Visekriterijumsko Kompromisno Rangiranje Research Articles

Multi-objective optimization design of automobile seat backrest considering coupling effect

To investigate the impact of the coupling effects of carbon fiber reinforced polymer in the seat back layer on the performance of car seats, this paper presents a comprehensive optimization design method for composite materials. In detail, the finite element models firstly established and validated through five typical working conditions of automotive seats based on experimental data. Then, the optimized variables are divided and determined through backrest stress nephograms for each working conditions of the automotive seats, in which the various perspective are taken into account, such as the total mass of seat backrest, safety performance, and comfort index. Subsequently, an optimization strategy for unequal thickness layers lay-up design is constructed, which combines strength factors, optimal Latin hypercube sampling, best-worst method, gray relational analysis, and Visekriterijumsko KOmpromisno Rangiranje method for the optimal design of the automotive CFRP seat backrest. Additionally, the impact of layer coupling effects on different performance indices of the seat is examined through simulating and analyzing the seat backrest with various layer coupling types, while incorporating the classical laminate theory. The study reveals that by minimizing the laminate coupling effect, the comfort of the seat can be enhanced. Finally, a comprehensive comparative analysis of the optimal trade-off solution is carried out in terms of optimization strategies. The results show that ensuring the safety performance, the total mass of the seat backrest decreased by 21.3%, as a result of the optimization strategy proposed in this paper, and the comfort performance is also improved to some extent. Therefore, the multi-objective optimization strategy proposed in this paper performs well in terms of effectiveness and provides a reliable reference for related composite material multi-objective optimization.

An experimental investigation on copper square electrode wear in electric discharge machining of Hastelloy B2

Hastelloy B2 is a high-performance nickel-molybdenum alloy and has been used in micro reactor, pump, pipe, and corrosion-resistant equipment. Square holes are required in the above application components. Although square holes are easily produced by spending more electrodes wear in Electrical Discharge Machining (EDM). Moreover, the square hole with small electrode wear achieved is a challenging task in thermal machining. Hence, in this work, the effects of EDM process parameters on electrode taper angle, electrode radius, electrode wear length and cutting time of Hastelloy B2 are studied. Taguchi based VišekriterijumskoKompromisnoRangiranje (VIKOR) method is used to find the optimum process parameters and compared with Taguchi based Grey Relational Analysis (GRA) method for validation. The results showed that current and pulse duration greatly affects the electrode wear out surface and edges. The square electrodes with sharp edges and surfaces are fully transformed into hemispherical shapes at electrode ends due to an unstable spark with diffusion of heat. Also, the VIKOR method provides an alternative multi-criteria optimization method that enhances the process performance over the grey relational analysis due to comparability, uniqueness, assessment and prediction.

Player selection in football by integrated SWARA-VIKOR methods under fuzzy environment

This study aims to provide an objective evaluation and selection of the most suitable players for the Turkish National Football Team by using multi-criteria decision-making methods, specifically Stepwise Weight Assessment Ratio Analysis (SWARA) and VIsekriterijumsko KOmpromisno Rangiranje (VIKOR) based on neutrosophic numbers. In the initial step of the study, the important criteria for player selection were determined, and a total of 21 and 26 criteria were identified for goalkeeper and players, respectively. Agility, reflexes and jumping ability are very important for goalkeeper whereas marking, passing ability, agility, dribbling, and footwork are the most important criteria for players. The performances of the players were evaluated due to these criteria and finally the Turkish National Football Team was established scientifically because of the best player selection. This decision-making process will be more beneficial in making more informed and effective decisions in the national team's player selection process. The success of the team can be improved by providing an objective and systematic player selection approach.

