158 research outputs found

    A STRUCTURED FRAMEWORK FOR RELIABILITY AND RISK EVALUATION IN THE MILK PROCESS INDUSTRY UNDER FUZZY ENVIRONMENT

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    This paper aims at proposing a novel integrated framework for studying reliability and risk issues of the curd unit in a milk process industry under uncertain environment. The considered plant’s complex series-parallel configuration was presented using the Petri Net (PN) modeling. The Fuzzy Lambda-Tau (λ-τ) approach was applied to study and analyze the reliability aspects of the considered plant. Failure dynamics of the curd unit has been analyzed with respect to increasing/ decreasing trends of the tabulated reliability indices. Availability of the considered plant shows a decreasing trend with an increase in spread values. For improving the system’s availability, a risk analysis was done to identify the most critical failure causes. Using the traditional FMEA approach, the FMEA sheet was generated on the basis of expert’s knowledge/experience. The Fuzzy-Complex Proportional Assessment (FCOPRAS) approach was applied within FMEA approach for identification of critical failure causes associated with different subsystem/components of the considered plant. In order to check the consistency of the ranking results, the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) was applied within the FCOPRAS approach. Ranking results are compared for checking consistency and robustness of critical failure causes related decision making which would be useful in designing the finest maintenance schedule for the considered curd unit.  Overheating/moisture lead to winding failure (MSCP5), visible sediment of milk jam in filter (MBFP3), improper quality of oil (H4), blade breakage (CTK4), wearing in gears (PFM11), and cylinder leakage (CFM7) were recognized as the most critical failure causes contributing to system unavailability. The analysis results were supplied to the maintenance manager for framing a suitable time-based maintenance intervals policy for the considered unit

    Resilience-enhancing solution to mitigate risk for sustainable supply chain-an empirical study of elevator manufacturing

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    As the complexity of supply chains increases, the enhancement of resilience for mitigating sustainable disruption risks in supply chains is an important issue. Quality function deployment (QFD) has been successfully applied in many domains to solve multicriteria decision-making (MCDM) problems. However, research on developing two houses of quality to connect sustainable supply chain disruption risks, resilience capacities, and resilience-enhancing features in elevator manufacturing supply chains by using the MCDM approach is lacking. This study aims to develop a framework for exploring useful decision-making by integrating the MCDM approach and QFD. By applying the framework, supply chain resilience can be improved by identifying the major sustainable risks and the key resilience to mitigate these risks. Important managerial insights and practical implications are obtained from the framework implementation in a case study of the elevator manufacturing industry. To strengthen resilience and thus mitigate key risks, the most urgent tasks are to connect the working site and the backstage to enhance product development and design and to share real-time job information. When these features are strengthened, agility, capacity, and visibility can be improved. Finally, unexpected events lead to changes in supplier delivery dates, and factors such as typhoon and lack of critical capacities/skilled employees with the greatest impact can be alleviated. This framework will provide an effective and pragmatic approach for constructing sustainable supply chain risk resilience in the elevator manufacturing industry.</p

    Uncertain Multi-Criteria Optimization Problems

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    Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

    Multi-Objective and Multi-Attribute Optimisation for Sustainable Development Decision Aiding

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    Optimization is considered as a decision-making process for getting the most out of available resources for the best attainable results. Many real-world problems are multi-objective or multi-attribute problems that naturally involve several competing objectives that need to be optimized simultaneously, while respecting some constraints or involving selection among feasible discrete alternatives. In this Reprint of the Special Issue, 19 research papers co-authored by 88 researchers from 14 different countries explore aspects of multi-objective or multi-attribute modeling and optimization in crisp or uncertain environments by suggesting multiple-attribute decision-making (MADM) and multi-objective decision-making (MODM) approaches. The papers elaborate upon the approaches of state-of-the-art case studies in selected areas of applications related to sustainable development decision aiding in engineering and management, including construction, transportation, infrastructure development, production, and organization management

    VIKOR Technique:A Systematic Review of the State of the Art Literature on Methodologies and Applications

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    The main objective of this paper is to present a systematic review of the VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) method in several application areas such as sustainability and renewable energy. This study reviewed a total of 176 papers, published in 2004 to 2015, from 83 high-ranking journals; most of which were related to Operational Research, Management Sciences, decision making, sustainability and renewable energy and were extracted from the “Web of Science and Scopus” databases. Papers were classified into 15 main application areas. Furthermore, papers were categorized based on the nationalities of authors, dates of publications, techniques and methods, type of studies, the names of the journals and studies purposes. The results of this study indicated that more papers on VIKOR technique were published in 2013 than in any other year. In addition, 13 papers were published about sustainability and renewable energy fields. Furthermore, VIKOR and fuzzy VIKOR methods, had the first rank in use. Additionally, the Journal of Expert Systems with Applications was the most significant journal in this study, with 27 publications on the topic. Finally, Taiwan had the first rank from 22 nationalities which used VIKOR technique

