Contemporary manufacturing must prioritise the #sustainability of its manufacturing processes and systems. Zero Defect Manufacturing (#ZDM) focusses on minimising #waste of any kind using data-driven technology, hence enhancing the quality of all manufacturing aspects (product, process, service, etc.). Making things right on the first try is the central tenet of #ZDM. In recent years, the application of automation for in-line quality #inspection systems has begun to attract the interest of both practitioners and academics because of its capability to #detect defects in real-time, and thus adapt the system to disturbances. In this work, we provide a systematic review of the literature on current trends in the application of automation for in-line quality inspection with the ultimate objective of achieving ZDM. Additionally, bibliometric and performance analyses have been performed to gain a complete picture of the field. In this work, we have collected bibliometric data from the most widely referred search engines for academic engineering papers, i.e. Scopus, Web of Science, and IEEE Explorer, involving a total of 145 academic publications from 2011 to 2021. Uniquely for this study, we used three research attributes for the analysis of the selected articles, that is, the level of automation, the condition for quality inspection, and the contribution to ZDM dimensions. The literature suggests that there is a lack of research on the use of in-line detection data for the prediction of defects or repair. Based on the results and our interpretation of the literature, an adapted framework of ZDM and multi-layer quality inspection is presented.
Operators role in inspection, in Industry 5.0
Moving toward #ZDM requires knowledge capturing from the #operator’s feedback. The ability to identify non-conformances using digital tools in addition to the expertise and #knowledge that #human resources have to offer is essential for accomplishing ZDM. Operators must adjust to new robot-equipped workstations. Due to their outstanding repeatability and indefatigability, robots are gradually taking over the repetitive labour, but operators are necessary for a task requiring a high level of dexterity. In addition to being cost-effective, #human–#robot collaboration may also be a technical means of minimising mistakes in the industrial sector. Future research should focus on closing the gap on human-centric #ZDM. For instance, interdisciplinary research in hardware, software, interaction design, cognitive psychology, and system engineering is needed to integrate humans and technology in production contexts efficiently and in a sustainable manner. Future studies in the direction of human-centric #ZDM should focus on both the #working #environment and employee #wellbeing.
Towards 100% inspection
Performing 100% #inspection is the only way to assuring that the desired quality levels have been achieved and the product delivered to the customers is the correct one. Another aspect of 100% is that no defective items will ever leave the factory, minimising the harmful effects of production on the environment without increasing the workload associated with production. Additionally, in 100% in-situ inspection is used to increase the resilience of Cyber-Physical System (CPS) against cyber attacks. Besides the positive effects of 100% inspection, there are a few also negative. The employment of this level of inspection has a number of drawbacks, including a significant cost rise caused by the need for extra employees or measuring equipment, as well as time consuming. Additionally, implementing 100% inspection is unreliable when destructive inspection techniques are required, such as when mandated by law. To enable #early #defect identification and prevent its spread through the growth of in-process inspection, also known as in-line inspection or quality control, 100% production inspection is becoming essential for #smart factories. Implementing 100% inspection might have a negative impact on the performance of the manufacturing system, but compared to the losses brought on by a defective product at the customer’s end, these losses would be far smaller. Fenech and Perkins indicated that 36% of customers want to buy a personalised product, with 50% saying they would accept a longer length of time for doing so, to counteract this little performance loss.
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