Integration of Sustainability in Risk Management and Operational Excellence through the VIKOR Method Considering Comparisons between Multi-Criteria Decision-Making Methods

In the current context, organizations face an important challenge in managing risks related to environmental, social and governance (ESG) issues. This research presents a general method for prioritizing organizational risks with a focus on sustainability based on the characterization of five typologies of organizational risks and their respective sub-risks, based on an analysis of global reports. Subsequently, paired surveys are administered to a group of experts from various sectors, who assign importance to the organizational sub-risks. Their responses serve as the basis for the prioritization of these risks, using the VIšekriterijumsko KOmpromisno Rangiranje (VIKOR) method, which highlights the following most relevant organizational sub-risks for each type of risk: (1) Lack of ethics in the conduct of business (geopolitical risk); (2) Deficit in economic growth (economic risk); (3) Chemical safety (social risk); (4) Massive data fraud or theft incidents (technological risk); and (5) Water depletion (environmental risk). Additionally, a sensitivity analysis is performed to determine the robustness of the results of the VIKOR method and then compare the correlation coefficients with respect to the results obtained in previous studies for the AHP and ANP methods. Finally, we propose the implementation of a model to manage organizational risks, which are addressed proactively through an integral vision, allowing for continuous improvement and alignment with corporate strategy by means of an operational excellence management system (OEMS).

Examining the role of digitalization and technological innovation in promoting sustainable natural resource exploitation

In the era of technological advancement, the potential of digitalization and technical innovation to revolutionize sustainable resource exploitation has become a focal point. The promises of reduced environmental impact, heightened efficiency, and improved socio-economic outcomes underscore the transformative power that digitalization holds for resource management. To this extent, the fuzzy Analytical Hierarchy Process (AHP) and fuzzy VIsekriterijumsko KOmpromisno Rangiranje (VIKOR) methods are used to examine challenges and come up with possible solutions for the mining sector in Pakistan to adopt digital transformation. The study identifies several key challenges, sub-challenges, and strategies, giving readers a thorough grasp of digital transformation. These challenges and sub-challenges are evaluated and ranked according to their relative weights using the fuzzy AHP approach. The fuzzy VIKOR method is applied to determine strategies that can help overcome these challenges and promote digitalization and technological innovation in the sustainable exploitation of natural resources. The results of fuzzy AHP show that policy and regulation, infrastructure, and human capital are key challenges. The findings of fuzzy VIKOR indicate that robust policy development, investment in Research and Development (R&D), and leveraging global trends and partnerships are key strategies to overcome the challenges. These findings provide valuable insights for policymakers, researchers, and practitioners, offering new perspectives on integrating digital technology into the natural resource sector to foster sustainable development.

Supplier selection among manufacturing companies based on their MSME partners’ supply chain finance adoption capability using BWM and VIKOR

PurposeThe purpose of this paper is to identify and prioritise supply chain finance (SCF) adoption enablers and develop a novel comprehensive framework to select supplier firms based on their SCF adoption capability.Design/methodology/approachThe study deploys a three-phase method to identify and prioritise SCF adoption enablers, followed by developing a model to select suppliers according to their SCF adoption capability. An extensive literature review, followed by a Delphi approach-based expert interview, has been used to finalise the enablers. Using the Best Worst Method and the VIsekriterijumsko KOmpromisno Rangiranje technique, a supplier selection model has been developed in the context of a case company.FindingsThe financial health and technological advancement variables received the top priority, followed by collaborative efficiency, whereas the human resources and organisational variables received the slightest significance. A supplier selection framework has also been developed by using the adoption capability of these factors by the supplier partners. In this study’s model, Supplier 4 exhibited better SCF adoption capability and received the top priority.Research limitations/implicationsManufacturing supply chains in a developing country are the scope of the current study. Extensive future studies are required to derive a global consensus.Practical implicationsThe proposed framework of this study can be used to select supplier firms based on their SCF adoption capability. Policymakers can emphasise the most critical enablers of SCF adoption to assist small supplier firms to be a part of the advanced global supply chains.Originality/valueThe current study established a novel comprehensive framework for supplier selection based on the Supply Chain Finance adoption capability of MSME supplier firms.

