34,360 research outputs found

    Evaluating strategies for implementing industry 4.0: a hybrid expert oriented approach of B.W.M. and interval valued intuitionistic fuzzy T.O.D.I.M.

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    open access articleDeveloping and accepting industry 4.0 influences the industry structure and customer willingness. To a successful transition to industry 4.0, implementation strategies should be selected with a systematic and comprehensive view to responding to the changes flexibly. This research aims to identify and prioritise the strategies for implementing industry 4.0. For this purpose, at first, evaluation attributes of strategies and also strategies to put industry 4.0 in practice are recognised. Then, the attributes are weighted to the experts’ opinion by using the Best Worst Method (BWM). Subsequently, the strategies for implementing industry 4.0 in Fara-Sanat Company, as a case study, have been ranked based on the Interval Valued Intuitionistic Fuzzy (IVIF) of the TODIM method. The results indicated that the attributes of ‘Technology’, ‘Quality’, and ‘Operation’ have respectively the highest importance. Furthermore, the strategies for “new business models development’, ‘Improving information systems’ and ‘Human resource management’ received a higher rank. Eventually, some research and executive recommendations are provided. Having strategies for implementing industry 4.0 is a very important solution. Accordingly, multi-criteria decision-making (MCDM) methods are a useful tool for adopting and selecting appropriate strategies. In this research, a novel and hybrid combination of BWM-TODIM is presented under IVIF information

    Multicriteria optimization to select images as passwords in recognition based graphical authentication systems

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    Usability and guessability are two conflicting criteria in assessing the suitability of an image to be used as password in the recognition based graph -ical authentication systems (RGBSs). We present the first work in this area that uses a new approach, which effectively integrates a series of techniques in order to rank images taking into account the values obtained for each of the dimen -sions of usability and guessability, from two user studies. Our approach uses fuzzy numbers to deal with non commensurable criteria and compares two multicriteria optimization methods namely, TOPSIS and VIKOR. The results suggest that VIKOR method is the most applicable to make an objective state-ment about which image type is better suited to be used as password. The paper also discusses some improvements that could be done to improve the ranking assessment

    A robust fuzzy possibilistic AHP approach for partner selection in international strategic alliance

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    The international strategic alliance is an inevitable solution for making competitive advantage and reducing the risk in today’s business environment. Partner selection is an important part in success of partnerships, and meanwhile it is a complicated decision because of various dimensions of the problem and inherent conflicts of stockholders. The purpose of this paper is to provide a practical approach to the problem of partner selection in international strategic alliances, which fulfills the gap between theories of inter-organizational relationships and quantitative models. Thus, a novel Robust Fuzzy Possibilistic AHP approach is proposed for combining the benefits of two complementary theories of inter-organizational relationships named, (1) Resource-based view, and (2) Transaction-cost theory and considering Fit theory as the perquisite of alliance success. The Robust Fuzzy Possibilistic AHP approach is a noveldevelopment of Interval-AHP technique employing robust formulation; aimed at handling the ambiguity of the problem and let the use of intervals as pairwise judgments. The proposed approach was compared with existing approaches, and the results show that it provides the best quality solutions in terms of minimum error degree. Moreover, the framework implemented in a case study and its applicability were discussed

    A framework for the selection of the right nuclear power plant

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    Civil nuclear reactors are used for the production of electrical energy. In the nuclear industry vendors propose several nuclear reactor designs with a size from 35–45 MWe up to 1600–1700 MWe. The choice of the right design is a multidimensional problem since a utility has to include not only financial factors as levelised cost of electricity (LCOE) and internal rate of return (IRR), but also the so called “external factors” like the required spinning reserve, the impact on local industry and the social acceptability. Therefore it is necessary to balance advantages and disadvantages of each design during the entire life cycle of the plant, usually 40–60 years. In the scientific literature there are several techniques for solving this multidimensional problem. Unfortunately it does not seem possible to apply these methodologies as they are, since the problem is too complex and it is difficult to provide consistent and trustworthy expert judgments. This paper fills the gap, proposing a two-step framework to choosing the best nuclear reactor at the pre-feasibility study phase. The paper shows in detail how to use the methodology, comparing the choice of a small-medium reactor (SMR) with a large reactor (LR), characterised, according to the International Atomic Energy Agency (2006), by an electrical output respectively lower and higher than 700 MWe

