Digital Human and Robot Simulation in Automotive Assembly using Siemens Process Simulate: A Feasibility Study

摘要

The global trend toward customization in the automotive sector has led to significant increase in the variability of components available to the assembly process. The increase in product variability directly impacts the complexity of the manufacturing process and consequently increases the possibility for human-generated error. Several solutions have been offered to reduce the potential risk of error in complex assembly processes which can be generalized as cognitive-based or physical-based assistive methods. Creating a digital twin of the process, both the human and machine elements, is a preliminary requirement before deploying such solutions in a real-world manufacturing environment. The digital twin simulation provides a platform for testing a variety of solutions and what-if scenarios to improve planning and decision making. While there exist commercially available products of human digital twin modeling, these do not provide a proper platform for human – machine interaction modeling. In the context of this work,machineis defined as an industrial robot with an objective of investigating the feasibility of deploying a smart collaborative robotic solution to provide physical assistance to the human worker in a cumbersome manufacturing process. To do so, an overhead assembly operation from a real-world vehicle assembly plant is identified, and a digital twin of human model is created in Siemens Tecnomatix suite. The study starts with the simulation of various human anthropomorphic models to discover the limitations in performing the assembly tasks based on gender, weight and height. Furthermore, a digital twin of a mobile robot designed to provide physical assistance to the human to perform the assembly operation is introduced. The results are evaluated in terms of process time, joint ergonomic impact and reveal some current limitations of combined digital twin modeling of humans and robots collaborating.