Future Technology Development Using VIKOR Method

Future Technology Development. Future technologies could consist of tangible objects like robots, drones, and wearable technology. These can occasionally be utilized as human-powered tools to gather data, access information, or carry out helpful tasks nearby. Current and upcoming technologies are the main topics of Introduction to Technology. It covers the study of technology with a focus on management, operations, industries, specialized knowledge, security, interpersonal relationships, and developing technologies. India is now engaged in the development of cutting-edge technologies including 5G, AI, blockchain, augmented reality, virtual reality, robots, natural language processing, etc. Robotics, artificial intelligence, machine learning, and other technological advancements have greatly sped up transition. By 2025, 50 billion connected devices will make up the Industrial Internet of Things (IIoT), and 70 percent of manufacturers will be employing digital twins. Everybody who has access to virtual reality or augmented reality gadgets by the year 2040 will also have access to a digital virtual assistant. Virtual assistants can now be created on language model platforms that are significantly more powerful than previous language models, such as GPT-3. The VIKOR (VIšekriterijumsko Kompromisno Rangiranje) Optimal replacement Select method is used in Water, Carbon dioxide, Nitrogen gas, Oxygen, Silicon oxide, Calcium carbonate, Iron oxide, and Enthalpy (kJ/mol), Entropy (kJ/mol), Exergy (kJ/mol). Water, Carbon dioxide, Nitrogen gas, Oxygen, Silicon oxide, Calcium carbonate, and Iron oxide. Enthalpy (kJ/mol), Entropy (kJ/mol), Exergy (kJ/mol). Water got the first rank whereas Calcium carbonate is having the lowest rank.

A novel integrated approach based on best–worst and VIKOR methods for green supplier selection under multi-granularity extended probabilistic linguistic environment

With consideration for the extensive resources consumption and environmental degradation being on the rise today, implementing green development strategy to pursue both socioeconomic growth and the coordinated of environment sustainability, has become an increasingly important issue in modern enterprise supply chain operations management. Hence, the appropriate green supplier selection (GSS), viewed as a core issue in green supply chain management (GSCM), requires continuous research in this field to obtain a complete perception on GSS practices. It can be regarded as a multi-attribute group decision-making (MAGDM) problem that involves many conflict and unmeasurable evaluation criteria. In view of the superiority of multi-granularity extended probabilistic linguistic term sets (MGEPLTSs) in modeling such issues on potential ambiguity, complexity and uncertainty in actual GSS practices, we propose a novel integrated MAGDM methodology for GSS problems, by integrating the BWM (best–worst method) with the VIKOR (VIšekriterijumsko KOmpromisno Rangiranje) technique under the MGEPLTSs environment. First, by introducing the multi-granularity and probabilistic linguistic term sets, the MGEPLTSs are proposed to represent and quantify the decision information of GSCM practitioners. Then, the BWM is introduced to the MGEPLTSs environment to compute the weights of decision-making panels and evaluation attributes in GSS problems, by building the fuzzy mathematical programming model, respectively. Finally, we extend a multi-granularity extended probabilistic linguistic VIKOR method to calculate the compromise measure of alternatives considering the group utility maximization and the individual regret minimization, thereby achieving the full ranking of alternatives. A GSS case is conducted to illustrate the feasibility of the proposed approach, and the sensitivity analysis and comparative analysis with other similar approaches are presented to demonstrate its effectiveness and advantages.

