83 research outputs found

    A New Integrated Fuzzy Multi-Criteria Decision Model for Performance Evaluation

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    The perspective of competition in the high technology industry has changed impressively over the last two decades and the indicators which can be defined as the traditional indicators of business performance are insufficient today. So we have identified a new set of financial and non-financial performance indicators that can be used by firms and then, we developed a business performance measurement model. There may be relations and dependencies among the dimensions of performance. For this reason, performance evaluation should be conducted in a holistic manner. In this study, a hybrid method, Equated Priority Values (EPV), has been used to reflect the outcomes of the most commonly used approaches, including the modified Fuzzy Logarithmic Least Squares Method (modified fuzzy LLSM), Chang’s Extent Analysis Method and Mikhailov’s Fuzzy Prioritization Approach. A real world application is carried out to illustrate how the model can be utilized. The application could be interpreted as demonstrating the effectiveness and feasibility of the proposed model

    Cost minimization for unstable concurrent products in multi-stage production line using queueing analysis

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    This research and resulting contribution are results of Assumption University of Thailand. The university partially supports financially the publication.Purpose: The paper copes with the queueing theory for evaluating a muti-stage production line process with concurrent goods. The intention of this article is to evaluate the efficiency of products assembly in the production line. Design/Methodology/Approach: To elevate the efficiency of the assembly line it is required to control the performance of individual stations. The arrival process of concurrent products is piled up before flowing to each station. All experiments are based on queueing network analysis. Findings: The performance analysis for unstable concurrent sub-items in the production line is discussed. The proposed analysis is based on the improvement of the total sub-production time by lessening the queue time in each station. Practical implications: The collected data are number of workers, incoming and outgoing sub-products, throughput rate, and individual station processing time. The front loading place unpacks product items into concurrent sub-items by an operator and automatically sorts them by RFID tag or bar code identifiers. Experiments of the work based on simulation are compared and validated with results from real approximation. Originality/Value: It is an alternative improvement to increase the efficiency of the operation in each station with minimum costs.peer-reviewe

    A Fuzzy AHP Model in Risk Ranking

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    The signification risks associated with construction projects need special attention from contractors to analyze and mange the risks. Risk management is the art and science of identifying, analyzing and responding to risk factors throughout the life cycle of the project and in the best interest of its objectives. In proposed model, we firstly identify risks in the construction projects and suitable criteria for evaluate risks and then structure the proposed AHP model. Finally we measure the significant risks in construction projects (SRCP) based on the project’s objectives by using fuzzy analytical hierarchy process (FAHP) technique. Keyword: Construction projects, Project Risk Management, Fuzzy AH

    Intelligent synthesis mechanism for deriving streaming priorities of multimedia content

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    We address the problem of integrating user preferences with network quality of service parameters for the streaming of media content, and suggest protocol stack configurations that satisfy user and technical requirements to the best available degree. Our approach is able to handle inconsistencies between user and networking considerations, formulating the problem of construction of tailor-made protocols as a prioritization problem, solvable using fuzzy programming

    Investigation of IoT applications in supply chain management with fuzzy hierarchical analysis

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    The IoT is currently growing rapidly and uses technologies such as smart barcode sensors, RFID, wireless communications, cloud computing, and more. The Internet of Things, in addition to being a revolutionary technology for all industries; has also demonstrated its potential in processes such as supply chain. Management, forecasting, and monitoring applications help managers improve the operational efficiency of their company distribution and increase transparency in their decisions. So more than ever, the benefits of using the Internet of Things are evident in the supply chain. The existence of comprehensive and valid information platforms is one of the requirements of supply chain management. Therefore, the most accurate use of integrated information devices such as Internet technology of objects in this part of the management of the organization is important. Coverage of this information accurately and in an instant facilitates matters and makes the process progress more transparent. To improve this process, cloud computing is used as a solution. In addition, other cloud computing capabilities can be used, such as facilitating object communication, integrating monitoring devices, and IoT storage, analyzing data, and paving the way for cyberspace to provide the customer with supply chain management. This requires a model that defines how Internet technology relates to objects, cloud computing, and supply chain management. The purpose of this study is to identify and prioritize IoT applications in the supply chain management sector with a multi-criteria decision-making approach. The results show that applications such as intelligent control and intelligent maintenance have the highest priorities

    Identifying and ranking key performance indicators in football clubs

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    Key performance indicators are actually measurable variables based on which we can measure the success rate of an organization in reaching defined key goals. In order to create key performance indicators, steps, and standards must be passed, each of which is of great importance. Based on how the key performance indicator (KPI) is defined and determined, it is possible to measure the performance of a person, department, process, campaign, or strategic goals of a brand. In fact, KPIs can be considered for different industries and for different levels of each business. Considering the importance of football clubs and their high social impact, the purpose of this research is to investigate these key performance indicators in order to grow and improve their comprehensive performance. In order to extract data, a literature review was used. Data refinement and prioritization were done using the fuzzy decision-making method, and the opinions of active experts in clubs and football players were used. The results show that indicators based on infrastructure development are among the most important indicators and should be given special attention

    Security and privacy analysis based on Internet of Things in the fourth industrial generation (Industry 4.0)

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    The connection of smart devices using the Internet has dramatically changed the way people live, and this concept has also been extended to the industrial sector. This practice not only provides more stable, faster, and safer communications but also makes it possible to realize the concept of the smart factory in the fourth industrial revolution. The Internet of Things uses a unique Internet Protocol to identify, control, and transmit data to individuals as well as databases. Data is collected through the Internet of Things, stored in cloud storage, and managed and calculated through analytical tools. Internet of Things security is a field of technology that focuses on protecting connected devices and networks in the Internet of Things (IoT). Ensuring the safety of networks with connected IoT devices is critical. Security in the Internet of Things includes a wide range of techniques, strategies, protocols, and measures aimed at mitigating the ever-increasing vulnerabilities of the Internet of Things in modern businesses. The simultaneous connection of objects also brings privacy concerns. For this reason, in this research, an effort has been made to examine and analyze the most important privacy requirements in the Internet of Things in digital businesses in Industry 4.0. In this regard, by using experts' opinions and literature review, privacy requirements were extracted and evaluated using fuzzy non-linear decision-making methodology. The results showed that acquired and intrinsic information has the highest importance

    A Fuzzy Group Prioritization Method for Deriving Weights and its Software Implementation

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    Several Multi-Criteria Decision Making (MCDM) methods involve pairwise comparisons to obtain the preferences of decision makers (DMs). This paper proposes a fuzzy group prioritization method for deriving group priorities/weights from fuzzy pairwise comparison matrices. The proposed method extends the Fuzzy Preferences Programming Method (FPP) by considering the different importance weights of multiple DMs . The elements of the group pairwise comparison matrices are presented as fuzzy numbers rather than exact numerical values, in order to model the uncertainty and imprecision in the DMs’ judgments. Unlike the known fuzzy prioritization techniques, the proposed method is able to derive crisp weights from incomplete and fuzzy set of comparison judgments and does not require additional aggregation procedures. A prototype of a decision tool is developed to assist DMs to implement the proposed method for solving fuzzy group prioritization problems in MATLAB. Detailed numerical examples are used to illustrate the proposed approach
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