Industrial robots can perform repetitious, difficult and hazardous tasks with precision. They can improve quality and productivity, and reduce delivery time and production cost. There are many industrial robots with different specifications and applications, so selecting a suitable industrial robot for particular application and manufacturing environment from lots of robots available is one of the important and decisive problems in practice.
Industrial robot selection in consideration of multiple conflicting performance attributes is a very difficult multi-attribute decision making (MADM) problem. For industrial robot selection, many MADM methods (MADMs) are applicable.
Many researchers have applied some different MADMs to practical industrial robot selection problems. But they only compared the results from MADMS, and failed to consider which MADM is the most suitable and reasonable to the given robot selection problem. Moreover, few of them determined reasonable final results by combining the results from different MADMs.
Choe Myong Song, a researcher at the Faculty of Mechanical Science and Engineering, proposed a reasonable method for industrial robot selection combined with multiple MADMs based on final comprehensive performance (CP) values using the weighted average of the CP values from individual MADMs. Then, he applied the proposed method to the selection of the best industrial robot for some pick-n-place operations avoiding some obstacles.
The results showed that the proposed method is a reasonable industrial robot selection method for determining the FCP values and FCRs of candidate robots in consideration of the preference weights of each MADM, and that it could be widely used in many practical problems for industrial robot selection and other MADM applications.
For further information, please refer to his paper “A reasonable method for industrial robot selection combined with several multi-attribute decision making methods” in “International Journal on Interactive Design and Manufacturing” (EI).
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