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Importance of maintenance data quality in extended warranty simulation

Tutkimustuotosvertaisarvioitu

Standard

Importance of maintenance data quality in extended warranty simulation. / Mahlamäki, Katrine; Niemi, Arto; Jokinen, Juuso; Borgman, Jukka.

julkaisussa: International Journal of COMADEM, Vuosikerta 19, Nro 1, 01.01.2016, s. 3-10.

Tutkimustuotosvertaisarvioitu

Harvard

Mahlamäki, K, Niemi, A, Jokinen, J & Borgman, J 2016, 'Importance of maintenance data quality in extended warranty simulation', International Journal of COMADEM, Vuosikerta. 19, Nro 1, Sivut 3-10.

APA

Mahlamäki, K., Niemi, A., Jokinen, J., & Borgman, J. (2016). Importance of maintenance data quality in extended warranty simulation. International Journal of COMADEM, 19(1), 3-10.

Vancouver

Mahlamäki K, Niemi A, Jokinen J, Borgman J. Importance of maintenance data quality in extended warranty simulation. International Journal of COMADEM. 2016 tammi 1;19(1):3-10.

Author

Mahlamäki, Katrine ; Niemi, Arto ; Jokinen, Juuso ; Borgman, Jukka. / Importance of maintenance data quality in extended warranty simulation. Julkaisussa: International Journal of COMADEM. 2016 ; Vuosikerta 19, Nro 1. Sivut 3-10.

Bibtex - Lataa

@article{ff8bab01bbfe4443a3b32636cddfe6b4,
title = "Importance of maintenance data quality in extended warranty simulation",
abstract = "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.",
keywords = "Asset management, Data quality, Hitman factors",
author = "Katrine Mahlam{\"a}ki and Arto Niemi and Juuso Jokinen and Jukka Borgman",
note = "INT=mei,”Jokinen, Juuso”",
year = "2016",
month = "1",
day = "1",
language = "English",
volume = "19",
pages = "3--10",
journal = "International Journal of COMADEM",
issn = "1363-7681",
publisher = "COMADEM International",
number = "1",

}

RIS (suitable for import to EndNote) - Lataa

TY - JOUR

T1 - Importance of maintenance data quality in extended warranty simulation

AU - Mahlamäki, Katrine

AU - Niemi, Arto

AU - Jokinen, Juuso

AU - Borgman, Jukka

N1 - INT=mei,”Jokinen, Juuso”

PY - 2016/1/1

Y1 - 2016/1/1

N2 - 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.

AB - 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.

KW - Asset management

KW - Data quality

KW - Hitman factors

UR - http://www.scopus.com/inward/record.url?scp=84960940492&partnerID=8YFLogxK

M3 - Article

VL - 19

SP - 3

EP - 10

JO - International Journal of COMADEM

JF - International Journal of COMADEM

SN - 1363-7681

IS - 1

ER -