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At the present time, industrial robots for assembly tasks only constitute a small portion of the annual robot sales. One of the main reasons is that it is difficult for conventional industrial robots to adapt to the complicity and flexibility of assembly processes. Therefore, intelligent industrial robotic systems are attracting more and more attention. However, because of the modeling difficulty...
An improved harmony search algorithm is presented for solving continuous optimization problems in this paper. In the proposed algorithm, an elimination principle is developed for choosing from the harmony memory, so that the harmonies with better fitness will have more opportunities to be selected in generating new harmonies. Two key control parameters, pitch adjustment rate (PAR) and bandwidth distance...
High precision assembly processes using industrial robots require the process parameters to be tuned in order to achieve desired performance such as cycle time and First Time Through (FTT) rate. Some researchers proposed methods such as Design-of-Experiment (DOE) to obtain optimal parameters. However, these methods only discuss how to find the optimal parameters if the part and/or workpiece location...
This paper presents a study on the Design Of Experiments (DOE)-based parameter optimization technique to adapt to the manufacturing environment changes in robotic force control assembly. Based on a real-world transmission torque converter assembly production process, investigation and analysis are performed in production. An on-pendant robotic assembly parameter optimization tool is introduced. When...
Differential evolution is a novel method to search global optimum. A new pruning algorithm for solving the fuzzy neural network design problem is proposed based on differential evolution with division of work. Based on the proposed algorithm, an optimal and efficient fuzzy neural network structure can be constructed by the requirements. Numerical simulations show the effectiveness of the proposed...
In this paper, aim at the characteristics of multi-objective multi-constrained and difficult to solve of the three-dimensional container-packing problem, we propose to solve the problem with improved differential evolution (IDE) algorithm. By overloading the evolutionary operation of differential evolution algorithm that we can deal with discrete optimization problems effectively. Define the adaptive...
The topic of tuition fees has recently sparked heated discussions in various media. Based on China's national conditions, this article collected elevant data, such as national student average funding, training costs, household disposable income and did the quantitative analysis for tuition standards of several types of schools, then built a Multi-level fuzzy evaluation model, which regarded the tuition...
This paper presents the objective metric study on design of experiments (DOE)-based robotic force control parameter optimization in transmission torque converter assembly. Based on a real-world assembly production process, investigation and analysis are performed on the optimization metrics of assembly cycle time mean (MEAN), its mean plus three times of standard deviation (MEAN+3*STDEV), and first...
Differential evolution is a powerful evolutionary inspired search technique for global optimization. We have proposed a new algorithm based on differential Evolution to solve the fuzzy neural network design problem, it can identify an optimal and efficient fuzzy neural network structure for a given problem. Numerical simulations show the effectiveness of the proposed algorithm.
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