Evaluating motor choices for a smart wheelchair prototype using an integrated TODIM-CoCoSo approach with MEREC weighting
Abstract
This study aims to advance the decision-making process for assessing the optimal motor for a smart wheelchair prototype through the application of a hybrid Multi-Criteria Decision-Making (MCDM) method. By integrating the TODIM (Tomada de Decisao Interativa Multicriterio), CoCoSo (Combined Compromise Solution), and MEREC (Method based on the Removal Effects of Criteria) methodologies, the research aims to enhance the precision and reliability of evaluations. These methods are designed to manage complex decision-making, considering 10 critical parameters such as MRP, Weight, Noise level, Power, Torque, Speed, Energy efficient, Size and Integration, control and responsiveness, Durability and Reliability, and 9 potential motors for their suitability in smart wheelchair design. While the TODIM and CoCoSo approaches independently compute the performance rating to generate ranking of selected motors, the MEREC weighting methodology assesses the influence of criteria as sourced from online B2B market data and expert recommendations. The M-9 version is the greatest choice for developing smart wheelchairs. The purpose of the sensitivity evaluation was to collect pertinent data for the purpose of streamlining the decision-making process related to motor purchases. It also provides practical insights into motor selection for smart wheelchair prototypes, with potential applications in healthcare and assistive technology design.
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