Importance of maintenance data quality in extended warranty simulation

Katrine Mahlamäki, Arto Niemi, Juuso Jokinen, Jukka Borgman

    Research output: Contribution to journalArticleScientificpeer-review

    7 Citations (Scopus)


    As manufacturing industries are transforming towards service orientation, predicting the costs of product-service systems is becoming essential. Simulation is one possibility for evaluating the costs and risks involved in product-service systems, such as extended warranty agreements. We conducted a case study with a globally operating manufacturer of industrial goods who also provides services for the equipment. We created equipment performance simulation (EPSi) models and a tool, EPSitor, for using the models in predicting extended warranty costs. However, reliable simulation results require good quality maintenance and operation data from existing installations. We discovered that it is difficult to collect the data needed for simulations and there were many challenges with data quality. Quality problems were mainly observed in manually collected data. Insufficient data quality leads to a wider margin of error in the simulation models, which increases business risk. Identifying these challenges is the first step in transforming the data collection routines to support equipment performance simulations. The key to long-term business benefits of simulation is to acknowledge the importance of data quality and to establish efficient data collection routines. Future research should find ways to motivate maintenance technicians to collect good quality data. This would contribute to more accurate cost analysis and thus to better profitability of extended warranty contracts.

    Original languageEnglish
    Pages (from-to)3-10
    Number of pages8
    JournalInternational Journal of COMADEM
    Issue number1
    Publication statusPublished - 1 Jan 2016
    Publication typeA1 Journal article-refereed


    • Asset management
    • Data quality
    • Hitman factors

    Publication forum classification

    • Publication forum level 1

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering
    • Industrial and Manufacturing Engineering
    • Safety, Risk, Reliability and Quality
    • Bioengineering
    • Signal Processing
    • Strategy and Management


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