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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.

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.