Abstract
Increased environmental awareness in industry combined with the globalized market economy has created an increase in demand for sustainable and efficient resource utilization. In this context, maintenance plays a critical role by linking business objectives to the strategic and operational activities aimed at retaining system availability performance, cost-efficiency, and sustainability. Performing maintenance effectively and efficiently requires corresponding infrastructure for decision-support provided through eMaintenance solutions. A proper eMaintenance solution needs to provide services for data acquisition, data processing, data aggregation, data analysis, data visualization, context-sensing, etc. For Quality of Service (QoS) in eMaintenance solutions, the performance of both system-of-interest, enabling systems, and related processes have to be measured and managed. However, the QoS has to be considered on all aggregation levels and must encompass the aspects of Content Quality (CQ), Data Quality (DQ), and Information Quality (IQ). Hence, the purpose of this paper is to study and describe some aspects of DQ in eMaintenance related to the process industry in northern Europe.
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References
Muller A, Suhner MC, Iung B (2007) Maintenance alternative integration to prognosis process engineering. J Qual Maint Eng 13(2):198–211
Tsang AHC (2002) Strategic dimensions of maintenance management. J Qual Maint Eng 8(1):7–39
Karim R (2008) A service-oriented approach to eMaintenance of complex technical systems. PhD Thesis. Luleå, Luleå University of Technology, Sweden
Parida A, Kumar U (2006) Maintenance performance measurement (MPM): issues and challenges. J Qual Maint Eng 12(3):239–251
International Electrotechnical Commission (2004) Dependability management—part 3–14: Application guide—maintenance and maintenance support. International Electrotechnical Commission, Geneva, Switzerland, 24 Mar 2004. Report No.: 60300-3-14
Kajko-Mattsson M, Karim R, Mirijamdotter A (2010) Fundamentals of the eMaintenance concept. In: Proceedings of the 1st international workship and congress on eMaintenance, Luleå University of Technology, Luleå, Sweden, 22–24 Jun 2010, pp 147–154
Muller A, Crespo Marquez A, Iung B (2008) On the concept of eMaintenance: review and current research. Reliability Eng Syst Saf 93(8):1165–1187
Koc M, Lee J (2001) A system framework for next generation EMaintenance Systems. In: Proceedings of the 2nd international Symposium on environmentally conscious design and inverse manufacturing, Tokyo, Japan, 11–15 Dec 2001
Parida A, Kumar U (2004) Managing information is key to maintenance effectiveness. In: Proceedings of the intelligent maintenance systems (IMS) international conference. Arles, France, 15–17 July 2004
International Electrotechnical Commission (2008) System engineering—system life cycle processes, International Electrotechnical Commission, Geneva, Switzerland. Report No.: 15288
Lee J, Ni J, Djurdjanovic D, Qiu H, Liao H (2006) Intelligent prognostics tools and eMaintenance. J Comp Ind 57(6):476–489
Parida A, Phanse K, Kumar U (2004) An integrated approach to design and development of e-maintenance system. In: Proceedings of VETOMAC-3 and ACSIM-2004, Allied Publishers Ltd, India, 6–9 Dec 2004, pp 1141–1147
Juran JM, Blanton GA (1999) Juran’s quality handbook. McGraw-Hill, New York
Karim R, Kajko-Mattsson M, Söderholm P (2008) Exploiting SOA within eMaintenance. In: Proceedings of the 30th international conference on software engineering (ICSE), the 2nd international workshop on systems development in SOA environment, Liepzig, Germany, 10 May 2008
International Organization for standardization (2009) Data quality—part 100: master data: Exchange of characteristic data: Overview. Report No.: 8000-100:2009
Price R, Shanks G (2005) A semiotic information quality framework: development and comparative analysis. J Inf Technol 20(2):88–102
Wand Y, Wang RY (1996) Anchoring data quality dimensions in ontological foundations. Commun ACM 39(11):86–95
Harding JA, Shahbaz M, Srinivas S, Kusiak A (2006) Data mining in manufacturing: a review. J Mfg Sci Eng 128(4):969–976
Bogus SM, Migliaccio GC, Cordova AA (2010) Assessment of data quality for evaluations of manual pavement distress. Geol Prop Earth Mater 2010:1–8
Ergen E, Akinci B, East B, Kirby J (2007) Tracking components and maintenance history within a facility utilizing radio frequency identification technology. J Comput Civ Eng 21(1):11–20
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Al-Jumaili, M.I., Rauhala, V., Jonsson, K., Karim, R., Parida, A. (2014). Aspects of Data Quality in eMaintenance: A Case Study of Process Industry in Northern Europe. In: Lee, J., Ni, J., Sarangapani, J., Mathew, J. (eds) Engineering Asset Management 2011. Lecture Notes in Mechanical Engineering. Springer, London. https://doi.org/10.1007/978-1-4471-4993-4_5
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DOI: https://doi.org/10.1007/978-1-4471-4993-4_5
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