Worst Method Research Articles

A FMEA Optimization Method Based on TODIM and Best Worst Method-Water Filling Theory in Pythagorean Fuzzy Language Environment for Reliability Assessment of Industrial Robot

Abstract In view of the shortcomings of traditional failure modes and effects analysis (FMEA) in risk evaluation language, weight information, risk priority number (RPN), this paper proposes an FMEA optimization method. First, using the Pythagorean fuzzy language as the evaluation language, the hesitation psychology of the evaluator is truly reflected. Then, the best worst method (BWM) is used to calculate the weight of the evaluator, it can reduce the number of pairwise comparison evaluations. Second, water filling theory (WFT) uses mean values instead of extreme values to determine the discreteness of evaluation information, which is more consistent with FMEA. Therefore, WFT is used to calculate the weight of influencing factors. Finally, the tomada de-decisao iterativa multicriterio (TODIM) method is used for compromise calculation to obtain the risk ranking of failure modes. Compared with RPN, TODIM can avoid the situation that the failure mode scores are the same. At the end of the paper, the robustness and superiority of the new method are verified by taking the reliability assessment of reversing system of industrial robots as an example.

A new probabilistic linguistic decision-making process based on PL-BWM and improved three-way TODIM methods

Probabilistic linguistic term sets (PLTSs) provide a flexible tool to express linguistic preferences, which allow decision-makers to label linguistic information with different probabilities. In this paper, a method based on a PLTS is proposed to address multi-criteria decision-making problems (MCDM). We develop the theory of PLTSs and put forward a novel best–worst method (BWM), termed PL-BWM, based on PLTS. Our method fully reflects the preference information of decision-makers and accurately provides the importance level of the criteria. The combined weight of the criteria is obtained by merging PL-BWM-based subjective weights and similarity minimization-based objective weights. Upon introducing a three-way decision system to improve the TODIM method, a novel three-way TODIM method is proposed and showcased on an optimal new energy vehicle selection problem. The effectiveness and accuracy of the proposed method are verified by sensitivity analysis and comparative analysis. Our approach paves the way for new developments in solving MCDM problems and for novel applications in otherwise difficult ranking problems.

Design of a smart medical service quality evaluation system based on a hybrid multi-criteria decision model

As medical informatization continues to progress, the sophistication of smart medicine (SM) systems has led to a marked enhancement in the caliber of medical services provided. Nevertheless, the existing body of literature is sparse when it comes to frameworks for evaluating service quality, specifically within the domain of smart medicine (SM). Drawing on a hybrid multi-criteria decision-making model that fuses the best–worst method (BWM) with the VIKOR approach, this research has crafted an innovative framework for assessing the service quality of SM. BWM was used to obtain the weights of all dimensions and indicators under each dimension. Then, the service quality of hospitals H1, H2 and H3 in Xiamen was evaluated using the VIKOR method. The results showed that smart appointments, diagnosis and treatment are three important dimensions to evaluate SM service quality in medical institutions. The stability and robustness of the model were proved through sensitivity analysis. Findings suggest that hospitals can strengthen the construction of their appointment information platforms, the quality management of internal doctors, and the information connection between self-service terminals and information platforms to improve hospital service quality in the construction of smart medicine.

Hybrid Multi-Criteria Decision Making for Additive or Conventional Process Selection in the Preliminary Design Phase

Additive manufacturing (AM) has become a key topic in the manufacturing industry, challenging conventional techniques. However, AM has its limitations, and understanding its convenience despite established processes remains sometimes difficult, especially in preliminary design phases. This investigation provides a hybrid multi-criteria decision-making method (MCDM) for comparing AM and conventional processes. The MCDM method consists of the Best Worst Method (BWM) for the definition of criteria weights and the Proximity Index Value (PIV) method for the generation of the final ranking. The BWM reduces the number of pairwise comparisons required for the definition of criteria weights, whereas the PIV method minimizes the probability of rank reversal, thereby enhancing the robustness of the results. The methodology was validated through a case study, an aerospace bracket. The candidate processes for the bracket production were CNC machining, high-pressure die casting, and PBF-LB/M. The production of the bracket by AM was found to be the optimal choice for small to medium production batches. Additionally, the study emphasized the significance of material selection, process design guidelines, and production batch in the context of informed process selection, thereby enabling technical professionals without a strong AM background in pursuing conscious decisions.

