With advanced technologies such as IoT, cloud computing, analytics and AI manufacturers are entering the Fourth Industrial Revolution, also known as Industry 4.0. While the amount of data available to businesses has exponentially grown, it has been mostly limited to software businesses such as ecommerce. Physical manufacturers remain to struggle with missing data or misused data (data of poor quality). One technology known to solve both problems is the real-time locating system (RTLS). RTLS technologies identify and track the location of objects and people in real time within buildings where GPS falls short. A research study conducted by students at Chalmers University of Technology (Croona & Niklasson, 2020) identified 3 use cases that RTLS technologies are best suited to solve. Focusing on these use cases can not only increase the chances of a successful deployment for the manufacturer, but in aggregate drive the adoption of RTLS technologies and their stake within the Industry 4.0 ecosystem.
1. Increasing safety and productivity
With products increasing in sophistication, the complexity of manufacturing processes and equipment is increasing in tandem. Managing safety and productivity is becoming harder as a result. RTLS systems can draw up relationships between locations, people and equipment to identify risks and opportunities. For example, Croona & Niklasson (2020) mention that by accurately tracking people and vehicles in manufacturing plants, “near miss” thresholds can be defined. The thresholds are based on the minimum distance required between vehicles and employees to ensure safety. Subsequently, safety officers can review occurrences of “near misses” and optimize the plant layout to minimize injuries and insurance-related claims. In addition to safety, the same data can be used to increase the flow of materials and thereby, productivity. More specifically, the maximum speed at which vehicles travel inside a manufacturing plant can be automatically increased or decreased depending on their location or the presence of employees. For example, the maximum vehicle speed can be automatically increased when there are no employees present within a particular zone in the plant, allowing for higher flow of equipment or material.
2. Supplying data for KPI measurements
KPIs play an important role in the performance of a business since only aspects that are measured can be improved. For software businesses KPIs are easily measured since they solve byte problems and therefore are mostly related to interactions with websites or apps. In contrast, manufacturers solve atom problems and therefore need hardware to measure their KPIs which overall increases time and complexity of getting accurate data. While plant managers often rely on their experience, RTLS technologies can supplement the manager’s know-how with hard data for some KPIs. Figure 2 shows the KPIs that can be calculated based on indoor positioning data.
3. Manufacturing process analysis
Analysis of historical data is key for process optimization. RTLS technologies can help to generate data that when visualized can lead to actionable insights. For example, temporal heatmaps for vehicles and human resources can show bottle necks inside the manufacturing plant. Furthermore, Digital Twins can and will play an important part in the future of process analysis in manufacturing. Being able to visualize and replay all past interactions between locations, objects and will give process managers unprecedented tools to analyze and improve manufacturing processes.
Manufacturing and Industry 4.0 is rapidly evolving. One of the nascent technologies that can help manufacturers accelerate their effectiveness and efficiency are real-time locating systems (RTLS). Currently the key manufacturing use cases for RTLS technologies are threefold: (1) safety and productivity, (2) KPI measurements and (3) process analysis. Going after these use cases can create a flywheel effect for the RTLS deployment in manufacturing plants. The high impact and probability of success for these use cases will result in higher satisfaction amongst pilot customers and will then fuel the adoption of other existing and new use cases by manufacturers.