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Lean instrumentation framework for sensor pruning and optimization in condition monitoring
Luleå University of Technology, Department of Business Administration, Technology and Social Sciences.ORCID iD: 0000-0003-0147-0680
Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Human Work Science.
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0002-4107-0991
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
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2011 (English)In: The Eighth International Conference on Condition Monitoring and Machinery Failure Prevention Technologies: St. David's Hotel, Cardiff, Wales, 20 - 22 June 2011 ; CM2011/MFPT2011, Longborough, Glos: Coxmoor Publishing Co. , 2011, Vol. 1, 202-215 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper discusses a lean instrumentation framework for guiding the introduction of the lean concept in condition monitoring in order to enhance the organizational capability (i.e. human, technical and management trichotomy) and reduce the complexity in the maintenance management systems of industrial companies. Additionally, decision-making, based on severity diagnosis and prognosis in condition monitoring, is a complex maintenance function which is based on large data-set of sensors measurements. Yet, the entirety of such decision-making is not dependent on only the sensors measurements, but also on other important indices, such as the human factors, organizational aspects and knowledge management. This is because, the ability to identify significant features from large amount of measured data is a major challenge for automated defect diagnosis, a situation that necessitate the need to identify signal transformations and features in new domains. The need for the lean instrumentation framework is justified by the desire to have a modern condition monitoring system with the capability of pruning to the optimal level the number of sensors required for efficient and effective serviceability of the maintenance process. It is concluded that there are methodologies that can be developed to enable more efficient condition monitoring systems, with benefits for many processes along the value chain.

Place, publisher, year, edition, pages
Longborough, Glos: Coxmoor Publishing Co. , 2011. Vol. 1, 202-215 p.
Keyword [en]
Lean thinking, sensor pruning, Business / Economics - Business studies
Keyword [sv]
Ekonomi - Företagsekonomi
National Category
Production Engineering, Human Work Science and Ergonomics Other Civil Engineering Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Industrial Work Environment; Operation and Maintenance; Industrial Electronics
Identifiers
URN: urn:nbn:se:ltu:diva-37684Local ID: bc792dff-71f5-4722-a01f-19905cf292f9ISBN: 978-1-61839-014-1 (print)OAI: oai:DiVA.org:ltu-37684DiVA: diva2:1011182
Conference
International Conference on Condition Monitoring and Machinery Failure Prevention Technologies : 20/06/2011 - 22/06/2011
Note
Godkänd; 2011; Bibliografisk uppgift: CD-ROM; 20110624 (mohami)Available from: 2016-10-03 Created: 2016-10-03 Last updated: 2017-10-19Bibliographically approved

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http://www.bindt.org/Events/CM_Conferences_&_Seminars/CM_2011_and_MFPT_2011/Structured_Session_Organisers.html

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Sanda, Mohammed-AminuAbrahamsson, LenaGalar, DiegoKumar, UdaySandin, FredrikDelsing, Jerker
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Production Engineering, Human Work Science and ErgonomicsOther Civil EngineeringOther Electrical Engineering, Electronic Engineering, Information Engineering

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