Blockchain has been applied to quality control in manufacturing, but the problems of false defect detections and lack of data transparency remain. This paper proposes a framework, Blockchain Quality Controller (BCQC), to overcome these limitations while fortifying data security. BCQC utilizes blockchain and Internet-of-Things to form a peer-to-peer supervision network. This paper also proposes a consensus algorithm, Quality Defect Tolerance (QDT), to adopt blockchain for during-production quality control. Simulation results show that BCQC enhances data security and improves defect detections. Although the time taken for the quality control process increases with the number of nodes in blockchain, the application of QDT allows multiple inspections on a workpiece to be consolidated at a faster pace, effectively speeding up the entire quality control process. The BCQC and QDT can improve the quality of parts produced for mass personalization manufacturing.
With the mindset of constant improvement in efficiency and safety in the workspace and training in Singapore, there is a need to explore varying technologies and their capabilities to fulfil this need. The ability of Virtual Reality (VR) and Augmented Reality (AR) to create an immersive experience of tying the virtual and physical environments coupled with information filtering capabilities brings a possibility of introducing this technology into the training process and workspace. This paper surveys current research trends, findings and limitation of VR and AR in its effect on human performance, specifically in Singapore, and our experience in the National University of Singapore (NUS).
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