A maturity model for assessing Industry 4.0 implementation using data envelopment analysis and best and worst method approaches

A maturity model for assessing Industry 4.0 implementation using data envelopment analysis and best and worst method approaches

Techno economic analysis of electrolytic hydrogen production by alkaline and PEM electrolysers using MCDM methods

Hydrogen, a crucial clean and renewable energy source, addresses pressing challenges of energy security and environmental pollution. Water electrolysis for hydrogen production is a promising approach to satisfy the growing demand for sustainable energy. This study uniquely performs a comprehensive techno-economic analysis of hydrogen production using both Alkaline and Proton Exchange Membrane (PEM) electrolyzers, a first in the field to evaluate their performance comprehensively with advanced Multi-Criteria Decision-Making (MCDM) techniques. Leveraging TOPSIS, WASPAS interval methods, and the Best Worst Method (BWM) with fuzzy logic, this research introduces a novel evaluation framework that incorporates a wide-ranging set of factors, including environmental, technical, technological, economic, and social aspects, divided into 30 sub-criteria. These insights offer a comprehensive understanding of each electrolyser's strengths and weaknesses, helping stakeholders make informed decisions about cost reduction in hydrogen production technologies. This has not been done before. Although cost results favour Alkaline electrolysers, PEM electrolysers are attractive for specific applications where their benefits justify the higher initial cost, choosing between Alkaline and PEM electrolysers dependent on a given hydrogen production project's requirements.

Investigating the effects of barriers and challenges on Logistics 4.0 in the era of evolving digital technology

Purpose This study aims to reveal and prioritize the main barriers and challenges in front of the Logistics 4.0 transformation, which is the extension of Industry 4.0. Also, this study presents a roadmap for a company operating in developing countries to reduce and eliminate challenges and hurdles for each link in their supply chain. Design/methodology/approach A two-stage methodology was used in this study. First, a detailed literature review was conducted to identify the barriers to innovations compatible with Industry 4.0. Hence, barriers have been identified, including nine from the literature review. The best–worst method (BWM) is then used to determine these barriers’ weights and order of importance. To implement BWM, two-stage e-surveys are applied to experts. Findings The “Managerial and Economic Challenges” dimension is the most important, and “Regulatory and social challenges” is the least essential dimension among the main dimension. Moreover, financial constraints or capitals are the most critical barriers among the sub-barriers. This study gives the reader a comprehensive insight into how detected barriers affect digitalization performance. Therefore, this framework is a roadmap designed with a holistic view to guide manufacturers, logistics parties and even policy and decision-makers. Originality/value Theoretically and empirically identifies the potential barriers and challenges in the digital transformation of logistics is already missing at the desired level. From this point of view, to the best of the authors’ knowledge, this study is the first research that determines barriers based on the Logistics 4.0 model with an industrial perspective. One of the most important limitations of this study is that a total of nine dimensions were examined under only three basic barriers. Different alternatives can be identified for future studies.

A Model for Project Manager Competence Measurement in Iran Gas Engineering and Development Company

The purpose of this study is to build a Project Manager Competence Development (PMCD) model for Iran Gas Engineering and Development Company (IGEDC). The existent competence models in the related state-of-the-art are reviewed to generate and compile an initial list of project managers' competencies. Then, a Delphi analysis is used to complete the list and validate it. Further, the Best Worst Method (BWM) is employed to assign numerical weights to the competencies. As a result of the study, 16 competencies were identified in two categories: technical and behavioral. To show the applicability of the proposed PMCD, it is applied in a real-life study case. The results showed: (1) leadership competence has the highest weight, and (2) this fact that more than 99% of the total weight concerns only three competencies: leadership, project management knowledge, and judgment & decision making.

