Search Results (44)

Overall Equipment Effectiveness (OEE) measures manufacturing productivity as the product of Availability (A), Performance (P), and Quality (Q). Despite its widespread adoption, the classical OEE formula embeds a structural limitation, i.e., the three components are treated as equally important regardless of operational context. This fixed-weight assumption distorts maintenance prioritisation in environments where one component dominates operational losses. To the best of the authors’ knowledge, no published framework has formally addressed this limitation through a structured, auditable multi-criteria weighting model. This paper proposes Adaptive OEE, a FUCOM–TOPSIS framework that replaces the fixed A × P × Q product with a context-driven weighting model. FUCOM derives context-specific weights for A, P, and Q from expert judgement with minimum elicitation effort and mathematically guaranteed consistency. TOPSIS is adapted from its classical formulation by replacing data-derived ideal solutions with fixed reference poles defined independently of the observed data, ensuring that the effectiveness score of each asset is not influenced by the performance of other assets in the dataset. Three illustrative case studies covering availability-dominant, performance-dominant, and quality-dominant industrial scenarios suggest that classical OEE rankings are not preserved under asymmetric weight configurations, with ranking divergence being most severe when one component carries strongly asymmetric weight, precisely the condition that equal weighting cannot accommodate. The principal contributions are the formalisation of the equal-weight assumption as a formal methodological limitation, the replacement of multiplicative aggregation with a weighted distance measure, and the adaptation of TOPSIS with fixed reference poles for context-independent asset scoring. The framework is directly applicable by maintenance managers and industrial engineers seeking operationally justified equipment rankings without specialised analytical expertise. Full article

Organizations’ increasing reliance on digital systems has made Disaster Recovery Centers (DRCs) a critical component of sustainable urban resilience. Disruptions in digital infrastructures directly affect corporate operations as well as the continuity of education, healthcare, and public services. Therefore, DRC site selection requires a holistic evaluation of multidimensional criteria, including environmental risk, infrastructure continuity, and operational reliability, rather than relying solely on physical suitability analysis. This study proposes a generalizable decision-making framework that comparatively evaluates GIS-based spatial suitability analysis and the ELECTRE I outranking model. Criterion weights are derived using the Fuzzy FUCOM method and applied exclusively within the ELECTRE I model for alternative evaluation. In the first stage, spatial suitability was assessed in a GIS environment using topographic and physical risk indicators such as slope, landslide susceptibility, and flood hazard. In the second stage, operational continuity criteria, including energy redundancy, telecommunication continuity, and RTO/RPO compliance, were weighted using Fuzzy FUCOM. The resulting weights were employed in the ELECTRE I model to calculate outranking relationships, supported by net concordance and discordance indices. Application results demonstrate differing ranking structures between the two approaches, reflecting distinct representations of physical suitability and operational resilience. Sensitivity analysis confirms the robustness of the findings. The study presents a scalable decision-support framework for sustainable digital infrastructure planning. Ultimately, this study demonstrates that the integrated GIS–MCDM approach can support decision-makers in enhancing digital resilience and maintaining the long-term operational continuity of critical infrastructures in disaster-prone regions. The findings further indicate that locations with balanced physical suitability and strong infrastructure continuity emerge as the most appropriate alternatives for DRC establishment. Full article

