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Towards Zero-Defect Manufacturing: a review on measurement-assisted processes and their technologies
Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
University of Oslo, SIRIUS, Centre for Scalable Data Access, Gaustadalleen 23B, Oslo, 0373, Norway. Research Center on Production Engineering and Management (CIGIP), Universitat Politècnica de València, Spain.
Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.ORCID iD: 0000-0002-6062-2173
Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.ORCID iD: 0000-0001-5545-5457
2024 (English)In: Procedia Computer Science, Elsevier B.V. , 2024, Vol. 232, p. 1001-1010Conference paper, Published paper (Refereed)
Abstract [en]

No system is perfect or free of errors. For companies to reach zero defects in a highly volatile and uncertain environment, emerging technologies, as well as human involvement, are needed. The tenant is to measurement-assist the manufacturing system to predict and prevent deviations in dynamic conditions. This article reviews the Measurement-assisted manufacturing (MAM) literature with the aim to (i) reveal key technologies and processes for MAM, (ii) identify current practices and their weaknesses, and (iii) propose future directions. Results show that despite MAM and Zero-Defect Manufacturing (ZDM) being treated separately, they are deeply interrelated and combining both strategies can lead to true sustainability. The literature indicated that future work must be placed in 'hardware' as instrument operation and equipment maintenance, and 'software', as data analytics and geometry assurance strategies.

Place, publisher, year, edition, pages
Elsevier B.V. , 2024. Vol. 232, p. 1001-1010
Keywords [en]
in-line, measurement-assisted, Quality Control, Zero Defect Manufacturing (ZDM)
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-66467DOI: 10.1016/j.procs.2024.01.099ISI: 001196800601003Scopus ID: 2-s2.0-85189789590OAI: oai:DiVA.org:mdh-66467DiVA, id: diva2:1852302
Conference
5th International Conference on Industry 4.0 and Smart Manufacturing (ISM), Lisbon, November 22-24, 2023
Available from: 2024-04-17 Created: 2024-04-17 Last updated: 2024-12-19Bibliographically approved

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Azamfirei, VictorGranlund, AnnaLagrosen, Yvonne

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