    AN EXTENDED SINGLE-VALUED NEUTROSOPHIC AHP AND MULTIMOORA METHOD TO EVALUATE THE OPTIMAL TRAINING AIRCRAFT FOR FLIGHT TRAINING ORGANIZATIONS

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    Aircraft’s training is crucial for a flight training organization (FTO). Therefore, an important decision that these organizations should wisely consider the choice of aircraft to be bought among many alternatives. The criteria for evaluating the optimal training aircraft for FTOs are collected based on the survey approach. Single valued neutrosophic sets (SVNS) have the degree of truth, indeterminacy, and falsity membership functions and, as a special case, neutrosophic sets (NS) deal with inconsistent environments. In this regard, this study has extended a single-valued neutrosophic analytic hierarchy process (AHP) based on multi-objective optimization on the basis of ratio analysis plus a full multiplicative form (MULTIMOORA) to rank the training aircraft as the alternatives. Moreover, a sensitivity analysis is performed to demonstrate the stability of the developed method. Finally, a comparison between the results of the developed approach and the existing approaches for validating the developed approach is discussed. This analysis shows that the proposed approach is efficient and with the other methods

    Analysis of Decision Support Systems of Industrial Relevance: Application Potential of Fuzzy and Grey Set Theories

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    The present work articulates few case empirical studies on decision making in industrial context. Development of variety of Decision Support System (DSS) under uncertainty and vague information is attempted herein. The study emphases on five important decision making domains where effective decision making may surely enhance overall performance of the organization. The focused territories of this work are i) robot selection, ii) g-resilient supplier selection, iii) third party logistics (3PL) service provider selection, iv) assessment of supply chain’s g-resilient index and v) risk assessment in e-commerce exercises. Firstly, decision support systems in relation to robot selection are conceptualized through adaptation to fuzzy set theory in integration with TODIM and PROMETHEE approach, Grey set theory is also found useful in this regard; and is combined with TODIM approach to identify the best robot alternative. In this work, an attempt is also made to tackle subjective (qualitative) and objective (quantitative) evaluation information simultaneously, towards effective decision making. Supplier selection is a key strategic concern for the large-scale organizations. In view of this, a novel decision support framework is proposed to address g-resilient (green and resilient) supplier selection issues. Green capability of suppliers’ ensures the pollution free operation; while, resiliency deals with unexpected system disruptions. A comparative analysis of the results is also carried out by applying well-known decision making approaches like Fuzzy- TOPSIS and Fuzzy-VIKOR. In relation to 3PL service provider selection, this dissertation proposes a novel ‘Dominance- Based’ model in combination with grey set theory to deal with 3PL provider selection, considering linguistic preferences of the Decision-Makers (DMs). An empirical case study is articulated to demonstrate application potential of the proposed model. The results, obtained thereof, have been compared to that of grey-TOPSIS approach. Another part of this dissertation is to provide an integrated framework in order to assess gresilient (ecosilient) performance of the supply chain of a case automotive company. The overall g-resilient supply chain performance is determined by computing a unique ecosilient (g-resilient) index. The concepts of Fuzzy Performance Importance Index (FPII) along with Degree of Similarity (DOS) (obtained from fuzzy set theory) are applied to rank different gresilient criteria in accordance to their current status of performance. The study is further extended to analyze, and thereby, to mitigate various risk factors (risk sources) involved in e-commerce exercises. A total forty eight major e-commerce risks are recognized and evaluated in a decision making perspective by utilizing the knowledge acquired from the fuzzy set theory. Risk is evaluated as a product of two risk quantifying parameters viz. (i) Likelihood of occurrence and, (ii) Impact. Aforesaid two risk quantifying parameters are assessed in a subjective manner (linguistic human judgment), rather than exploring probabilistic approach of risk analysis. The ‘crisp risk extent’ corresponding to various risk factors are figured out through the proposed fuzzy risk analysis approach. The risk factor possessing high ‘crisp risk extent’ score is said be more critical for the current problem context (toward e-commerce success). Risks are now categorized into different levels of severity (adverse consequences) (i.e. negligible, minor, marginal, critical and catastrophic). Amongst forty eight risk sources, top five risk sources which are supposed to adversely affect the company’s e-commerce performance are recognized through such categorization. The overall risk extent is determined by aggregating individual risks (under ‘critical’ level of severity) using Fuzzy Inference System (FIS). Interpretive Structural Modeling (ISM) is then used to obtain structural relationship amongst aforementioned five risk sources. An appropriate action requirement plan is also suggested, to control and minimize risks associated with e-commerce exercises
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