Research & Development Period Prediction And Optimization Of The Mechanical System In Some Teaching Robot

In recent years, the government has adopted a series of policies in terms of the product, business and industry to encourage the development of robots and related industries. In order to meet the development needs of these industries, it is urgent to train the robot related technical personnel, to meet the demand of teaching robot in the teaching practice, the market prospect is broad. As the degree of innovation and responsiveness to customer needs has become the core competitiveness of the manufacturing enterprises, so how to rationally plan product's R & D duration should be prioritized by enterprises. This thesis studied the R & D of a mechanical system of a teaching robot. In order to solve the existing problem of development characteristics and schedule management, the duration prediction and optimization of the R & D are systematically analyzed. This would improve the status of the R &D tasks for duration management and efficiently meet customer needs.The main content of this research as follows:(1) Based on the mechanical system development process of a teaching robot,analyzed the problems in the management of task duration. The R & D tasks are broken down from the perspective of the structure and function. Realized identification of the coupled task by Design Structure Matrix(DSM) and applied separate sorting algorithm to sort the coupled tasks. It is the foundation for the task duration prediction and optimization research of the project.(2) Based on the Discrete Gray prediction Model(1,1),proposed the IDGM of five point cubic smoothing method. This model is applied to the coupling task duration prediction. Verified the validity of the model. Discrete gray prediction model DGM(1,1) and gray prediction model GM(1,1) are comparatively analyzed and tested precision to verify the superiority of this model. Calculated the task duration of the entire R & D project by critical path method and achieved the prediction of task duration.(3) In order to resolve the conflict that duration optimization between the enterprises and key R & D department, based on in-depth analysis of the Game relation between the two representatives, start from the view of revenue incentive,the optimization of task duration model is proposed based on Stackelberg Game.Cuckoo search algorithm is applied to verify the model,and the optimum value ofthe critical path task duration is obtained. Finally, the sensitivity of model parameters is analyzed to verify the validity and accuracy of the model.The result can provide a valid reference on the planning and designing schedule of the R&D project.