Sustainable forklift technologies have become essential in modern industrial logistics due to increasing environmental regulations, rising energy costs, and heightened occupational safety requirements. Given the complexity and variety of sustainable forklift options, selecting the most appropriate one has become a critical multi-criteria decision-making (MCDM) problem for companies. This study aims to determine the most appropriate sustainable forklifts by considering multiple qualitative and quantitative criteria that play a critical role in the forklift selection process of companies. To this end, meetings are conducted with managers possessing expertise in sustainability and logistics at companies operating in Turkey. Based on these insights, ten forklift alternatives and six evaluation criteria are identified. This is the first time, in this study, sustainability criteria such as sustainability in occupational health and safety, sustainability in agility, sustainability in ergonomics, durability and material sustainability, sustainability in load lifting capacity and sustainability in price are incorporated into the evaluation. To the best of our knowledge, no study in existing literature has specifically focused on sustainable forklift selection, incorporating the comprehensive sustainability-oriented criteria considered in this study. The Analytic Hierarchy Process (AHP) is employed to determine the weight of each criterion. Subsequently, forklift alternatives are ranked using the Multi-objective Optimization by Ratio Analysis (MOORA) ratio approach, the Additive Ratio Assessment (ARAS), and the Elimination and Choice Translating Reality (ELECTRE) methods. Moreover, weights derived based on different subjective and objective weighting schemes, specifically FUCOM, BWM, and Entropy, as well as the resulting ranking outcomes are comparatively examined to assess the impact of varying weighting structures on the robustness and consistency of the final decision results. The proposed methodology is applied within manufacturing and logistics companies in Turkey to assess its practical effectiveness. As a result of this study, the most appropriate sustainable forklifts for the companies are identified. Furthermore, the outcomes of the applied methods yield consistent/similar results. The results emphasize that managers should place greater importance on the criteria of sustainability in occupational health and safety—identified as the most critical factor—followed by durability and material sustainability, and sustainability in load lifting capacity when selecting forklifts. Sensitivity analyses indicate that the method yields consistent and effective results. Moreover, it demonstrates the robustness and accuracy of the forklift evaluations. In this context, this study serves as a guided reference for companies in the selection of sustainable forklifts. Full article

Vulnerabilities in conventional agri-food supply chains (CAFSCs) necessitate a shift toward resilient, localized production models. Within the Agri-Food 4.0 landscape, urban Controlled-Environment Hydroponic Agriculture (CEHA) systems address these challenges by shortening supply chains and mitigating climate-induced breakdowns. However, structurally aligning Triple Bottom Line (TBL)-oriented stakeholder needs with complex technical specifications remains a critical challenge in sustainable CEHA system design. To address this challenge, the present study proposes a novel framework integrating the Full Consistency Method (FUCOM) and Quality Function Deployment (QFD) within a Finite Interval Type-2 (FIT2) Gaussian fuzzy environment. This approach systematically translates TBL-oriented priorities into precise engineering specifications, mapping 17 stakeholder needs (SNs) to 30 technical design requirements (TDRs) while capturing linguistic uncertainty and hesitation. The findings reveal a clear strategic focus on environmental and social sustainability. Specifically, high product quality, food safety and traceability, consumer acceptance, and minimization of environmental impacts emerge as the primary drivers of CEHA adoption. The QFD translation identifies scalable IoT infrastructure, sensor maintenance and calibration, and AI-enabled decision support as the most critical TDRs. The framework’s reliability and structural robustness were rigorously validated through comprehensive analyses, including Kendall’s W test to confirm expert consensus, alongside a Leave-One-Out (LOO) approach, weight perturbations, and a structural evaluation of TDR intercorrelations. These findings provide a scientifically grounded roadmap for designing sustainable, intelligent urban agricultural systems. Ultimately, this framework offers actionable managerial implications for agribusiness stakeholders to bridge strategic TBL-oriented goals with practical engineering, significantly enhancing agri-food supply chain resilience. Full article

Traffic signal control at urban intersections is one of the key determinants of the overall efficiency of the transportation system, given its direct impact on travel time, congestion levels, and emissions of exhaust fumes. This study proposes an integrated hybrid model that combines a metaheuristic Genetic Algorithm for generating potential signal timing plans with fuzzy multi-criteria decision-making (MCDM) for their evaluation and selection of the optimal solution. In order to determine the relative importance of criteria, the fuzzy methods F-AHP, F-FUCOM, and F-PIPRECIA were employed, thus providing stable assessments of criteria importance under conditions of uncertainty and expert subjectivity. The ranking of generated alternatives was performed by employing the F-TOPSIS, F-WASPAS, and F-ARAS methods, while the robust decision-making rule approach was employed to develop a robust decision-making rule by integrating multiple MCDM methods. The proposed model was tested using data collected from a real urban intersection. The results show that the integrated hybrid approach enables a significantly more reliable selection of the optimal signal timing plan and achieves higher traffic management efficiency compared to traditional methods. The proposed model provides a flexible and scalable framework that can be adapted to different types of intersections and traffic demand conditions, thereby significantly contributing to the development of modern intelligent traffic management systems. Full article

