As products progress towards the end user in a standard supply chain, numerous firms are starting to acknowledge the significance of reverse logistics. Reverse logistics takes care of the return products to suppliers or vendors. In the return merchandise authorization (RMA) process, one of the main steps that decides the cost of repairing is to ascertain whether the damage is customer induced damage (CID) or vendor induced damage (VID). In this paper, a comprehensive computational procedure using Python and various libraries, including Pillow (PIL), NumPy, and SciPy was implemented in an electronic manufacturing company to automate and optimize the process of making the CID vs. VID decision.
Differentiation and Visualization of Board Image Changes: A Comprehensive Computational Approach using Python
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