Research Of Task Allocation Strategies Considering Task Matching And Ergonomics In The Human-robot Collaborative Hybrid Assembly Cell

With the development of the social economy,customers’ demand for small-lot personalized products is increasing.Facing the rapidly changing market environment,companies need to adopt a new production model to cope with the new consumption pattern of small-volume customization.Recently,the human-robot collaborative hybrid assembly cell(HRCHAC)production model has attracted much attention for its flexibility,economy,and flexibility,and it is widely used in small-volume customized production.Since workers and robots have different characteristics,to take full advantage of the human-robot collaborative hybrid assembly cell production model to improve productivity,the respective strengths of workers and robots must be fully utilized in task allocation.Thus,a tremendous challenge for enterprise decision-makers is how to utilize the respective strengths of workers and robots in task allocation to improve the productivity of assembly systems.In this regard,this paper explores how to fully utilize the respective advantages of workers and robots in task allocation and provides an in-depth study on how to assign tasks to the worker and robot in three dimensions: assembly efficiency,matching the skills of resources(worker or robot)with task characteristics,and ergonomics.The purpose of this study is to propose a task allocation method that can take full advantage of the skills of workers and robots while taking into account the efficiency of assembly and ergonomics,in order to improve the productivity of the assembly system by taking full advantage of the respective strengths of workers and robots.The research work is divided into the following three parts:(1)A task-matching metric that can quantify the degree of matching between resource skills and task characteristics is proposed by analyzing the characteristics of operational tasks.In addition,this paper investigates how sustainable robot workability can be used to improve the ergonomic risk of workers in the assembly process.Specific task allocation strategies are developed regarding ergonomics’ physiological and psychological fatigue dimensions to avoid worker fatigue proactively.(2)For the proposed task allocation strategy,this paper develops a bi-objective mixed integer programming model to minimize the unit product assembly time,maximize the total task matching,and establish ergonomics-related constraints.In addition,a VNS-NSGA-II algorithm with a mixture of the Variable Neighbourhood Search(VNS)algorithm and the Non-dominated Sorting Genetic Algorithm-II(NSGAII)is designed for solving the proposed task allocation model.(3)The effectiveness of the task allocation method and algorithm proposed in this paper was verified by testing one gearbox assembly case and eight randomly generated cases.In addition,a comparison of the task allocation scheme obtained using the proposed method with that obtained using the conventional method shows that the task allocation method proposed in this paper can significantly improve the physiological and psychological health of workers with minimal impact on assembly efficiency while improving the match between resource skills and task characteristics.Finally,the corresponding management insights are given through relevant case studies.