Application of fuzzy MOORA method in the design and fabrication of an automated hammering machine

Purpose In most developing countries riveting, upset forging and punching operations among others are performed using manual hammering technique. The use of the manual method increases production time and reduces efficiency. The use of the manual approach is predominantly due to the high cost of imported automated hammering machines (AHM) which the majority of the end-users are incapable of acquiring. The purpose of this paper, therefore, is to produce an AHM that is affordable using an effective material selection methodology in the design and fabrication process. Design/methodology/approach The material selection methodology proposed is the fuzzy multi-objective optimisation on the basis of the ratio analysis (MOORA) method. The tool was used to evaluate and determine the optimum material for the major of the components of the AHM from amongst alternative materials while considering several decision criteria. A case study of the shaft was applied to demonstrate the suitability of the proposed technique. The AHM components design is then carried out and machine fabricated and tested to ascertain performance effectiveness. Findings The result of the fuzzy MOORA evaluation showed that alloy steel is the optimal material for the shaft. The fuzzy MOORA approach was compared with the fuzzy Vlsekriterijumska Optimizacija Ikompromisno Resenje (VIKOR) and fuzzy grey relational analysis (GRA) methods to validate the proposed method. The fuzzy MOORA method produces completely the same result with the fuzzy VIKOR and fuzzy GRA methods. The machine was then designed, constructed and tested and found to be effective for the purpose of the design. Originality/value This is significant as no such study has been published by any other researcher to the best of our knowledge in this area.

Integrated Decision-Making Approach Based on SWARA and GRA Methods for the Prioritization of Failures in Solar Panel Systems under Z-Information

Encountering a problem or error in the final stages of providing products or services increases costs and delays scheduling. The key task is to ensure quality and reliability in the early stages of the production process and prevent errors from occurring from the beginning. Failure mode and effect analysis (FMEA) is one of the tools for identifying potential problems and their impact on products and services. The conventional FMEA technique has been criticized extensively due to its disadvantages. In this study, the concepts of uncertainty and reliability are considered simultaneously. The processes of weighting risk factors, prioritizing failures by using the stepwise weight assessment ratio analysis (SWARA)–gray relational analysis (GRA) integrated method based on Ζ-number theory and complete prioritization of failures are implemented. Crucial management indices, such as cost and time, are considered in addition to severity, occurrence and detection factors along with assigning symmetric form of the weights to them. This, in turn, increases the interpretability of results and reduces the decision-maker’s subjectivity in risk prioritization. The developed model is implemented on solar panel data with 19 failure modes determined by the FMEA team. Results show that the proposed approach provides a more complete and realistic prioritization of failures than conventional FMEA and fuzzy GRA methods do.

Fuzzy AHP-GRA approach to evaluating energy sources: a case of Turkey

Purpose Since the demand for energy has dramatically increased in the countries which have fast-growing population and economy, they have faced with a critical problem of how to evaluate a set of potential energy sources (i.e. nuclear, natural gas, bio, geothermal, hydro, wind and solar) and choose the ultimate energy source for their needs. On the other hand, this critical problem turns into a multiple-criteria decision-making (MCDM) in the presence of a set of energy source alternatives and evaluation criteria. In literature, there are many MCDM methods introduced to solve for different kinds of problems. The purpose of this paper is to present an integrated approach for evaluating energy sources using fuzzy AHP and GRA, with a case for Turkey. Design/methodology/approach In this paper, the analytic hierarchy process (AHP) and grey relational analysis (GRA) methods are used because of their advantages for similar problems. On the other hand, due to the fact that the conventional AHP by a nine-point scale and GRA method using a scale with crisp values can be unable to handle to capture the right judgments of a decision-maker(s), to reflect the vagueness and uncertainty on the judgments of a decision-maker, the fuzzy logic is integrated with the AHP and GRA. Findings The contributions of the paper to the literature are given in two dimensions as follows: it presents an integrated approach for complex decision processes with subjective data or vague information; the proposed approach, the fuzzy AHP-GRA method for energy source selection, is unique for the related problem in literature. The results of the proposed model from the case of Turkey will help practitioners and experts of how to apply it to the similar problems in the field of energy management. Research limitations/implications In short, in this paper, an integrated approach is proposed through the fuzzy AHP and the fuzzy GRA methods. As the fuzzy AHP is used to determine the weights of evaluation criteria, the fuzzy GRA is used to rank energy source alternatives. Practical implications In addition, a case study for Turkey is presented to show the applicability of the proposed approach for potential practitioners who are authority in the field of energy in public and private sectors. Social implications On the other hand, the proposed approach, the fuzzy AHP-GRA for energy source selection can also be an intelligent tool for public and private energy companies in Turkey, as well as others in the world. Originality/value On the other hand, in this paper, to the best of the authors’ knowledge, the study contributes to the literature that the first time, they use the fuzzy alpha-cut AHP and GRA in fuzzy environment for energy source evaluation problem.

INFORMATION SECURITY ASSESSMENT BASED ON MACHINE LEARNING TECHNOLOGY-FUZZY-GRA-AHP

With the advent of the information age, information security has become an urgent problem to be solved. Various application and platforms have not only brought convenience to people, but also brought hidden dangers - information security risks. This paper uses some of the machine learning technology - fuzzy computing and gray relation analysis (GRA), to analyze data of the three major video platforms of China, and takes the information security level as a new criterion to conduct the evaluation of their performance. An assessment model is constructed based on machine learning technology, namely the combination of fuzzy computing and GRA and analytic hierarchy process (AHP). Conclusions can be drawn as follows. First, consumers’ perception of video platform information security level is constantly being strengthened. Second, information security risks are affecting consumers' choice decisions about video platforms, and the weights will continue to increase. Third, video platforms are paying more attention to information security construction.