Research On Task Allocation Of Human-Robot Collaborative Assembly Based On Complexity

In the past few years,as a new generation of industrial robots,collaborative robots have been introduced to share work with workers.Unlike the industrial robots in the past,which perform single repetitive work and are isolated from human,collaborative robots and workers often share work tasks and space.The introduction of these collaborative robots makes Human-Robot Collaboration(HRC)more and more important.HumanRobot Collaboration is a new technology in the field of production system.It is performed by human and collaborative robots.It combines the advantages of manual production and automatic production,which can improve production efficiency and quality and reduce costs.These collaborative robots face many challenges in the industrial environment,especially in the assembly environment.One of the most important is the reasonable allocation of assembly tasks between workers and robots.Especially with the continuous shortening of product life cycle and the increasing popularity of multi variety and small batch production,task allocation has become a very important and frequent activity.According to the characteristics of robots and workers,we propose a task allocation method based on complexity.Both workers and robots have significant advantages.The advantage of workers is that they have strong cognitive ability,have high efficiency when dealing with complex tasks,and can quickly adapt to new process sequences.The advantages of robot are high strength,endurance,speed and accuracy.Assembly complexity consists of objective(physical)complexity and subjective(cognitive)complexity.We assign tasks with high cognitive load to workers,while tasks with simple repetition and low cognitive load to collaborative robots.At the same time,the assembly complexity is balanced for the assembly tasks assigned to workers,so that workers and collaborative robots can be fully utilized to reduce costs and improve production efficiency.This paper firstly proposes a measurement model of assembly complexity,which analyzes the assembly task from three aspects of process depth,operation process and cognitive process,and measures the complexity of each assembly task.Secondly,it puts forward the Human-Robot Collaborative Attribute(HRC Attribute),which measures each task and determines whether the task can be completed by the collaborative robot.Thirdly,this paper explains the calculation of the cost of the human-robot collaborative assembly system and determine the number of workers and collaborative robots in the assembly system with the goal of minimizing the cost.Fourthly,Time Use equilibrium Rate(TUR),Human load Balancing Rate(HBR),and Average Cognitive Complexity(ACC)are considered as constraints,the assembly tasks are allocated reasonably with the objective of minimizing the BD of the assembly system.Ensure the work time balance of each labor resource,the assembly complexity balance of each worker’s task,and the cognitive load of the task assigned to the collaborative robot is lower than the cognitive load of the worker’s task,so as to maximize the production efficiency.Fifthly,the genetic algorithm is used to solve the mathematical model of the task assignment,and the cooperation mode and coding mode are explained.Finally,we apply this method to the reducer assembly line of Y-axle company,and carry out an example verification.In this paper,the task allocation of human-robot collaborative assembly,which is currently in the forefront of research,is explained.The proposed structural method of task allocation takes into account the advantages of workers and robots,can significantly reduce the deployment and transformation time of human-robot collaborative assembly system,reduce the cost of assembly system,and lay the foundation for the realization of Intelligent Manufacturing in the future smart factory.