Supplier assessment plays a pivotal role in various sectors and is a key component of supply chain management (SCM); however, it combines complexities and challenges associated with uncertainty and dynamic requirements. Several studies have applied various methods to assess suppliers; however, their calculations are complex. Therefore, this work introduces a new hybrid method, depending on the full consistency method (FUCOM) with triangular fuzzy numbers (TrFNs) to consistently prioritize supplier assessment criteria, using the distance from the ideal assessment criterion to assess various suppliers, as well as to handle uncertainty. The proposed method is applied to a practical case study, and the results show that it prioritizes the assessment criteria, reflecting stakeholder preferences. Moreover, it enables decision makers to construct a set of decision matrices and take into account various viewpoints, and it uses simple, detailed steps with TOPSIS, thus avoiding confusion. Additionally, the results indicate that the use of the FUCOM-TrFNs provides consistent weights and a robust tool for imprecise problems, with fewer comparisons and less confusion during calculations. Ultimately, the findings provide valuable insights for assessing and selecting suitable suppliers with a more applicable method. Full article

With the growing demand for energy and the limitations of fossil fuel resources, the utilization of renewable energy sources has become a vital and sustainable solution. However, identifying optimal locations for the development of these resources remains a major challenge in energy planning. Accurate spatial potential assessment can play a critical role in enhancing efficiency and reducing production costs. This study aims to present a scenario-based framework for assessing solar and wind energy potential in Pakistan. A total of 19 spatial criteria were used, categorized into evaluation and constraint factors. The full consistency method (FUCOM) was applied to weight the criteria, while the ordered weighted averaging (OWA) method was employed to model various potential scenarios. The results revealed that global horizontal irradiation (GHI) and proximity to transmission lines are the most significant factors for solar energy, whereas wind speed and wind power density are crucial for wind energy potential. Scenario analysis indicated that, under the AND scenario, the area with very high potential for solar and wind energy is 8005.72 km² and 968.98 km², respectively. These values increase to 63,607.52 km² and 16,288.32 km² under the OR scenario. The spatial agreement map for the simultaneous development of solar and wind energy showed an overlap of 461.42 km² in the AND scenario and 11,836 km² in the OR scenario. These findings highlight the importance of scenario-based decision-making approaches and accurate spatial evaluations in the development of multiple renewable energy plant sites under various investment and policy conditions. Moreover, the proposed framework can serve as a practical model for simulating and assessing renewable energy development potential in other regions of the world. Full article

In modern industrial production, the selection and evaluation of technological processes is a factor in achieving high quality, efficiency, and sustainability. Due to the existence of numerous and often contradictory criteria, the decision-making process requires the application of reliable multi-criteria methods. This article demonstrates the application of MCDM (Multi-Criteria Decision-Making) methods, the FUCOM (Full Consistency Method), for evaluating and selecting a rational technological process under real production conditions. The research results presented in the article demonstrate that the FUCOM method ensures a high degree of consistency, transparency, and efficiency in the evaluation of technological processes. It allows, among a variety of alternative technological process for manufacturing a given product, for the clear identification of the most rational one according to specified requirements. The data obtained in a real production environment confirm the applicability of the method in the field of production engineering and provide a basis for future research and optimization of technological processes. Full article