Supply chain risk assessment using best worst method: a case study of agro-industry skipjack tuna in Ambon - Indonesia

One of the main issues in the agro-industry supply chain is identifying and ranking different risk factors to maintain business continuity. This study discusses the agro-food supply chain risk assessment for smoked skipjack tuna in Ambon. Related literature and expert interviews identify risk factors that arise along the supply chain. These risk factors are contained in internal risk, company external operational risk, and macro-level risk. This research aims to evaluate comprehensively the risk factors of the smoked skipjack agro-industry supply chain, which are a priority to be addressed. The decision-making framework uses the BWM (Best Worst Method) to determine each risk factor's relative weight, followed by a sensitivity analysis to determine how robust the outcome is. Experts pick the risk factor assessment, and then an optimization model is modelled to obtain the weight of each risk factor, which is calculated with the help of Lingo software. The findings show that three risk factors will be prioritized to be addressed out of the eleven risk factors assessed, namely "Quality of the final product," "Financial instability," and "degradation of fish populations." Sensitivity analysis was also carried out to see the overall robustness of the results achieved. The weight of the selected risk factor ("final product quality (R1c)") has its weight value changed from 0.1 to 0.9 with an increase of 0.1. These findings are expected to help smoked skipjack tuna agro-industry managers make decisions to reduce supply chain risks and better administration management to maintain the sustainability of their business processes.

A hybrid BWM–CRITIC–VIKOR approach for assessing oil and gas risk scenarios in probabilistic linguistic term set

The oil and gas industry plays a crucial role in supporting energy supply and economic development. Mitigating risks in oil and gas projects is essential for reducing decision-making uncertainties, optimizing resource allocation, and fostering the competitiveness and sustainable growth of enterprises. Therefore, evaluating decision-making risks in the oil and gas sector is of significant practical importance. This paper proposes a comprehensive approach based on the BWM–CRITIC–VIKOR multi-criteria decision-making (MCDM) evaluation model. An evaluation index system encompassing six critical dimensions—technology, economics, environment, security, societal impact, and political factors—is established. To enhance assessment precision, the AHP interval estimation method is employed to identify and eliminate indicators with low contributions. Subsequently, the probabilistic linguistic term set (PLTS) is introduced into the best–worst method (BWM) and CRITIC methods to calculate the weights for each index. This approach helps to circumvent the subjectivity inherent in single subjective weighting methods. To evaluate and rank alternatives, the PLTS is used as an evaluation linguistic tool within the VIKOR framework. Finally, this methodology is applied to decision-making in the oil and gas industry, and its effectiveness and superiority are compared with the AHP–TOPSIS method and the BWM–CRITIC method.

Prioritizing Success Factors for Start-ups in Indonesia Using the Best Worst Method (BWM)

The rapid growth of Indonesia’s start-up ecosystem presents both opportunities and challenges for new ventures striving for sustainability and competitiveness. This study applies the Best Worst Method (BWM) to prioritize key success factors for start-ups in Indonesia, providing a structured framework for decision-making. Six critical factors were evaluated: access to funding, innovation capability, market competition, regulatory environment, talent acquisition, and scalability potential. Through pairwise comparisons, this research identifies access to funding as the most critical factor, while scalability potential is considered the least influential in determining start-up success. The findings offer valuable insights for entrepreneurs, investors, and policy-makers, highlighting areas where targeted support can enhance the growth and sustainability of start-ups. This study contributes to the ongoing discourse on start-up development in emerging economies by providing a decision-making tool to guide strategic priorities within Indonesia’s dynamic entrepreneurial landscape.

