Real-Time Locating System for Changeover Analysis (SMED)

Abstract

The emergence of novel technologies necessitates innovation to sustain competitive ness. The smart factory concept, which is at the core of the Industrial Internet of Things (IIoT), is a derivative of industry 4.0. Real-time tracking is a crucial compo nent of intelligent manufacturing in this context. The implementation of real-time tracking systems for diverse objects within production and warehouse settings is a crucial control mechanism that facilitates informed decision-making for organisa tions. In instances where deviations and unforeseen alterations arise, timely and ap propriately formatted information can be provided. This thesis project investigates the application of tracking equipment to enhance changeover analysis (SMED) using method study based AviX software in partnership with the consulting firm Virtual Manufacturing Sweden AB (VM). The study yielded a case report demonstrating that the Marvelmind, a technology utilising ultrasonic sound waves and fitted onto the operator, was capable of tracking the operator’s walking trajectory during the changeover process. The Gazpacho tracking analysis software was subjected to test ing of its tracking data visualisation functions, which included spaghetti diagrams and heat maps. This master’s thesis addresses the constraints, areas of growth, and prospects pertaining to Real-Time Locating Systems (RTLS) in the context of manufacturing.