Optimization of the Energy Consumption for Robotic Kitting in the Automotive Industry

This paper presents a comprehensive Integer Programming (IP) model designed to optimize the robotic kitting process in industrial automotive settings. Robotic kitting, involving the efficient assembly and preparation of kits using automated systems, plays a crucial role in modern manufacturing facilities. The proposed IP model considers various key aspects related to the cycle time, including preparation time for kit boxes on Automated Guided Vehicles (AGVs), picking time with Autonomous Mobile Robots (AMRs), image acquisition and processing time, AMR and AGV travel times, and removal time of empty component bins by AMRs. The objective is to minimize the energy consumption of AGVs in the kitting process, enhancing operational efficiency while ensuring accurate kit assembly. The formulation of the mathematical programming model allows for the consideration of flow-related activities, improving the adaptability and flexibility of the kitting process to varying order patterns. Numerical experiments demonstrate the effectiveness of the model in achieving key insights into AGVs’ energy demand, contributing to advancements in mapping this process in industrial automation and logistics.