E-Learning Websites Selection and Ranking Using Multi-Criteria Decision-Making Methodology

The present research places significant importance on the evaluation and prioritization of E-learning platforms based on a predetermined set of selection criteria. The primary aim of this research project is to select and rank E-learning websites. The issue pertaining to the selection and ranking of e-learning platforms is addressed through the utilization of a methodology known as multiple-criteria decision-making (MCDM). The task of choosing E-learning websites is addressed through the application of the multicriteria decision-making (MCDM) technique known as Weighted-Combinative Distance-based Assessment (W-CODAS), which is specifically designed to tackle such issues. In order to assess the suitability and effectiveness of the proposed method, a comparison is made between the results obtained from methodology which is proposed and those obtained from established approaches such as Visekriterijumsko Kompromisno Rangiranje (VIKOR) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The methodology under consideration has not yet been employed to assess, choose, and prioritize the diverse E-learning platforms

Green-based supplier selection using BWM and VIKOR methods in the Indonesian manufacturing sector

The selection of green-based suppliers remains a challenge for manufacturing firms in Indonesia. In today's business landscape, it is crucial to consider green aspects as part of sustainability practices when choosing suppliers. However, there is a limited number of studies providing frameworks for selecting suppliers based on green factors, particularly in developing countries. This study aimed to propose a framework for selecting suppliers using multicriteria decision-making (MCDM) techniques. A case study was conducted in an Indonesian metal manufacturing company that considers carbon reduction and incorporates traditional supplier selection factors such as quality, cost, and capacity. The study integrated two MCDM techniques, namely the best-worst method (BWM) and Višekriterijumsko Kompromisno Rangiranje (VIKOR), to evaluate and select green-based suppliers. BWM was employed to determine the weights of the criteria, while VIKOR ranked the suppliers. Seven criteria were identified, including cost (C1), quality (C2), delivery time (C3), technology application (C4), compliance with environmental regulations (C5), green practice certification (C6), and green efforts (C7). Nine suppliers were screened and ranked accordingly. The results indicate that quality, delivery time, and cost are the top three ranked criteria based on their importance. Further, this study includes nine suppliers in which supplier S7 demonstrates the best performance compared to the others. This study highlights that in Indonesia, most organizations tend to prioritize traditional criteria, while green factors are still overlooked. However, the company examined in this study has taken the initiative to include environmental factors in its decision-making process. The findings of this study contribute to the development of a framework for selecting green suppliers in a developing country context.

SELECTION OF THE BEST COFFEE SHOP USING THE VIKOR METHOD

Coffee businesses in Medan are becoming increasingly competitive. Due to the invention of coffee menus and coffee serving packaging to remain competitive, every coffee shop has a distinct quality. However, choosing the finest coffee shop remains a challenge for the decision-maker in this scenario, the consumer. Therefore, we need a mechanism to pick which clients or visits to a coffee shop. Clear, simple-to-understand idea-winning tactics make it simple to make decisions that are effective. The efficacy of various choices may be assessed by an efficient computer procedure. The purpose of this study is to use the Visekriterijumsko Kompromisno Rangiranje (Vikor) technique to choose the best coffee shop based on the following criteria: ambience, taste, pricing, diversity of the menu, service, and facilities. The responses of the questionnaire are used to determine the weight gain based on weighing. The option with the lowest value is chosen as the best option when A5 = 0. In other words, alternative A5 was chosen as the spot where coffee is most strongly recommended

Decision Support System For Determining The Best Employee Using The Visekriterijumsko Kompromisno Rangiranje Method (Case Study At Distribution Center Guardian)

The quality of human resources is one of the supporting factors to increase the performance productivity of a corporate agency. Highly competent human resources can support the level of performance, with performance appraisal, the achievements of each employee will be obtained. To obtain fast and accurate information on employee performance that meets the expected criteria. To find out this, with a multi-criteria decision-making method by solving complex and unstructured situations into parts and compiling them using the Visekriterijumsko Kompromisno Rangiranje (VIKOR) method on Decision Support Systems (SPK), the determination of the best employee can be calculated based on the calculation of the weight their respective criteria, so that they can quickly select the best employees in the company. From the final results of the VIKOR method, ranking 1 is Sukron, with a value of 0.

