A proxy interpreter to upgrade automated legacy systems

Abstract

The present disclosure generally relates to upgrading existing automated legacy machines (20). More specifically, the present disclosure relates to system and method for a proxy interpreter system to collect and consolidate the setup, configuration, operation and quality inspection data from a plurality of interfacing devices and controllers of legacy machines (20) and subsequently build a Reinforcement learning module using the consolidated data to perform all the functions automatically without the intervention of a human operator. The consolidated data in the proxy interpreter module may be further analysed using Deep learning methods for data analytics and artificial intelligence to reliably and consistently classify the defect criteria of products to further enhance the quality of the inspection. The defect criteria classification enables the Proxy Interpreter system to highlight potential problems and aid in preventive maintenance of the legacy automated systems. The Proxy interpreter system enables legacy machines (20) to adapt and scale to manufacture newer products with no human intervention whether it is related to operation of the legacy equipment or in the process of quality control. Figure 2