To address the problem of how to build quantitative evaluation index models that reflect the essential characteristics of reconfigurable manufacturing system (RMS) and rank alternative reconfiguration schemes, which possess both advantages and disadvantages, an evaluation method based on the preference ranking organization method for enrichment evaluation (PROMETHEE) is proposed. Based on a consideration of the reconfiguration of the reconfigurable machine components and manufacturing cells, quantitative models of the key characteristics of an RMS (scalability, convertibility, diagnosability, modularity, integrability, and customization) are established, after which the quantitative models are used as the basis for constructing an RMS evaluation index system. The analytic hierarchy process (AHP) is used to assign the weights for these indices. During the evaluation process, PROMETHEE I is first applied to analyze the advantages and disadvantages of each alternative scheme. Then, PROMETHEE II is adopted to analyze the net advantages of the schemes. Finally, all of the alternative configurations are ranked according to the analysis results above. The workshop of an institute that has both research and production capabilities was used as an example to validate the effectiveness and practicability of the proposed method. The example contains 10 alternative reconfiguration schemes, and each scheme consists of six evaluation indices. The computation result shows that quantitative models of six key RMS characteristics are equipped with the ability of quantitative description of the RMS reconfiguration scheme, which gives intuitive decision-making information combined with PROMETHEE, including advantage and disadvantage between alternative schemes, for a decision-maker to select the satisfactory configuration. In addition, only a 7.2 % data loss during the evaluation data processing means the rationality of the selected evaluation index and evaluation algorithm.
In order to make manufacturing system to adapt to the rapidly changing global market environment, Reconfigurable Manufacturing Cells (RMCs) based on balanced distribution of machines function were presented. Firstly, Similarity Coefficient Method (SCM) was used to cluster some parts to form part families which are the foundation of RMC. Then, a mathematical optimization model was set based on the workshop layout whose functional characteristics are balanced distribution. Tabu Search (TS) algorithm was designed to solve the selection problem of process routes. In the algorithm, a recycled search method was used to generate an initial feasible solution, and then the method of swapping adjacent elements was used to generate neighborhoods. Finally, software MATLAB was used to realize the algorithm, and a case study of simulation was used to verify the feasibility and effectiveness of the algorithm.
To solve the tool flow and part flow interaction problems in job-shop scheduling, a kind of dynamic scheduling technology in job shop with tool flow is proposed. A new method of decision point calculation and a new heuristic approach for job selection named tools-minimally-occupied (TMO) are proposed. According to the method and the rule, the problems of when and how to select the parts in the dynamic scheduling are solved. The technology is proved to be effective by examples.
Particle-enhanced is the way to improve properties of solder alloys. In the present work, the influence of Ag particle-enhanced on the wettability and creep rupture life of 99.3Sn0.7Cu eutectic solder with Ag content of 1vol% to 10vol% were investigated. It was indicated that the wettability of the composite solders could be improved by adding minute amount of Ag particles. With increasing the amount of Ag particles, the spreading areas of the composite solders increased when Ag was below 5vol%. When Ag was above 5vol%, the spreading areas started decreasing. When Ag content was up to 10vol%, the wettability of the composite solder sharply deteriorated. In addition, the creep rupture lives of the composite solders were longer than that of 99.3Sn0.7Cu eutectic solder at the same condition. When Ag content was 5vol%, the creep rupture life of the composite solder was the longest among the investigated composite solders and about 23 times of that of 99.3Sn0.7Cu eutectic solder.
Traditional scientific research project cost estimating method cannot meet accuracy and practicability at the same time. Aiming at this problem, scientific research project cost estimating method based on neural network was built. Firstly, the construction and influencing factors of scientific research project cost were analyzed. Secondly, an estimating model based on improved BP neural network was built; a nonlinear expression between influencing factors (input) and cost (output) was created. Finally, an estimating system with the model was implemented by Java. The effectiveness of the method was tested. Testing experiment showed the estimating model based on improved BP neural network is reliable and the precision is high.
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