Agricultural Waste-Based Heterogeneous Catalyst for the Production of Biodiesel: A Ranking Study via the VIKOR Method

Agricultural waste-based heterogeneous catalysts are emerging as efficient and green catalysts. The present study explored the agricultural waste-based heterogeneous catalyst utilized in the production of biodiesel. The plant waste is composed of organic compounds and various metals which, on combustion, produces ashes that mainly consist of various metal carbonates and oxides. The most commonly employed approach for the solid catalyst preparation from plant materials is the calcination process, and it is performed at temperatures ranging from 300 to 1200°C. It is known that the temperature employed for calcination plays a vital role in the composition and development of the morphology of the catalyst. The variation in alkalinity, porosity, and, accordingly, the catalytic activity of the catalyst is significantly influenced by the calcination temperature. It was found that the potassium present in the form of oxide and carbonate as the main constituent in such catalysts played a significant role in delivering catalytic efficacy. Therefore, a number of agricultural waste-based catalysts were reported as efficient catalysts. The selection of the catalyst may be one of the important issues for application in large-scale biodiesel production. Thus, the present study was undertaken for the preparation of a rank list among the reported catalysts by following the VIKOR (Višekriterijumsko Kompromisno Rangiranje) multicriterion decision-making approach. In this work, the ranking study was performed considering the reported optimum reaction conditions (ORCs) of biodiesel synthesis reactions. The study was conducted strictly on the basis of the parameters, viz., catalyst concentration ( C 1 ), MTOR ( C 2 ), reaction temperature ( C 3 ), reaction time ( C 4 ), and biodiesel yield ( C 5 ). The parameters are considered good if C 1 , C 2 , C 3 , and C 4 are low or minimum and if C 5 is high or maximum. The catalyst prepared from plantain peel showed the best performance and ranked as the first one followed by Musa paradisiaca peel and cocoa pod husk catalysts which are ranked second. Thus, the VIKOR method can be useful for comparison and ranking purposes if there are a large number of data, and this may be expanded for thorough study by considering more criteria which may give more fruitful results.

Multi-criteria decision support systems for electric vehicle charging schedules in a smart secondary distribution system

The operation of a smart secondary distribution network (SDN) has gained significance due to the penetration of chargers for electric vehicle (EV) and in-situ generation. The SDN operators (SDNOs) need dedicated decision support systems (DSS) for scheduling the EVs for charging without overloading the distribution transformer. Multi-criteria DSS(MCDSS) are proposed for the first time to balance the conflicting constraints stemming from the perspectives of both EV users and grid operators. This new approach has also incorporated a contribution-based fairness value (CFV) for each prosumer. MCDSS formulations employing analytical hierarchy process (AHP), VIšekriterijumsko KOmpromisno Rangiranje (VIKOR), and Preference Ranking Organisation METHod for Enrichment Evaluation (PROMETHEE) have been developed for generating fair charging schedules. Performance metrics have also been proposed to compare the three MCDSS techniques. The developed scheduling approaches have been tested in an Australian 19-bus SDN with Ausgrid datasets, and the schedules obtained are presented to bring out the significance of the proposed MCDSS.

Barriers to supply chain performance measurement during disruptions such as the COVID-19 pandemic

