807 research outputs found

    A prototype knowledge based fuzzy analytic network process system for sustainable manufacturing indicator

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    Sustainable manufacturing is a relatively new but a very complex manufacturing paradigm. The complexity arises as this paradigm covers three interdependent yet mutually supporting sustainability dimensions of economic, environmental and social. In a further step to embark on the essence of sustainable manufacturing, the development of appropriate indicators needs to be emphasized as compared to other efforts. Regrettably, the existing indicators have several drawbacks that may hamper the accuracy of sustainability performance assessment of an organization. As such, there are only a few standardized indicator mechanisms which can suit specific requirements of various manufacturing organizations. Hence, this study suggests a novel Knowledge-Based Fuzzy Analytic Network Process (KBFANP) system which can assist the decision making process of sustainable manufacturing by developing a new indicator mechanism. The KBFANP system comprises of four major phases, namely Initialization, Selection, Evaluation and Prioritization. The system incorporates the advantages of Knowledge-Based System Fuzzy Set Theory and Analytic Network Process into a single unified approach as a standardized indicator, which is applicable to all types of problem setting. A prototype of KBFANP system was developed, tested and analyzed on three experimental data sets and two real manufacturing settings. The system was able to provide solutions on the areas that need improvement with different levels of priority. This study also supports the notion of lean and green manufacturing as the elementary foundation of sustainable manufacturing implementation. The proposed KBFANP system can act as an advisory Decision Support System which is beneficial to both academia and industrial practitioners

    Project portfolio selection for increasing sustainability in supply chains

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    [EN] Sustainability practices impact on the competitiveness of organizations. Enterprises need approaches that both support the implementation of these practices by helping to define the strategic elements of sustainable supply chains and prioritize projects to increase profitability. The purpose of this paper is to propose an approach using the Analytic Hierarchy Process that supports the portfolio project decision by aligning the project selection process to the strategic objectives of a supply chain that pursue sustainability. This approach will benefit enterprises to prioritize projects that have the highest impact on the sustainability strategy of the supply chain over time. The approach has been applied to an Agri-food supply chain.Authors of this publication acknowledge the contribution of the Project GV/2017/065 "Development of a decision support tool for the management and improvement of sustainability in supply chains" funded by the Regional Government of Valencia.Verdecho Sáez, MJ.; Pérez Perales, D.; Alarcón Valero, F. (2020). Project portfolio selection for increasing sustainability in supply chains. Economics and business letters. 9(4):317-325. https://doi.org/10.17811/ebl.9.4.2020.317-325S3173259

    Key performance indicators selection through an analytic network process model for tooling and die industry

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    Funding Information: Radu Godina and Pedro Espadinha-Cruz acknowledge Funda??o para a Ci?ncia e a Tecnologia (FCT-MCTES) for its financial support via the project UIDB/00667/2020 (UNIDEMI).In the last few decades, the fast technological development has caused high competitiveness among companies, encouraging a pursuit for strategies that allow them to gain competitive advantage, such as the monitoring of performance by using key performance indicators (KPIs). However, its selection process is complex since there are several KPIs available to evaluate performance and different relationships between them. To overcome this challenge, the use of a multiple criteria decision-making model (MCDM) was proposed, namely the analytic network process (ANP) through which a reduced number of them are prioritized. To identify which KPIs are suitable for the press cast and die manufacturing industry, a literature review was made, and 58 unique KPIs were identified. Thus, to validate the proposed methodology, a case study was carried out in an automotive press molding industry. With the implementation of the proposed ANP model it was possible to identify 9 KPIs that ensure the correct molding process monitoring, while being aligned with the Balanced Scorecard criteria. The results show that the proposed model is suitable for selecting KPIs for the molding industry.publishersversionpublishe

    A FRAMEWORK FOR STRATEGIC PROJECT ANALYSIS AND PRIORITIZATION

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    Projects that support the long-term strategic intent and alignment are considered strategic projects. Therefore, these projects must consider their alignment with the organization’s current strategy and focus on the risk, organizational capability, resources availability, political influence, and socio-cultural factors. Quantitative and qualitative methods prioritize the projects; however, they are usually suitable for specific industries. Although prioritization models are used in the private sector, the same in the public sector is not widely seen in the literature. The lack of models in the public sector has happened because of the projects’ social implications, the value perception of different projects in the public sector, and potentially differing value perceptions attached to the types of projects in different decision-making environments in the public sector. The thesis proposes a generic framework to develop a priority list of the available basket of projects and decide on projects for the next undertaking. The focus of the thesis is on public projects. The analysis in the framework considers the critical factors for prioritization obtained from the literature clustered through the agglomerative text clustering technique. In the proposed framework, 13 critical clusters are identified and weighted using the Criteria Importance Through Intercriteria Correlation (CRITIC) method to develop their ranking using the Technique for Order of Preference Similarity Ideal Solution (TOPSIS) method. In addition, the proposed framework uses vector weighting to prioritize projects across industries. The applicability of the framework is demonstrated through Qatar’s real estate and transportation projects. The outcome obtained from the framework is compared with those obtained through the experts using the System Usability Scale (SUS). The comparison shows that the framework provides good predictability of the projects for implementation