The selection of an appropriate technological process is essential to achieve optimal results in manufacturing companies. This affects quality, efficiency and competitiveness. In the modern industry, multi-criteria decision-making (MCDM) methods are increasingly used to evaluate, optimize and solve various manufacturing challenges. In this review article, existing methodologies and patents related to optimization and decision making are investigated. The main characteristics and applications of the methods are outlined. The purpose of this article is to provide a systematic review and evaluation of the main MCDM methods used in industrial practice, including through an analysis of relevant methodologies and patents. The methodology involves a structured literature and patent review, focusing on applications of widely used MCDM techniques such as the AHP (analytic hierarchy process), ANP (analytic network process), FUCOM (full consistency method), TOPSIS (technique for order preference by similarity to ideal solution), and VIKOR (višekriterijumsko kompromisno rangiranje). The analysis outlines each method’s strengths, limitations and areas of applicability. Special attention is given to the potential of the FUCOM for process evaluation in manufacturing. The findings are intended to guide researchers and practitioners in selecting appropriate decision-making tools based on specific industrial contexts and objectives. In conclusion, from the comparative analysis made, the methodologies reveal their advantages and disadvantages as well as limitations that arise in their application. Full article

In the conditions of modern production, the choice of a rational technological process is crucial for the competitiveness and efficiency of enterprises. Traditional decision-making methods are often accompanied by subjectivity and insufficient precision, which determines the need for the implementation of modern information technologies. This paper addresses the selection of an optimal technological process through the application of a developed web-based software application. The software application integrates an algorithm in which a multi-criteria decision-making (MCDM) method—FUCOM (Full Consistency Method)—is implemented, which allows the evaluation and comparison of alternative technological processes according to criteria such as price, time to produce, accuracy, roughness, shape deviation, etc. To confirm the effectiveness of the application, real production data is used, and the results show a significant reduction in time and subjectivity in decision-making. The developed application can be successfully implemented in enterprises of different industries, contributing to the increase in the efficiency of production processes and the optimization of resources. Full article

Considering the characteristics of urban planning that are becoming increasingly demanding, and the trend that urban zones should meet users’ needs based on the principle of everything in one place, this paper evaluates the potentials of urban zones in Novi Sad. An expert analysis defined 25 criteria related to urban, traffic, architectural, environmental and sociological aspects to assess the current potentials of urban zones in a sustainable manner. Based on these criteria, 10 urban zones were evaluated using a multi-structure fuzzy MCDM model, including: the Fuzzy FUCOM, IMF SWARA and Fuzzy OPARA methods, and the Fuzzy Heronian Mean and Fuzzy Bonferroni operators. Fuzzy FUCOM was applied to determine the importance of the main groups of criteria, while IMF SWARA was used to determine the importance of sub-criteria, with the final weights obtained using the Fuzzy Heronian Mean operator. The Fuzzy OPARA method was implemented to determine the rankings of urban zones based on the potentials they offer. This model represents an innovation, as it is being presented for the first time in the literature. The final values of the urban zones show that Liman and the Center are the two urban zones with the greatest potential, which was confirmed through extensive verification analysis. Such modeling can provide support in the sense that the management of the city can obtain information about the shortcomings and potentials of the location, which allows for the definition of a more specific planning and development policy, based on the previously verified state. Full article

Background: Supply chain management (SCM) plays a fundamental role in the progress and success of organizations and has continuously evolved to better adapt to today’s complex business environments. Consequently, the issue of supplier evaluation and selection (SES), which is one of the most critical decisions in SCM, has gained special significance and has been examined from various perspectives. The concept of green and resilient (gresilient) SCM has emerged in response to recent concerns about environmentally friendly production and operations, as well as organizations’ ability to cope with crises and disasters. In the rapidly growing construction industry, applying gresilient principles can ensure green operations and help overcome future challenges. Methods: This study focuses on gresilient SES in a real-world construction case study, proposing a streamlined FUCOM (S-FUCOM) approach. The proposed method streamlines traditional FUCOM processes to solve decision-making problems in deterministic and uncertain environments. Several numerical examples are provided to illustrate its applicability. Results: the case study results identify air emissions, environmental management systems, and restorative capacity as the most critical gresilient SES criteria. Conclusions: The third supplier emerged as the top performer based on decision-making indicators. Finally, a sensitivity analysis was conducted across 20 scenarios, demonstrating that S-FUCOM is robust and provides stable results. Full article