PurposeAmid the outbreak of coronavirus disease 2019 (COVID-19), supply chains have faltered. This has influenced operational and financial performance and lead to uncertainty in supply and distribution. Therefore, systems measuring supply chain risk and disruption management performance have gained interest. This study explores barriers to supply chain performance measurement during disruptions such as COVID-19.Design/methodology/approachBased on a survey and literature review, the authors formalise the barriers and rank them using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) fuzzy Višekriterijumsko kompromisno rangiranje (VIKOR) methodology. A total of 14 experts in 11 countries were surveyed. Performance measurement is based on a balanced scorecard.FindingsFifteen barriers are identified. Based on DEMATEL analysis, the cause–effect relationships among the four scorecard aspects are explored. The customer axis is revealed as the cause, while the financial, internal business and learning/development are identified as the effect of the supply chain performance measurement. Fuzzy VIKOR calculations show that uncertainty of investment, disrupted cash flows and the bullwhip effect are the most critical barriers to measure supply chain performance during outbreaks such as the COVID-19 pandemic.Research limitations/implicationsThe study identifies and ranks general barriers; additional research is required to differentiate barriers in specific industrial sectors.Practical implicationsThe findings may help develop proactive, resilient supply chain performance strategies to overcome disruptions.Social implicationsPolicy-makers and decision-makers in industrial and service firms can explore these findings to inform strategies for robust supply chains that can resist disruption in risky environments.Originality/valueThis research addresses a knowledge gap in barriers to measure supply chain performance in post-pandemic areas. It is unclear how far firms will measure supply chain performance in terms of learning from disruption patterns, managing financial and customer demand processes in light of COVID-19. This study contributes by explaining the influences among the barriers and exploring them, offering insights from multiple stakeholders.

Optimization of Welding Process Parameters Using the VIKOR MCDM Method

Optimization of welding process parameters These welding parameters are welding current, welding voltage, gas flow rate, wire feed rate, etc. They affect welding strength, weld pool geometry of steel material during welding. By using the DOE method, the parameters can be optimized and have the best combination of parameters for the target quality. The VIKOR (VIšekriterijumsko Kompromisno Rangiranje) Optimal replacement Select method is used Biomass product, Catalyst, Solvent, Temperature/ K. in Evaluation. Alternatives Wood, Bio-oil, Lignin, Glucose, Saccharine is the Best and Worst Value. Saccharides is got the first rank whereas is the Glucose is having the Lowest rank.

Evaluation of Merchant Banking and Financial Services using VIKOR Method

Commercial banking is a professional service offered by commercial banks to customers for adequate consideration to make payments for their financial needs. Commercial banks are banks that raise funds, provide financial advice and lend to large corporations. These banks are experts in international trade and are experts in dealing with large companies and industries. Commercial banking provides finance to multinational businesses and large commercial enterprises in the country, which helps in boosting the economic strength of the country. Commercial banks do not provide services to the general public; Their services are limited to commercial companies and large business enterprises. A merchant banker fa-cilitates the subscription of securities. A commercial banker plays an important role and undertakes many responsibilities such as private placement of securities, management of public issue of securities, stock broking, and international financial advisory services. A commercial bank is a type of financial institution that offers underwriting, credit services, financial advice services, and fundraising to high-net-worth individuals and large corporations (HWNIs). Commercial banks are transnational organizations with a focus on global trade and service delivery. The VIKOR (VIšekriterijumsko Kompro-misno Rangiranje) Optimal replacement Select method is used in Australia/New Zealand, Continental, Europe, UK, Japan, Singapore, United States. Alternative: Australia/New Zealand, Continental, Europe, UK, Japan, Singapore, United States. Evaluation parameters of Area of manufacturing: Number of Partners, Number of Partners Bank Years, Share of joint venture banks assets, Average ownership per partner. Results: Australiar/New Zealand is got the first rank whereas is the Singapore is having the Lowest rank.

Type-II fuzzy collaborative intelligence for assessing cloud manufacturing technology applications