Bi-level optimization and integrated multiple-criteria decision making under uncertainty for structural design of insulated bearings

To address the premature failure of insulated bearings, this article proposes a design method for the structure of bearings to prolong their service life. First, a bi-level optimization model is established to determine the structural parameters of bearings considering their insulating and mechanical properties. Upper-level problems include bearing voltage ratio, porosity of insulating coatings, minimum thickness of oil film and Hertz contact area. Lower-level problems include fatigue life of bearings and adhesion of insulating coatings. Second, a non-dominated sorting genetic algorithm-III based on space decomposition and penalty-based boundary intersection (NSGA-III-SD-PBI) is designed to solve the optimization model. Third, the integrated multiple-criteria decision-making (MCDM) using the fuzzy best–worst method (BWM) and fuzzy technique for order preference by similarity to an ideal solution (TOPSIS) is developed to determine the best structural parameters of bearings. A case study demonstrates the effectiveness and superiority of the proposed method, with fatigue life increased by 20%.

Prioritizing freight carrier selection factors with the best worst method

Prioritizing freight carrier selection factors with the best worst method

A novel hybrid decision-making framework based on modified fuzzy analytic network process and fuzzy best–worst method

A novel hybrid decision-making framework based on modified fuzzy analytic network process and fuzzy best–worst method

GIS-based spatial modeling of landslide susceptibility using BWM-LSI: A case study – city of Smederevo (Serbia)

Abstract Landslides and slope processes constitute one of the most frequent natural hazards in valleys near major rivers and mountainous regions. The surface layer, characterized by its relatively loose composition, is prone to sliding due to a combination of distinct natural and human-related factors. Specific sections along the right bank of the Danube River in Smederevo city exhibit significant susceptibility to landslide activation, often leading to substantial material losses and posing a risk to the local population. The initial step in the provided research involves analyzing existing literature and mapping landslides within the study area. The initial analysis covers both natural conditions and anthropogenic activities. The second step includes establishing a geospatial database in the Geographic Information System and generating eight thematic maps. In the third step, different weight coefficients were assigned to the criteria, which facilitated the creation of the Landslide Susceptibility Index using the Best–Worst Method. Subsequently, in the fourth step, a composite map illustrating landslide susceptibility was produced. According to this research, about 4% of the territory of Smederevo, or 19.3 km2, is highly or very highly susceptible to landslides. These localities are located on the right bank of the Danube River and around the Ralja River. Receiver operating characteristic-area under the curve value indicates very high predictive power (approximately 1), thus suggesting the reliability of the used methodology. This visualization of areas highly prone to such occurrences empowers policymakers to implement more effective environmental protection measures and institute sustainable management practices for agricultural parcels in this region. Also, the provided research represents the inaugural integration of advanced remote sensing techniques and interdisciplinary investigations, offering deeper insights into landslide activity in the study area and yielding more comprehensive results.

Sustainability index development by integrating lean green and Six Sigma tools: a case study of the Indian manufacturing industry

PurposeIndia’s manufacturing sector employs about 12% of the labour force and contributes to about 17% of the nation’s GDP. The Indian government intends to implement several initiatives under the “Make in India” and Atma Nirbhar Bharat banners to increase the manufacturing sector’s share of the nation’s GDP to 25% by 2025. Applying lean manufacturing, green manufacturing and Six Sigma is crucial to ensure that India’s manufacturing sectors grow sustainably in international markets. This study aims to identify sustainability indicators and ascertain their respective weights to evaluate the sustainability performance of the Indian manufacturing industry.Design/methodology/approachThis research identifies 25 sustainability indicators and classifies them into the triple bottom line of sustainability based on an evaluative literature review and expert opinion. The Best Worst Method was utilised to determine the weights of the sustainability indicators. The sustainability index was developed to evaluate economic, social and environmental sustainability.FindingsThe sustainability performance of a foundry in a significant Western Indian State city was assessed by applying the developed sustainability index. After the adoption of integrated lean, green and Six Sigma (LG&SS) strategies and related practices in the foundry, there has been a notable improvement of 68.03% in the economic index, 61.62% in the social index and 13.24% in the environmental index.Research limitations/implicationsThe proposed sustainability index is applied and evaluated specifically for assessing the sustainability performance of Indian manufacturing SMEs. It can be used to substantiate firm’s sustainability performance and also to assess the improvement in firm’s performance in economic, environmental and social dimensions after implementing various operational excellence practices. However, it cannot serve as a benchmark tool across similar companies or organisations.Practical implicationsThe developed sustainable index can be used to analyse the company or organisation’s sustainability performance and see how various strategies have improved things. Practitioners can use this index to assess social, economic and environmental performance and focus on areas that need improvement.Social implicationsThe proposed sustainability index serves as a vital tool for monitoring a firm’s progress in triple bottom line (TBL) dimensions of sustainability, tracking a diverse range of indicators and encouraging sustainable organisational practices.Originality/valueThis study attempts to assess the economic, social and environmental performance of Indian Manufacturing SMEs by proposing a sustainability index.

