Indoor positioning systems to digitalize manual production processes

Modern manufacturing companies operate at fast pace and their processes presents several in-plant interdependencies. In addition, human operators still play a pivotal role in particular for scenarios in which automation is not feasible or economically viable. Therefore, consistent decision-making processes are needed to reinforce in-plant performances at targeted levels. In this scenario, traditional tools of analysis are no more adequate to monitor such complex and variable environments. Recently, different digital technologies have been developed to acquire insightful and structured datasets of manufacturing processes. Among them, indoor positioning systems have gained interest due to their ability to accurately track any tagged moving asset within a certain coverage area. This paper proposes an original hardware and software architecture to autonomously and quantitatively monitor labor intensive job shops. The hardware consists in an Ultrawide-band based indoor positioning system, where tags are assigned to workers. The software counterpart leverages the acquired spatial and temporal data to enhance the visibility of production processes into different levels. On one hand, an automatically evaluated from to chart defines the rate of dependency among the geofenced areas of the job shop. Times spent within the storage areas are computed to evaluate the impact of replenishment routes for each worker. On the other hand, a Gantt chart displays times spent in each area along with the visiting sequence. By selecting a time interval equal to the cycle time of the job shop is possible to visualize how working times are divided into the different areas. From these valuable outputs, a re-layout of the entire job shop may be suggested and identified to increase the productivity of the process. The consistency and the resilience of this digital architecture is tested in a real manufacturing job shop which performs manual and automatic machining for the automotive industry.