Open Access

Sebastian Schötz, Christian Pfitzner

• Automated guided vehicles systems (AGVS) are of increasing importance regarding material transportation in manufacturing since companies can benefit from the application of these systems. However, AGVS cause high energy consumption for material transportation. This consumption can vary within material transportation paths due to movements such as turns, which may lead to deceleration and acceleration of the vehicle. Hence, planning energy-efficient paths for AGVS-conducted material transportation processes is of great importance, but it leads to a high planning effort within the companies. This paper describes the development of a novel method that facilitates manufacturing companies to plan energy-efficient paths for AGVS-conducted material transportation processes with low effort. First, relevant requirements for the method are defined. Then, an existing pathfinding algorithm is selected based on the predefined requirements. Afterwards, a general framework for determining optimal paths of AGVS in manufacturing facilities regardingAutomated guided vehicles systems (AGVS) are of increasing importance regarding material transportation in manufacturing since companies can benefit from the application of these systems. However, AGVS cause high energy consumption for material transportation. This consumption can vary within material transportation paths due to movements such as turns, which may lead to deceleration and acceleration of the vehicle. Hence, planning energy-efficient paths for AGVS-conducted material transportation processes is of great importance, but it leads to a high planning effort within the companies. This paper describes the development of a novel method that facilitates manufacturing companies to plan energy-efficient paths for AGVS-conducted material transportation processes with low effort. First, relevant requirements for the method are defined. Then, an existing pathfinding algorithm is selected based on the predefined requirements. Afterwards, a general framework for determining optimal paths of AGVS in manufacturing facilities regarding energy consumption is developed prior to the description of a holistic procedure for planning energy-efficient paths in manufacturing. Finally, the method is validated for a sample manufacturing environment.…