The sustainable development and operation of mining enterprises as major sources of economic growth in many countries is determined by a balance of economic, environmental, and social objectives and the resources required to achieve these objectives. Transportation is one of the main equipment at open pits. It accounts for up to 70% of open pit operating expenses. Various parameters of transportation means should be coordinated both with the parameters of the open pit and meet the conditions of its operation. The authors have developed a universal system of criteria for selecting a dump truck model for open pit conditions. The novelty of the proposed system lies in the complex consideration of all known factors to date and criteria of dump truck selection and the allocation of four groups of criteria: technical, technological, environmental, economic, and organizational. The groups of criteria and specific criteria in each group were ranked by the degree of importance using the multi-criteria decision-making method FUCOM (Full Consistency Method). The methodology of creating criteria systems in conditions of influence on the choice of alternatives of a set of interrelated factors is presented. The peculiarity of the methodology is the evaluation of different sets of criteria by several groups of experts with different competencies. The obtained criterion ranks are recommended to be used by managers of mining enterprises to choose a dump truck model. The presented methodology is suitable for the development of new systems of criteria, considering significant changes in operating conditions or the emergence of factors not considered in this study. Evaluation of all models of dump trucks on the market using the developed system of criteria is envisaged by the authors in a future study. Full article

The selection of the appropriate distribution channel is crucial for the success of any business dealing with physical goods. When dealing with this selection, it is crucial to have an effective decision support system (DSS) that can assist with such decisions. While various DSS approaches exist in the literature, not all are suitable for real-world applications. This research aims to address this gap by developing practical DSS tools that can aid decision-makers in making optimal decisions even in situations of uncertainty. The paper explores six different distribution channels (retailer’s warehouse, wholesaler’s warehouse, manufacturer’s warehouse, cross-dock, 3PL services, and direct delivery) in order to select the optimal one based on nine established criteria (inventory costs, distribution costs, delivery speed, service level, market coverage, product availability, order consolidation capability, reverse logistics, and order tracking) by using the FUCOM (Full Consistency Method) and ADAM (Axial-Distance-Based Aggregated Measurement) methods. After applying the FUCOM method, C1 (inventory costs) had the highest value when observing criteria weights, whereas C9 (order tracking) had the lowest. The results of the ADAM method showed that A5 (3PL services) was the best-ranked alternative, whereas A4 (cross-dock) was ranked as the worst. Based on the results, a model validation, and sensitivity analysis was conducted to determine whether the final ranking of the alternatives will change. This research provides decision makers with the necessary tools for better decision making, leading to improved distribution operations and increased profitability for the business. Full article

In the past decade, sustainable supply chain management has received much attention from practitioners and academics due to the heightened emphasis on environmental, economic, and social sustainability by customers, for-profit and non-profit institutions, community organizations, legislation, and government oversight. Evaluating and selecting a suitable supplier is considered a critical choice, crucial in supply chain management. Social sustainability in the supplier selection process is an important factor that has not received sufficient attention from academicians. Social and societal challenges are increasingly impacting supply chains. To tackle this challenge in the agricultural section of nations with emerging economies, this study proposed a new methodology using Grey FUCOM (Full Consistency Method) and Gray PROMTHEE (Preference Ranking Organization Method for Enrichment Evaluation) methods for evaluating the social sustainability of wheat and barley seed production companies. This study assists seed users in identifying the most significant supplier selection criteria and one of the most effective suppliers for ecological sustainability throughout the supply chain while maintaining market competitiveness. The results demonstrated a consistent and dependable rating behavior about the weight coefficients of the criteria. Improving the procedures used to evaluate wheat and barley seed suppliers results in a healthier society. So, the proposed model can efficiently evaluate a critical component of the food supply chain in the early stages. Full article