جستجوی مقالات مرتبط با کلیدواژه « robotic cell » در نشریات گروه « صنایع »
تکرار جستجوی کلیدواژه «robotic cell» در نشریات گروه «فنی و مهندسی»-
In this study, we model a stochastic scheduling problem for a robotic cell with two unreliable machines susceptible to breakdowns and subject to the probability of machine failure and machine repair. A single gripper robot facilitates the loading/unloading of parts and cell-internal movement. Since it is more complicated than the other cycles, the focus has been on the S_2 cycle as the most frequently employed robot movement cycle. Therefore, a multi-objective mathematical formulation is proposed to minimize cycle time and operational costs. The -constraint method is used to solve small-sized problems. Non-dominated sorting genetic algorithm II (NSGA-II), is used to solve large-sized instances based on a set of randomly generated test problems. The results of several Test problems were compared with those of the GAMS software to evaluate the algorithm's performance. The computational results indicate that the proposed algorithm performs well. Compared to GAMS software, the average results for maximum spread (D) and non-dominated solutions (NDS) are 0.02 and 0.04, respectively.Keywords: Breakdowns, Identical parts, NSGA-II, Probable failures, Robotic cell, scheduling}
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Flexible robotic cells are used in many real-life industries to produce standardized items at a high production speed. Determining the schedules of these cells is an important optimization problem in those industries. In this study, the cell's machines are identical and parallel. In the cell, there is an input and an output buffer wherein items being processed and the finished items are kept, respectively. There is a robot performing the loading/unloading operations of the machines and transporting the items. The system repeats a cycle in its run. Each machine processes one part in each cycle. The cycle time depends on the order of the loading/unloading activities. Therefore, determining the order of these activities for the minimum cycle time is needed. We propose a new mathematical model to solve the problem. For large size problems, three metaheuristic algorithms based on local search algorithm are proposed. In the metaheuristics, in order to compute the minimum cycle time of a given solution a linear programming model is needed to be solved which is one of the recent cases in the literature to the best of our knowledge. Several numerical examples are solved by the proposed algorithms and their performance and solutions are compared.Keywords: scheduling, Flexible manufacturing system, Robotic cell, Metaheuristic}
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در این تحقیق، مساله زمانبندی سلول رباتیک با سه ماشین CNC و با فرض یک عملیات بر روی هر ماشین با هدف بهینه کردن هزینه کل تولید و زمان، در چرخه بررسی شده است. برای به دست آوردن بهینه هزینه کل تولید از زمان بهینه پردازش عملیات بر روی ماشین ها استفاده شده است. این مساله در سه حالت بررسی گردیده است. در حالت اول زمان بهینه پردازش عملیات بر روی هر یک از ماشین ها در کران پایین آنها می باشد. در حالت دوم زمان بهینه پردازش عملیات بر روی هر یک از ماشین ها در کران بالای آنها می باشد. در حالت سوم زمان بهینه پردازش عملیات بر روی هر یک از ماشین ها بین کران بالا و کران پایین آنها می باشد. قدم بعدی در این تحقیق ارائه رویکرد حل، برای حالت هایی است که در بالا ذکر شد. . برای حل این مساله از روش لاگرانژ استفاده شده است. مهمترین حاصل این تحقیق، مدل سازی و حل مساله زمانبندی برای سلول رباتیک سه ماشینه در سه حالت مختلف و یافتن جوابهای بهینه هزینه کل تولید و زمان می باشد. لازم به ذکر است که در ادبیات موضوع، مساله زمانبندی سلول رباتیک جهت بهینه کردن هزینه تولید و مقدار زمان تنها برای حالت دو ماشینه مدل سازی و حل شده است.کلید واژگان: زمانبندی, سلول رباتیک, بهینه سازی هزینه تولید, ماشین CNC}International Journal of Industrial Engineering & Production Management, Volume:23 Issue: 3, 2012, PP 293 -302In this research, robotic cell scheduling problem with three CNC machines and with an operation on each machine with the purpose of optimizing manufacturing cost and time in S1 cycle has been investigated. To obtain the optimal total cost of production has been used the optimal processing time on machine operation. In this research, robotic cell scheduling is studied in three different situations. In the first situation the optimal processing time of operation in each machine, are on the lower bound. In the second situation the optimal processing time of operation in each machine, are on the upper bound. In The third situation the Optimal processing time of operation in each machine, are between upper bound and lower bound.The next step in this research is proposing solving approaches for the problems mentioned above.the Lagrange method is used, To solve this problem. The most important result of this research is modeling and solving scheduling problem for three-machine robotic cell in three different situations and finding optimized answers for the cost and time. It should be mentioned that in the literature, robotic cell scheduling problem for optimization of manufacturing cost and time is only solved and modeled for two-machine situation.Keywords: scheduling, robotic cell, optimization of manufacturing cost, CNC machine}
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In this paper, the researchers have investigated a Concatenated Robot Move (CRM) sequence problem and Minimal Part Set (MPS) schedule problem with different setup times for two-machine robotic cell. They have focused on simultaneous solving of CRM sequence and MPS schedule problems with different loading and unloading times. They have applied a Simulated Annealing (SA) algorithm to provide a good solution rapidly. A domination rule has been developed and used in SA algorithm that strongly reduces the search space and increases speed and solution''s quality of the algorithm. Numerical experiments indicate the results of the proposed SA from two points of view: quality of solution and consumed time.
Keywords: CRM sequence, MPS schedule, Robotic cell, Simulated annealing}
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