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Multi-Layer Quality Inspection System Framework for Industry 4.0
Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation. Malardalen Univ, Div Prod Realizat, Sch Innovat Design & Technol, 15 Hamngatan, S-63220 Eskilstuna, Sweden..
Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation. Malardalen Univ, Div Prod Realizat, Sch Innovat Design & Technol, 15 Hamngatan, S-63220 Eskilstuna, Sweden..ORCID iD: 0000-0002-6062-2173
Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation. Malardalen Univ, Div Prod Realizat, Sch Innovat Design & Technol, 15 Hamngatan, S-63220 Eskilstuna, Sweden..ORCID iD: 0000-0001-5545-5457
2021 (English)In: International Journal of Automation Technology, ISSN 1881-7629, E-ISSN 1883-8022, Vol. 15, no 5, p. 641-650Article in journal (Refereed) Published
Abstract [en]

In the era of market globalisation, the quality of products has become a key factor for success in the manufacturing industry. The growing demand for customised products requires a corresponding adjustment of processes, leading to frequent and necessary changes in production control. Quality inspection has been historically used by the manufacturing industry to detect defects before customer delivery of the end product. However, traditional quality methods, such as quality inspection, suffer from large limitations in highly customised small batch production. Frameworks for quality inspection have been proposed in the current literature. Nevertheless, full exploitation of the Industry 4.0 context for quality inspection purpose remains an open field. Vice-versa, for quality inspection to be suitable for Industry 4.0, it needs to become fast, accurate, reliable, flexible, and holistic. This paper addresses these challenges by developing a multi-layer quality inspection framework built on previous research on quality inspection in the realm of Industry 4.0. In the proposed framework, the quality inspection system consists of (a) the work piece to be inspected, (b) the measurement instrument, (c) the actuator that manipulates the measurement instrument and possibly the work-piece, (d) an intelligent control system, and (e) a cloud-connected database to the previous resources; that interact with each other in five different layers, i.e., resources, actions, and data in both the cyber and physical world. The framework is built on the assumption that data (used and collected) need to be validated, holistic and on-line, i.e., when needed, for the system to effectively decide upon conformity to surpass the presented challenges. Future research will focus on implementing and validating the proposed framework in an industrial case study.

Place, publisher, year, edition, pages
FUJI TECHNOLOGY PRESS LTD , 2021. Vol. 15, no 5, p. 641-650
Keywords [en]
quality inspection, Industry 4.0, cyber-physical systems, zero-defect manufacturing, CAD/CAM/CAE
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:mdh:diva-55962DOI: 10.20965/ijat.2021.p0641ISI: 000693411200009Scopus ID: 2-s2.0-85115102684OAI: oai:DiVA.org:mdh-55962DiVA, id: diva2:1596736
Available from: 2021-09-23 Created: 2021-09-23 Last updated: 2023-10-23Bibliographically approved
In thesis
1. Robotic in-line quality inspection for changeable zero defect manufacturing
Open this publication in new window or tab >>Robotic in-line quality inspection for changeable zero defect manufacturing
2021 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The growing customer demands for product variety have put unprecedented pressure on the manufacturing companies. To maintain their competitiveness, manufacturing companies need to frequently and efficiently adapt their processes while providing high-quality products. Different advanced manufacturing technologies, such as industrial robotics, have seen a drastic usage increase. Nevertheless, traditional quality methods, such as quality inspection, suffer from significant limitations in highly customised small batch production. For quality inspection to remain fundamental for zero-defect manufacturing and Industry 4.0, an increase in flexibility, speed, availability and decision upon conformance reliability is needed. If robots could perform in-line quality inspection, defective components might be prevented from continuing to the next production stage. Recent developments in robot cognition and sensor systems have enabled the robot to carry out perception tasks they were previously unable to do. The purpose of this thesis is to explore the usage of robotic in-line quality inspection during changeable zero-defect manufacturing. To fulfil this aim, this thesis adopts a mixed-methods research approach to qualitative and quantitative studies, as well as theoretical and empirical ones. The foundation for this thesis is an extensive literature review and two case studies that have been performed in close collaboration with manufacturing companies to investigate how in-line quality inspection is perceived and utilised to enhance industrial robots. The empirical studies also aimed at identifying and describing what opportunities arise from having robotic in-line quality inspection systems. The result of this thesis is a synthesis of literature and empirical findings. From the literature review/study, the need for enhancing quality inspection was identified and a multi-layer quality inspection framework suitable for the digital transformation was proposed. The framework is built on the assumption that data (used and collected) needs to be validated, holistic, and online, i.e. when needed, for the system to effectively decide upon conformity to surpass the challenges of reliability, flexibility and autonomy. Empirical studies show that industrial robotic applications can be improved in precision and flexibility using the in-line quality inspection system as measurement-assisted. Nevertheless, this methodological changes and robot application face the hurdle of previous and current management decisions when passing from one industrial paradigm to another (e.g. mass production to flexible production). A discussion on equipment design and manufacturing process harmony and how in-line quality inspection and management can harmonise such a system was provided.

