Analyze the factors influencing human-robot interaction using MCDM method

Bhalaji, R. K. A.; Ponnambalam, S. G.; Saravanasankar, S.

doi:10.1016/j.matpr.2020.06.316

Cited by 7 publications

(3 citation statements)

References 12 publications

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“…All weight allocation methodologies assign the same ranks to each robot, suggesting very little sensitivity of the method to criteria weights. While SAW is a simple technique that demands very little computational effort for decision making, TOPSIS is a slightly more elaborate method wherein the first step is to normalize the decision matrix using Equation (18). The normalized decision matrix is multiplied with the criteria weights to formulate a weighted normalized decision matrix.…”

Section: Optimal Robot Selectionmentioning

confidence: 99%

“…In the literature, different MCDM methods have been used by researchers to solve such robot selection problems. Bhalaji et al [18] used DEMATEL (decision-making trial and evaluation laboratory) to analyze the risk factors influencing the human-robot interaction and found that automation level and reliability of the robot are the major factors that need to be carefully checked to reduce the risk factor for efficient assembly. Parameshwaran et al [19] worked on an integrated fuzzy MCDM-based approach for robot selection considering objective and subjective criteria.…”

Section: Introductionmentioning

confidence: 99%

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Decision Models for Selection of Industrial Robots—A Comprehensive Comparison of Multi-Criteria Decision Making

Shanmugasundar¹,

Kalita

Čep

et al. 2023

Processes

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Due to increased demands of production capacity and higher quality requirements, industries are automating at a fast pace. Industrial robots are an important component of the industrial automation ecosystem. However, the selection of appropriate robots is a challenging task due to the sheer number of alternatives present and their varied specifications. The various characteristics or attributes of industrial robots that need due consideration before selection of an optimal robot for a given application are found to be conflicting in nature. Thus, in this paper, several multi-criteria decision-making (MCDM) methods are deployed to select an optimal robot depending on the application. Three different industrial robot selection problems are solved in this paper by using Simple Additive Weighing (SAW), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), the Linear Programming Technique (LINMAP), VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Elimination and Choice Translating Priority III (ELECTRE-III), and the Net Flow Method (NFM).

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Section: Optimal Robot Selectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Decision Models for Selection of Industrial Robots—A Comprehensive Comparison of Multi-Criteria Decision Making

Shanmugasundar¹,

Kalita

Čep

et al. 2023

Processes

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show abstract

“…High accuracy and repeat in various conditions with precision Due to the ability to repeat tasks, Robots in a wide range of fields are widely used. [3]. Industrial robots are more accurate than humans at repetitive, difficult, and risky tasks, which results in higher-quality products and more efficient production.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Industrial Robots Selection in Manufacturing Industries Using the EDAS Method

2021

rmc

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Robots commonly utilized in manufacturing applications in industries are referred to as industrial robots. Robots are used to execute repetitive, difficult, and dangerous tasks with greater precision, accuracy, and speed. The main reason why businesses use industrial robots is to increase manufacturing productivity and reduce operational expenses. The choice of an appropriate robot necessitates careful consideration of their needs. An inappropriate robot could eventually hurt a company's ability to compete in the market. A commercial robot has several different characteristics, including mechanical weight, payload capacity, repeatability, etc. It is an MCDM challenge because of these parameters. The EDAS approach, a relatively new and mathematically powerful tool of MCDM (Multi-Criteria Decision Making), has been employed in this research.Here Industrial Robot1 (IR1) is ranked fifth, Industrial Robot2 (IR2) is ranked second, Industrial Robot3 (IR3) is first ranked, Industrial Robot4 (IR4) is fourthranked, Industrial Robot5 (IR5) is ranked seventh, Industrial Robot6 (IR6) is sixthranked and Industrial Robot7 (IR7) is ranked third. The result of this paper shows the best robot for industrial purposes is industrial robot 3 and industrial robot 2 and followed by industrial robot.

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A Framework for Timely Delivery of Serviced Vehicles in Automotive Service Garages Using a Rough—DEMATEL Technique

Thomas¹,

Uthayakumar²,

Sankaranarayanan³

et al. 2022

Materials, Design and Manufacturing for Sustainable Environment

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Analyze the factors influencing human-robot interaction using MCDM method

Cited by 7 publications

References 12 publications

Decision Models for Selection of Industrial Robots—A Comprehensive Comparison of Multi-Criteria Decision Making

Decision Models for Selection of Industrial Robots—A Comprehensive Comparison of Multi-Criteria Decision Making

Assessment of Industrial Robots Selection in Manufacturing Industries Using the EDAS Method

A Framework for Timely Delivery of Serviced Vehicles in Automotive Service Garages Using a Rough—DEMATEL Technique

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