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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.

In the realm of Industry 4.0, measurement systems play an important role in adapting industrial robots to dynamic environments. Real-time control techniques such as Measurement Assisted Assembly (MAA) can exploit the digital measurements for operation process corrections. Likewise, the propagation of defects can be avoided with in-line measurement conditions. The purpose of this paper is to first understand the capability of robotic in-line measurement assisted assembly in the industrial case of peg-in-hole assembly and second, record the encountered challenges and their enablers. A proof of concept - formed by two 6DoF industrial robots, an in-line Linear Laser (LL), and an on-machine force sensor - have been designed and tested in a lab environment. The experimental results show that robotic in-line measurement assisted assembly can be performed within the tight tolerances of (i) 0, 071 ° to 0, 154° angular deviation between X and Y axes, (ii) applying minimum (near 0) Newton forces in X and Y axes when performing the peg-in-hole robotic assembly of two parts with only 50μm clearance, and (iii) within the company's cycle time. Further, for the effectiveness and practicality of robotic measurement assisted assembly systems, we recorded the encountered challenges and key enablers.