Task Allocation Optimization Of A Car Seat Welding Production Line Based On Human Robot Collaboration

Under the background of industry 4.0,the manufacturing mode of human-robot collaboration is playing an important role in the manufacturing industry.Human-machine collaboration has been widely used in the welding production of car seat frame.In the face of man-machine collaboration system,the man-machine task allocation faces severe challenges because of the real-time transformation of man-machine interaction and the dynamic change of man-machine operation state.How to effectively analyze the role of human,human factors and man-machine relationship in human robot collaboration system is the key to realize the rationality of human robot collaboration task allocation.Therefore,considering human factors to optimize the task allocation in the man-machine cooperative working process is an effective way to improve the efficiency of human robot collaboration,and has important practical significance to study the reliability of human robot collaboration and reduce the workload of workers.Based on this,this paper takes the human-machine cooperative welding workstation of car seat skeleton as the research object,considers the human-machine cooperative welding process affected by worker fatigue,and systematically studies the optimization method of human-machine cooperative task allocation.The main research contents are as follows:(1)Aiming at the problem of strong subjectivity in the comprehensive evaluation of fatigue of workers in automobile seat frame welding workstations,a comprehensive evaluation model of fatigue of human-machine collaborative welding workstation based on cloud model is constructed.The fatigue factors of workers in automobile seat frame welding workstation were analyzed,and the fatigue evaluation system of automobile seat frame welding workstation workers was constructed from the aspects of physical and psychological fatigue.Combined with the fuzzy AHP-DEMATE combination weighting to calculate the weight of each factor,the cloud model comprehensive evaluation method is used to reduce the subjective influence of fatigue evaluation and determine the fatigue level of welding workstation workers.(2)Aiming at the problem of dynamic change of human fatigue and fuzzy description of human-machine event relationship during human-machine collaborative welding operation of automobile seat frame,a human-machine collaborative welding operation model based on generalized random Petri network is established.The probability distribution function of worker fatigue state parameters is established,and the dynamic change process of each part of the human-machine collaboration system is described by applying the library change,directed arc and token,so as to realize the mathematical description of man-machine operation time under the dynamic change of worker operation state.(3)Aiming at the problem of unreasonable task allocation in the human-machine collaborative welding process of automobile seat frame,a human-machine collaborative task allocation optimization method based on the improved migratory bird algorithm is proposed.The task allocation optimization model of human-machine collaborative welding production line with the goal of minimizing production cycle is established,and a model solving algorithm based on improved migratory bird algorithm is proposed,which solves the problem that human-machine collaboration tasks are easy to fall into local optimization when redistributing human-machine collaboration tasks,and obtains the optimal human-machine collaboration task allocation scheme for automobile seat frame welding workstations.(4)Frame to test the welding workstation man-machine collaboration task allocation,the feasibility and effectiveness of using PDPS car seat before and after the simulation software to optimize welding workstation to carry on the simulation,and from the production line,the man-machine operation time and line daily output three aspects analyze the human-machine collaborative task allocation effect,to realize the objective and rationality verification of the optimization results of human-machine cooperative task allocation for automobile seat skeleton welding.