Customer relationship management in healthcare: strategies for adoption in a public health system

ABSTRACT This study explores the adoption of customer relationship management (CRM) strategies in India’s public health system. A reflexive methodology and the fuzzy Delphi technique were used to identify 32 factors; these factors were weighted using the fuzzy best – worst method and evaluated to develop 18 strategies ranked using a quantitative strategic planning matrix analytical tool. A multiple-level appraisal of health needs, formation of integrated digitalized care pathways, establishment of a national health regulator, intersectoral integration of a unique national health identity, and promotion of health literacy emerged as key strategies for the adoption of CRM in public health systems.

Identifying hidden groundwater reserves: GIS advances and multi-criteria decision analysis for enhanced potential assessment

The aquifer system may become susceptible as a result of excessive groundwater extraction without regard for scientific principles. This study evaluates the Groundwater Potential (G.P.) using multicriteria decision analysis (MCDA) and geospatial modelling. Here in MCDA, the G.P. is measured using Remote Sensing (R.S.) and Geographic Information System (GIS), together with Analytical Hierarchical Process (AHP), Fuzzy Analytical Hierarchical Process (FAHP), and Best Worst Method (BWM). Analysis and model creation took into account 15 groundwater affecting elements that affect the G.P. Groundwater Potential Zones (GPZs) in Cachar District, India varied by the following percentages: 46.97%, 37.41%, and 15.62% for AHP; 46.13%, 40.92%, and 12.95% for FHP; and 50.65%, 36.51%, and 12.84% for BWM, respectively, for low, medium, and high zones. The FAHP and BWM models outperformed the AHP model, according to the results of the qualitative validation. The concerned authorities might identify vulnerable locations and plan sustainable groundwater management with the use of these MCDA approaches combined with GIS.

Risk assessment of energy performance contracting in Türkiye utilizing best–worst method

Risk assessment of energy performance contracting in Türkiye utilizing best–worst method

Integration of organizational, economic and customer-related attributes to prioritize marketing strategies

PurposeA well-designed marketing strategy is critical for the survival of any company in today’s competitive market. To be formulated and implemented effectively, a marketing strategy must be phased and aligned to levels in the organization. This study aims to advance a three-tier hierarchical framework of marketing strategies, including corporate, business and functional levels. The authors use the proposed framework to select the most appropriate marketing strategy based on the factors relevant to a factory that produces sporting goods.Design/methodology/approachThe authors conduct a literature review to identify marketing strategies at corporate, business and functional levels. To appraise strategies at the corporate and business levels, the authors use market share as a key criterion. When evaluating functional strategies, the authors use criteria categorized into organizational, economic and customer dimensions. Additionally, the authors conduct interviews to assess strategies at the first level and use the best worst method to appraise strategies at the other two levels.FindingsThe authors use the suggested structure for a company producing sports goods in Iran. According to the results, an offensive approach and customer orientation are the most appropriate strategies at corporate and business levels. Additionally, offensive advertising and managerial capabilities are identified as the best portfolio of strategies and the most important criterion at functional level, respectively.Originality/valueSo far, a specific category of marketing strategies has not been implemented at corporate, business and functional levels. Accordingly, there is not a framework of criteria to evaluate the strategies at each level. The approach is implemented in the case of a sportswear manufacturer in a developing country, where quantitative analysis has been lacking until now.