ABSTRACT
Currently, the Aviation industry uses traditional methods of communication, coordination, & human interaction to give disposition to resolve any kind of nonconformance occurrences which occur during manufacturing or operation of commercial or defense products. This involves increased in-person interaction and additional travel, especially to address the nonconformance issues arising at supplier plants or airports around the globe. During Covid and post-Covid environments, human interactions for the transfer of detailed information at different & distant manufacturing plant locations has been difficult, since support engineering teams (Example: Liaison, Product Review, Quality, Supplier Quality, and Manufacturing Engineering, and/or Service Engineering) have been working remotely. Thus, it has been challenging to coordinate with support engineers to get correct dispositions in short timeframes with no additional cost of quality, thereby creating non-value-added time which delayed the release & execution of the respective rework orders. Mixed Reality (MR) based remote assistance can enable delivery of large amount of complex information, knowledge in a cost-effective way. It helps to simulate and visualize various nonconformance scenarios faced in manufacturing unit which can be viewed and worked on without geographic boundaries. Thus, the members of the Engineering, Operations, and Quality team can unite under one platform to gain a better understanding of the nonconformance issue and deliver more informed decision. This quick decision making not only reduces manufacturing lead time and cost of quality for respective plants but also optimizes product delivery and shipment time of the overall supply chain and reduction of Aircraft on Ground (AOG) time for aircraft in service. In this work, we will demonstrate benefits and applications of MR based remote assistance with various cases which will help in taking accurate, realistic dispositions & enable resolutions on any nonconformance resulting in optimized cost of quality in minimum timeframe © 2022 Boeing.