Optimised Shop-Floor Operator Support on an Integrated AR and PLM Framework for Remanufacturing

Abstract

Product disassembly and inspection are essential operations in a sustainable product life cycle, particularly in end-of-life strategies such as remanufacturing. This study identifies critical aspects of usability of a framework that supports the remanufacturing process and its operators. Two of the challenges faced by operators in remanufacturing are the number of product variants and quality decisions. As a result of these, the performance time and the number of errors committed increase. The integration of Augmented Reality (AR), product lifecycle management and expert systems increase the efficiency of managing stored data and supports the remanufacturing process and its operators. A head-mounted display has been used to run the application, allowing the operator to take it right to the working area. The information displayed during the manufacturing processes includes CAD models or images of the industrial equipment and its components and dynamic information, providing clear instructions easy to follow during the remanufacturing process. The proposed methodologic approach uses the concept of rule-based Expert Systems to determine the information content that is dynamically displayed on the AR device and to optimise the route that should be followed in remanufacturing operations. A pilot testing was done to assess the functional suitability of the final AR application to support the delivery of dynamic information in its final industrial environment. The evaluation was done in a real-working environment selecting the assembly, disassembly and inspection operations as a base. A questionnaire to measure the usability of the system was provided to the test subjects after the testing. The results from the questionnaire show a positive perception of the usability of the framework. According to the result analysis, the framework has high usability and can reduce errors and impaired decision-making.