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This paper aims to investigate the effect of fly ash reinforcement ratio (Rr) and sintering temperature (T) on the transverse rupture strength (TRS), hardness and density of fly ash reinforced bronze-based composite materials by using multi-objective Taguchi technique, analysis of variance (ANOVA) and regression analysis.

The bronze-based composite materials containing 5, 10 and 15 Wt.% fly ashes were prepared by using spark plasma sintering carried out under a pressure of 35 MPa, at 750, 800 and 850 °C for 3 min. Sintering temperature and fly ash reinforcement ratio were considered as input parameters; the TRS, hardness and density were considered as output parameters. Experiments were designed according to Taguchi L9 orthogonal array. Multi signal-to-noise ratio (MSNR) was computed to define the optimal process parameters. ANOVA was conducted to detect the importance of the input parameters for the process performance. Moreover, the linear model was developed for predicting the performance parameters by using regression analysis.

Fly ash can be a good alternative as reinforcement to reduce the cost for composite materials. Optimal process parameters had obtained 850°C sintering temperature and 5 per cent reinforcement ratio by using multi-objective Taguchi technique. The per cent contributions of the control factors on the performance parameters had obtained sintering temperature (95.78 per cent) and fly ash reinforcement ratio (3.00 per cent) with ANOVA. The obtained results indicate that the sintering temperature was found to be the dominant factor among controllable factors. However, the reinforcement ratio showed an insignificant effect.

It has been indicated that multi-objective Taguchi technique and regression analysis are effective and powerful tools in modeling and simultaneous optimization of quality characteristics for composite materials.

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.

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.

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.

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.

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.

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.

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.

In this paper, two popular multiple-criteria decision-making (MCDM) methods with hesitant fuzzy logic approach; hesitant fuzzy analytic hierarchy process (hesitant F-AHP) and hesitant fuzzy the technique for order preference by similarity to ideal solution (HF-TOPSIS) are integrated as HF-AHP-TOPSIS to evaluating a set of enterprise resource planning (ERP) alternatives and rank them by weight to reach to the ultimate one that satisfies the needs and expectations of a company.

Selecting the best ERP software package among the rising number of the options in market has been a critical problem for most companies for a long time because of the reason that an improper ERP software package might lead to many issues (i.e. time loss, increased costs and a loss of market share). On the other hand, finding the best ERP alternative is a comprehensive MCDM problem in the presence of a set of alternatives and several potentially competing quantitative and qualitative criteria.

In this integrated approach, the hesitant F-AHP is used to determine the criteria weights, as the hesitant F-TOPSIS is utilized to rank ERP package alternatives. The proposed approach was also validated in a numerical example that has five ERP package alternatives and 12 criteria by three decision-makers in order to show its applicability to potential readers and practitioners.

If the number of the alternatives and criteria are dramatically increased beyond reasonable numbers, the reaching to final solution will be so difficult because of the great deal of fuzzy based calculations. Therefore, the number of criteria and alternatives should be at reasonable numbers.

The proposed approach was also validated in a illustrated example with the five ERP package options and 12 criteria by the three decision-makers in order to show its applicability to potential readers and practitioners.

Furthermore, in literature, to the best of our knowledge, the authors did not come cross any work that integrates the HF-AHP with the HF-TOPSIS for ERP software package selection problem.