• Nine cloud manufacturing applications are compared. • Efficient approximating alpha-cut operations method is proposed to enhance the derivation of fuzzy priorities. • Type-II fuzzy VIKOR is applied to assess a cloud manufacturing application. Cloud Manufacturing (CMfg) is a new manufacturing paradigm that can reduce costs, improve data analysis, increase efficiency and flexibility, and provide manufacturers with closer partnerships. However, most previous studies on CMfg focused on the planning and scheduling of a hypothetical CMfg system or its infrastructure. In addition, the cost effectiveness of a CMfg application has rarely been evaluated. Consequently, manufacturers are not certain about adopting specific CMfg applications. To address this issue, this research proposed a type-II fuzzy collaborative intelligence approach to assist in the selection of suitable CMfg applications in a factory. In the proposed methodology, first, an efficient approximating alpha-cut operations (exACO) method was proposed to enhance the efficiency of the derivation of the fuzzy priorities of factors, which is an innovative treatment. Subsequently, the membership function of a type-II fuzzy priority was derived from the overall and partial consensuses among decision makers using layered fuzzy intersection (LFI), which is also a novel approach. As the type-II fuzzy priority cannot be described using a type-II triangular or trapezoidal fuzzy set, a type-II fuzzy VIšekriterijumskoKOmpromisnoRangiranje (VIKOR) method based on the α -cuts of fuzzy priorities was employed to assess and compare nine CMfg applications. The experimental results revealed that “migrating legacy system to CMfg services” and “cloud-based customization environment” were the most and least preferable CMfg applications, respectively.

Assessment of third-party logistics providers by introducing a new stochastic two-phase compromise solution model with last aggregation

In the conditions of increasing governments' and consumers' awareness of environmental protection and sustainability, the enterprises have been encouraged to devote more attention to reverse logistics (RL) activities. Assessment of third-party reverse logistics providers (3PRLPs) is a crucial decision strategy for companies who choose to outsource their RL activities to third-party partners. To ensure accurate information is reflected in the decision process, it is imperative to consider uncertain information. To this aim, this paper draws attention to the selection of the most preferred RL providers using a novel comprehensive stochastic compromise solution by considering the uncertainty associated with decision variables. This paper presents a novel multi-attribute group decision-making (MAGDM) framework by integrating a new stochastic criteria importance through inter-criteria correlation (CRITIC) method and an innovative last aggregation stochastic two-phase compromise solution based on the visekriterijumsko kompromisno rangiranje (in Serbian) (VIKOR) approach to provide systematic decision support for companies to select the most preferred RL providers. In the proposed framework, the CRITIC method is utilized to calculate the priority weights of the attributes. The innovative last aggregation stochastic two-phase compromise solution is employed to evaluate decision-makers (DMs) and alternatives simultaneously. Moreover, the proposed compromise method exploits the pessimistic, most likely, and optimistic solutions to deal with stochastic uncertainty and provide DMs with more flexibility in the final evaluation. The approach is also validated by applying a sample case for selecting 3PRLPs along with sensitivity analysis on the weights of the different attributes in order to investigate the robustness of the results. Consequently, to demonstrate the reliability of the suggested approach, comparative analyses of the final ranking are conducted. The outcome of the study reveals the proposed model provides a viable, high-performance, and flexible decision-making process, by which the DMs can provide more prompt and correct judgments on the selection of the best 3PRLPs.

Application of MEREC in Multi-Criteria Selection of Optimal Spray-Painting Robot

Robots are being increasingly utilized for various operations in industrial and household applications. One such application is for spray painting, wherein atomized paint particles are sprayed on a surface to coat the surface with paint. As there are different models of robots available for the job, it becomes crucial to select the best among them. Multi-criteria decision-making (MCDM) techniques are widely used in various fields to tackle selection problems where there are many conflicting criteria and several alternatives. This work focuses on selecting the best robot among twelve alternatives based on seven criteria, among which payload, speed, and reach are beneficial criteria while mechanical weight, repeatability, cost, and power consumption are cost criteria. Five MCDM techniques, namely combination distance-based assessment (CODAS), complex proportional assessment (COPRAS), combined compromise solution (CoCoSo), multi-attributive border approximation area comparison (MABAC), and višekriterijumsko kompromisno rangiranje (VIKOR) were used for the selection while a weight calculation was performed using an objective weight calculation technique called MEREC. HY1010A-143 was found to be the most suitable robot for spray-painting applications by four of the five techniques used. Correlation studies showed a significant level of correlation among all the MCDM techniques.