    Three Decades of Fuzzy AHP: A Bibliometric Analysis

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    [EN] For decades, Fuzzy Sets Theory (FST) has been consistently developed, and its use has spread across multiple disciplines. In this process of knowledge transfer, fuzzy applications have experienced great diffusion. Among them, Fuzzy Analytic Hierarchy Process (fuzzy AHP) is one of the most widely used methodologies today. This study performs a systematic review following the PRISMA statement and addresses a bibliometric analysis of all articles published on fuzzy AHP in journals indexed in Web of Science, specifically in Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI). The analyzed database includes 2086 articles published between 1994 and 2022. The results show the thematic clusters, the evolution of the academic conversation and the main collaboration networks. The main contribution of this article is to clarify the research agenda on fuzzy AHP. The results of the study allow academics to detect publication opportunities. In addition, the evidence found allows researchers and academics setting the fieldÂżs agenda to advise the editors of high-impact journals on gaps and new research trends.Castello-Sirvent, F.; Meneses-Eraso, C.; Alonso-GĂłmez, J.; Peris-Ortiz, M. (2022). Three Decades of Fuzzy AHP: A Bibliometric Analysis. Axioms. 11(10):1-34. https://doi.org/10.3390/axioms11100525134111

    Multi-Criteria Analysis and Decision-Making Approach for the Urban Regeneration: The Application to the Rimini Canal Port (Italy)

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    In recent decades, urban settlements have been greatly affected by globalisation, climate change, and economic uncertainty. When designing cities, these factors should be taken into account and adapted to the different contexts involved. The redevelopment of degraded urban areas is the first step toward achieving the sustainability aims set out in the Sustainable Development Goals. In this context, evaluation methods are required in the decision-making process, considering different social, economic, and environmental aspects to define the correct policies and actions for city redevelopment. In this paper, an evaluation methodology is proposed in order to obtain a priority scale of interventions for urban regeneration. Starting from on-site inspections to better know the current scenario, a set of indicators is established to evaluate the urban quality. Criticalities and potentials emerge through SWOT analysis and, with the ANP-BOCR method, the priority scale of the identified scenarios is defined. This decision-making approach was applied to the case study of the Rimini Canal Port, in the northeast of Italy, which is a degraded area of the city. This methodology is a tool that can be used in the future by decision makers (DMs) for the redevelopment of small port areas within similar urban contexts

    Comparison of decision-making approaches to prioritization of clean air action plans for sustainable development

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    Background: Clean air action plans have been prepared and are still being implemented in Turkey to control and prevent air pollution, and improve the air quality. The plans reveal a picture of the current situation and available inventory information. However, in order to implement the identified plans in real life, they need to be prioritized. This study aimed to identify and prioritize clean air action plans for Turkey using a framework of both fuzzy and crisp evaluations. Methods: In this study, priorities of the plans were identified and analyzed with a decision-making model. A three-step research methodology was provided. First, literature was reviewed regarding sustainable development and action plans. Second, in order to narrow and specify action plans, the nominal group technique (NGT) was implemented. Finally, fuzzy analytic hierarchy process (AHP) and best-worst method (BWM) surveys were applied to environmental engineers and experts working on sustainable development to prioritize the action plans. Results: It was revealed that heating dimension is considered as the most important criterion with the weight of 0.7469 in fuzzy AHP and 0.758 in BWM. AP1 with a weight of 0.3356 in fuzzy AHP and AP3 with a weight of 0.3289 in BWM were the most important sub-criteria, which are the plans for reducing coal use ranked at the forefront in reducing air pollution. Conclusion: According to the results, there is no significant difference in the priority ranking results. The results of fuzzy AHP and BWM are very similar. For example, traffic criterion has the best performance in both methods in the evaluation of decision makers. In addition, the main and sub-criteria with the lowest priority are the same in these two methods. Keywords: Air pollution, Cities, Decision making, Surveys and questionnaire
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