Design and modeling to identify a defective workpiece in manufacturing process: an industry 4.0 perspective
Springer Science and Business Media LLC - Trang 1-17 - 2023
Tóm tắt
Traditionally, the sampling process is done manually by verifying a handful of objects from a batch of several objects being produced. Based on the quality of the handful of objects verified, the whole batch may be accepted or rejected. Mistakes during manual sampling process may cause a number of defected objects to be accepted and a number of fine objects to be rejected which in turn may increase risk both at the manufacturer’s and the consumer’s end. Therefore, there is a need to transform manual sampling process into automatic. The purpose of this research work is to use Industry 4.0 concept and develop an image recognition-based system (IRBS) for identifying a defected workpiece to increase the accuracy of the quality inspection process. Based on recently published journals and patents, manual sampling process, Industry 4.0 concept, and Image Processing Technique are reviewed. Then, IRBS for identifying a defected workpiece is designed and developed. Next, trial is taken on developed IRBS model to investigate its performance. It is found that the use of IRBS model reduces manufacturer’s risk. After implementation of the IRBS model the process accuracy is increased from 90.67 to 100%, labour productivity is increased from 5.69 to 18.4 units/min and the average time required for inspection of 05 samples is reduced from 53 to 16 s. IRBS makes sampling process automatic which results in increase in the accuracy of the quality inspection process, reduction in time required for inspection process and increase in the labor productivity.
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