A Framework to Design a Scalable and Reliable Indoor Positioning System-IPS for Industrial Applications

Knowing the positions of people or objects has become crucial for developing services in many fields, such as logistics. Manufacturing systems present a challenge for positioning systems because of multiple obstacles and metallic objects that reflect signals and disturb signal detection. Because the most widespread positioning systems, such as global positioning systems (GPS), are not suitable for position detection in indoor environments, indoor positioning systems (IPSs) have emerged. IPSs locate objects, people, or vehicles in closed structures such as office buildings, hospitals, stores, factories, and warehouses. According to the technology adopted, IPSs can differ mainly in terms of accuracy, precision, cost, and type of positioning data (e.g., real-time data). This chapter illustrated and applied a comprehensive framework for designing a scalable and reliable IPS for vehicle and product tracking in an industrial context. This process involved three main steps. The first step used material and information flow mapping to highlight current information gaps that lead to system inefficiencies and bottlenecks. The second step determined the best technology for achieving the expected benefits. Finally, the third step dealt with the design and implementation of IPSs within an industrial context by introducing measurement and monitoring metrics such as key performance indicators. A case study illustrated that the proposed framework can be applied to a gear motor manufacturing system to design and implement a scalable IPS based on ultra-wideband technology for vehicle and product tracking. The potential of this framework lies in its scalable and customizable applicability to different industrial contexts.