Abstract
The amount of different data available for maintenance decision makers is extensive. However, in practice most companies are not exploiting the data in the best possible way but are wasting their resources in sub-optimal data management processes. This paper reviews the current literature on exploiting data in maintenance decision making and analyses how the principles of lean management could contribute to the issue of wasted resources. The objective of the paper is to create a literature-based framework, which will be used as the starting point for empirical research and value modelling in the later stages of the study. The presented framework highlights the role of data in maintenance management decision-making situations, and suggests how the principles of lean management could be adopted in the process of managing maintenance data to improve its value and resource efficiency. The results of this paper will contribute to future research which will include modelling and optimizing the use of data in maintenance decision making.
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References
Andersson, R., Manfredsson, P., Lantz, B.: Total productive maintenance in support processes: an enabler for operation excellence. Total Qual. Manag. 26(10), 1042–1055 (2015)
Baglee, D., Marttonen, S., Galar, D.: The need for big data collection and analyses to support the development of an advanced maintenance strategy. In: The Proceedings of the 11th International Conference on Data Mining, Las Vegas, 27–30 July, pp. 3–9 (2015)
Bahga, A., Madisetti, V.K.: Analyzing massive machine maintenance data in a computing cloud. IEEE Trans. Parallel Distrib. Syst. 23(10), 1831–1843 (2012)
BS EN 13306 Std.: Maintenance. Maintenance terminology, BSI Stand- ards Ltd., ISBN 978-0-580-64184-8 (2010)
BS EN ISO 9001 Std.: Quality management systems. Requirements, BSI Standards Ltd., ISBN 978-0-580-91816-2 (2015)
BS EN ISO 14224 Std.: Petroleum, petrochemical and natural gas industries – Collection and exchange of reliability and maintenance data for equipment, BSI Standards Ltd., ISBN 978-0-580-50138-8 (2006)
BS ISO 55000 Std.: Asset management. Overview, principles and terminology, BSI Standards Ltd., ISBN 978-0-580-86467-4 (2014)
BS ISO 55002 Std.: Asset management. Management systems – Guidelines for the application of ISO 55001, BSI Standards Ltd., ISBN 978-0-580-86468-1 (2014)
Bucherer, E., Uckelmann, D.: Business models for the internet of things. In: Uckelmann, D., Harrison, M., Michahelles, F. (eds.) Architecting the Internet of Things, 352 p., e-ISBN 978-3-642-19157-2. Springer (2011)
Bumblauskas, D., Gemmill, D., Igou, A., Anzengruber, J.: Smart maintenance decision support systems (SMDSS) based on corporate big data analytics. Expert Syst. Appl. 90(C), 303–317 (2017)
Candell, O., Karim, R., Söderholm, P.: eMaintenance – Information logistics for maintenance support. Robot. Comput.–Integr. Manuf. 25(6), 937–944 (2009)
Crespo Márquez, A.: The maintenance management framework. In: Models and Methods for Complex Systems Maintenance, Springer series in reliability engineering, ISBN 978-1-84628-820-3 (2007)
Gupta, S., Sharma, M., Sunder, V.M.: Lean services: a systematic re- view. Int. J. Prod. Perform. Manag. 65(8), 1025–1056 (2016)
Huang, J., Bian, Y., Cai, W.: Weapon equipment lean maintenance strategy research. In: The International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE), Chengdu, China, pp. 1217–1221, ISBN 978-1-4673-0788-8 (2012)
Jylhä, T., Junnila, S.: Learning from lean management – going beyond input-output thinking. Facilities 31(11/12), 454–467 (2013)
Keltanen, M.: Why ‘lean data’ beats big data (2013). https://www.theguardian.com/media-network/media-network-blog/2013/apr/16/big-data-lean-strategy-business. Accessed 10 Nov 2017
Kinnunen, S.K., Marttonen-Arola, S., Ylä-Kujala, A., Kärri, T., Ahonen, T., Valkokari, P., Baglee, D.: Decision making situations define data requirements in fleet asset management. In the proceedings of the 10th World Congress in Engineering Asset Management (WCEAM 2015). Lecture Notes in Mechanical Engineering 2195-4356, pp. 357–364, ISBN 978-3-319-27062-3. Springer (2016)
Kortelainen, H., Kunttu, S., Valkokari, P., Ahonen, T., Kinnunen, S.-K., Ali-Marttila, M., Herala, A., Marttonen-Arola, S., Kärri, T.: D2BK data to business knowledge model – Data sources and decision making needs. FIMECC S4Fleet P3 SP1 Fleet information network and decision making, 29 p. (2015)
Lacerda, A.P., Xambre, A.R., Alvelos, H.M.: Applying value stream mapping to eliminate waste: a case study of an original equipment manufacturer for the automotive industry. Int. J. Prod. Res. 54(6), 1708–1720 (2016)
Moayed, F.A., Shell, R.L.: Comparison and evaluation of maintenance operations in lean versus non-lean production systems. J. Qual. Maint. Eng. 15(3), 285–296 (2009)
Mostafa, S., Lee, S.-H., Dumrak, J., Chileshe, N., Soltan, H.: Lean thinking for a maintenance process. Prod. Manuf. Res. 3(1), 236–272 (2015)
Murthy, D.N.P., Karim, M.R., Ahmadi, A.: Data management in maintenance outsourcing. Reliab. Eng. Syst. Saf. 142, 100–110 (2015)
Obeysekare, E., Marucci, A., Mehta, K.: Developing a lean data management system for an emerging social enterprise. In: IEEE Global Humanitarian Technology Conference, Seattle, WA, USA, 13–16 October, pp. 54–61, ISBN 978-1-5090-2432-2 (2016)
Pakdil, F., Leonard, K.M.: Criteria for a lean organization: development of a lean assessment tool. Int. J. Prod. Res. 52(15), 4587–4607 (2014)
Rolfsen, M., Langeland, C.: Successful maintenance practice through team autonomy. Empl. Relat. 34(3), 306–321 (2012)
Sharma, A., Yadava, G.S., Deshmukh, S.G.: A literature review and future perspectives on maintenance optimization. J. Qual. Maint. Eng. 17(1), 5–25 (2011)
Takata, S., Inoue, Y., Kohda, T., Hiraoka, H., Asama, H.: Maintenance data management system. Ann. CIRP 48(1), 389–392 (1999)
Wang, L., Qian, Y., Li, Y., Liu, Y.: Research on CBM information system architecture based on multi-dimensional operation and maintenance data. In: IEEE International Conference on Prognostics and Health Management, 19–21 June, Allen, TX, USA, ISBN 978-1-5090-0382-2 (2017)
Ylä-Kujala, A., Marttonen, S., Kärri, T., Sinkkonen, T.: Inter organisational asset management: linking an operational and a strategic view. Int. J. Process Manag. Benchmark. 6(3), 366–385 (2016)
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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska Curie grant agreement No 751622.
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Marttonen-Arola, S., Baglee, D., Kinnunen, SK., Holgado, M. (2020). Introducing Lean into Maintenance Data Management: A Decision Making Approach. In: Liyanage, J., Amadi-Echendu, J., Mathew, J. (eds) Engineering Assets and Public Infrastructures in the Age of Digitalization. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-48021-9_28
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DOI: https://doi.org/10.1007/978-3-030-48021-9_28
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