Open AccessA Study on Weighted Aggregated Sum Product Assessment (WASPAS) w.r.t Multiple Criteria Decision Making
Author(s) -
C. Venkateswaran,
D R Pallavi,
M Ramachandran,
Sathiyaraj Chinnasamy,
Chinnasami Sivaji
Publication year - 2022
Publication title -
1
Language(s) - English
DOI - 10.46632/daai/2/1/5
Subject(s) - computer science , ranking (information retrieval) , multiple criteria decision analysis , machining , automation , reliability engineering , mathematical optimization , control theory (sociology) , mathematics , control (management) , mechanical engineering , engineering , artificial intelligence
Advantages of the WASPAS method Weight Total Model (WSM) and Weight Product Model (WPM) Uses. Combining WSM and WPM improves the ranking accuracy of WASPAS alternatives. That At the moment, WASPAS calculates an optimal registration parameter, which will be given in detail later. The Weight the Product Assessment (WASPAS) system is a unique combination of Weight Gross Model (WSM) and Weight Product Model (WPM). Its mathematical simplicity and ability to deliver more accurate results compared to WSM and WPM methods Due to this, it is now widely accepted as an effective decision maker. In this paper, (a) a flexible production system, (b) a machine in a flexible production cell, (c) an automated guide vehicle and (d) an automation study. Structure and (c) an industrial robot. For all these five problems, the WASPAS method provides the most acceptable results. The optimal 1 value is determined for each issue considered and the effects of different values on the ranking of candidate alternatives in theWASPAS system are also analyzed. In this study, the compatibility of the Weighted the Product Evaluation (WASPAS) method is being explored as an effective MCDM tool, while eight production Decision making issues are resolved. Condition, Mac inability of objects and electro-discharge Micro-machining process parameters. The system has the ability to accurately sequence alternatives across the entire Selection issues are considered. In the ranking performance of the WASPAS system the effect of the parameter is also explored.