    Development, test and comparison of two Multiple Criteria Decision Analysis(MCDA) models: A case of healthcare infrastructure location

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    When planning a new development, location decisions have always been a major issue. This paper examines and compares two modelling methods used to inform a healthcare infrastructure location decision. Two Multiple Criteria Decision Analysis (MCDA) models were developed to support the optimisation of this decision-making process, within a National Health Service (NHS) organisation, in the UK. The proposed model structure is based on seven criteria (environment and safety, size, total cost, accessibility, design, risks and population profile) and 28 sub-criteria. First, Evidential Reasoning (ER) was used to solve the model, then, the processes and results were compared with the Analytical Hierarchy Process (AHP). It was established that using ER or AHP led to the same solutions. However, the scores between the alternatives were significantly different; which impacted the stakeholders‟ decision-making. As the processes differ according to the model selected, ER or AHP, it is relevant to establish the practical and managerial implications for selecting one model or the other and providing evidence of which models best fit this specific environment. To achieve an optimum operational decision it is argued, in this study, that the most transparent and robust framework is achieved by merging ER process with the pair-wise comparison, an element of AHP. This paper makes a defined contribution by developing and examining the use of MCDA models, to rationalise new healthcare infrastructure location, with the proposed model to be used for future decision. Moreover, very few studies comparing different MCDA techniques were found, this study results enable practitioners to consider even further the modelling characteristics to ensure the development of a reliable framework, even if this means applying a hybrid approach

    Identifying and Prioritizing the Effective Criteria in Selecting Lean Six Sigma Improvement Projects in the Healthcare Sector

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    [EN] The main objective of this study was to identify and prioritize effective criteria in selecting Lean Six Sigma improvement projects in the healthcare and treatment sector in Iran. The present study was an applied research in terms of objective and a descriptive and analytical one according to the research methodology and data collection approach. The research statistical population included experts and managers with experience in the field of implementing the lean six sigma methodology in the field of healthcare and treatment in Iran. We used interviews and questionnaire tools to collect the data. The effective criteria were identified through reviewing previous research, which were then prioritized based on the experts’ opinions using the BWM method. According to the results, out of the six main dimensions and 20 criteria identified, the customer development dimension with a weight of 0.387 and the customer satisfaction criterion with a weight of 0.066 were determined as the most effective dimension and the most effective criterion, respectively. Accordingly, the directors of medical centers and organizations affiliated with the healthcare sector are recommended to pay special attention to these defined criteria of the customer development dimension to effectively implement the lean six sigma methodology and managing an effective customer relationship.Bazrkar, A.; Aramoon, V.; Aramoon, E. (2021). Identifying and Prioritizing the Effective Criteria in Selecting Lean Six Sigma Improvement Projects in the Healthcare Sector. WPOM-Working Papers on Operations Management. 12(2):41-55. https://doi.org/10.4995/wpom.15766OJS4155122Ahmed, S., Abd Manaf, N. H., & Islam, R. (2018). 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Total Quality Management & Business Excellence, 28(3-4), 405-426. https://doi.org/10.1080/14783363.2015.1090291Li, J., Wang, J. Q., & Hu, J. H. (2019). Multi-criteria decision-making method based on dominance degree and BWM with probabilistic hesitant fuzzy information. International Journal of Machine Learning and Cybernetics, 10(7), 1671-1685. https://doi.org/10.1007/s13042-018-0845-2Lizarelli, F. L., & Alliprandini, D. H. (2020). Comparative analysis of Lean and Six Sigma improvement projects: performance, changes, investment, time and complexity. Total Quality Management & Business Excellence, 31(3-4), 407-428. https://doi.org/10.1080/14783363.2018.1428087Maghsoodi, A. I., Mosavat, M., Hafezalkotob, A., & Hafezalkotob, A. (2019). Hybrid hierarchical fuzzy group decision-making based on information axioms and BWM: Prototype design selection. Computers & Industrial Engineering, 127, 788-804. https://doi.org/10.1016/j.cie.2018.11.018Malek, J., & Desai, T. N. (2019). 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