Place, publisher, year, edition, pages
Eskilstuna: Mälardalen University, 2021
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 312
Keywords
industrial robot, in-line quality inspection, industry 4.0, changeable manufacturing, zero-defect manufacturing
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Innovation and Design
Identifiers
urn:nbn:se:mdh:diva-56193 (URN)978-91-7485-530-2 (ISBN)
Presentation
2021-11-12, A1-068, Mälardalens högskola, Eskilstuna, 13:15 (English)
Opponent
Supervisors
Funder
Knowledge Foundation, 16484
Available from: 2021-10-14 Created: 2021-10-13 Last updated: 2023-11-01Bibliographically approved
2. Robotic in-line quality inspection system for Zero-Defect Manufacturing: Requirements and Challenges
Open this publication in new window or tab >>Robotic in-line quality inspection system for Zero-Defect Manufacturing: Requirements and Challenges
2023 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The modern manufacturing paradigm is characterised by an increased level of competition, growing demand for customisable or one-of-a-kind products, and stricter sustainability requirements. To maintain their competitiveness, manufacturing companies must adapt their processes frequently and efficiently while providing high-quality products. Given the importance of establishing flexible and reconfigurable systems, different advanced manufacturing technologies, such as industrial robotics, have seen a drastic increase in usage. However, no system is perfect or free from uncertainties (defects). To achieve Zero-Defect Manufacturing (ZDM, i.e., no defective products leave the manufacturing system, four strategies ‘detect’, ‘predict’, ‘prevent’, and ‘repair’ are needed. However, traditional quality methods, such as quality inspection (detect), suffer from significant limitations in highly customised small batch production.

The objective of this thesis is to facilitate the design of robotic in-line quality inspection systems for ZDM. To achieve the objective, this thesis follows a mixed methods research approach, and its foundation is based on two extensive systematic literature reviews and four case studies in close collaboration with manufacturing companies to investigate how robotic in-line quality inspection is perceived and used. This thesis contributes to the research area of quality management.

Through its findings, this research revealed the unexplicit and partial usage of the ZDM principles in research studies. Thus, this thesis characterises robotic in-line quality inspection, identifies its challenges, and pinpoints its enablers. Robotic in-line quality inspection systems are characterised as ‘connected’, ‘fast’, ‘accurate’, ‘reliable’, ‘holistic’, ‘flexible’, and ‘intelligent’. Several challenges to performing robotic in-line quality inspection have been encountered during this research. As part of the control system, as well as the manufacturing system, performance is highly dependent on its integration with ‘people’, ‘processes’, and ‘technologies’. For example, people need certain competences, time, communication, and participation in the development of ZDM; processes such as ZDM standards are lacking; and available technologies need to be balanced between equipment footprint, interoperability, measurement speed and accuracy, and reliability. Finally, to align all physical, digital, or cognitive components and characteristics, two frameworks and a design flowchart are proposed to help practitioners establish ZDM.

Place, publisher, year, edition, pages
Eskilstuna, Sweden: Mälardalens universitet, 2023
Series
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 395
Keywords
automation, industrial robot, sensor, in-line quality inspection, Zero-Defect Manufacturing (ZDM)
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Innovation and Design
Identifiers
urn:nbn:se:mdh:diva-64570 (URN)978-91-7485-618-7 (ISBN)
Public defence
2023-12-05, C3-003, Mälardalens universitet, Eskilstuna, 09:15 (English)
Opponent
Supervisors
Projects
ARRAY
Available from: 2023-10-24 Created: 2023-10-23 Last updated: 2024-12-17Bibliographically approved

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Azamfirei, VictorGranlund, AnnaLagrosen, Yvonne

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