time threshold aims to limit the time delay in repairing failures and to compensate for any losses incurred by consumers. Using probability theory, the RCPMW-RTT is evaluated in terms of cost and time, and relevant variants are derived by analyzing key parameters. As an exemplary representation of the RCPMW-RTT, two random replacement policies named the discrete random renewable back replacement (DRRBR) and the discrete random renewable front replacement (DRRFR) are proposed and modelled to ensure reliability after the expiration of the RCPMW-RTT. In both policies, product replacement is triggered either by the occurrence of the first extreme mission cycle or by reaching the limit on the number of non-extreme mission cycles, whichever comes first. Probability theory is used to present cost rates for both policies in order to determine optimal values for decision variables. Finally, numerical analysis is performed on the RCPMW-RTT to reveal hidden variation tendencies and mechanisms; numerical analysis is also performed on the DRRBR and the DRRFR. The numerical results show that the proposed random replacement policies are feasible and unique; the replacement time within the post-warranty coverage increases as the maintenance quality improves and the cost rate can be reduced by setting a smaller repair-time threshold.
dc.description.confidentialfalse
dc.edition.editionSeptember-2 2024
dc.identifier.citationChen H, Chen J, Lai Y, Yu X, Shang L, Peng R, Liu B. (2024). Discrete Random Renewable Replacements after the Expiration of Collaborative Preventive Maintenance Warranty. Mathematics. 12. 18.
dc.identifier.doi10.3390/math12182845
dc.identifier.eissn2227-7390
dc.identifier.elements-typejournal-article
dc.identifier.number2845
dc.identifier.urihttps://mro.massey.ac.nz/handle/10179/71978
dc.languageEnglish
dc.publisherMDPI (Basel, Switzerland)
dc.publisher.urihttps://www.mdpi.com/2227-7390/12/18/2845
dc.relation.isPartOfMathematics
dc.rights(c) 2024 The Author/s
dc.rightsCC BY 4.0
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectmission cycle
dc.subjectwarranty
dc.subjectrepair-time threshold
dc.subjectback replacement
dc.subjectfront replacement
dc.titleDiscrete Random Renewable Replacements after the Expiration of Collaborative Preventive Maintenance Warranty
dc.typeJournal article
pubs.elements-id491944
pubs.organisational-groupCollege of Health
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