Assessment of shop floor environment dynamics in production plants by developing an innovative methodology for an appropriate implementation of mobile transport robots

Abstract

Abstract In the era of Industry 4.0 and increasingly innovative production plants, automotive manufacturers and suppliers face various challenges, such as a shortage of skilled labor, cost pressure, and volatile markets. While production processes are highly automated, material transport – which is necessary but does not directly add value to the products – is often performed manually. Consequently, the automation of material flow is becoming more and more relevant to further increase the efficiency of production plants. A critical solution to address these challenges is the implementation of mobile robots. Options range from low-autonomy Automated Guided Vehicles to Autonomous Mobile Robots. Both industry and academic literature suggest that Autonomous Mobile Robots are better suited for dynamic environments. Therefore, determining the degree of shop floor environment dynamics in production areas is crucial for selecting mobile robots with the optimal level of autonomy. Although tools such as simulations and digital twins address dynamic shop floor conditions, they are often complex, or not easily transferable. This research contributes a practical and adaptable methodology to support early-stage planning for mobile robot deployment. This paper follows the Design Science Research approach to introduce a methodology that quantifies shop floor environment dynamics based on real data. It was successfully applied to a plant of an automotive supplier. The case study demonstrates how high-dynamic areas can be identified through heatmap visualizations. The methodology supports decision-makers by providing insights into shop floor environments, enabling an evaluation of which mobile robot concepts may be better suited to different production environments. It is adaptable to other industries.