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This paper aims to describe an application of hybrid Multi Criteria Decision Making (MCDM) technique for the selection of wastewater treatment (WWT) technology for treating wastewater.

The proposed approach is based on Analytical Hierarchy Process (AHP) under fuzzy environment, Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) and hierarchy Grey Relation Analysis (GRA) techniques. Two models are proposed to evaluate the best WWT. The first model, Fuzzy Analytical Hierarchy Process (FAHP) is integrated with Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) technique. The second model, FAHP is integrated with hierarchy Grey Relation Analysis (GRA) technique. The Fuzzy Analytical Hierarchy Process (FAHP) is used to determine the weights of criteria and then ranking of the WWT technology is determined by PROMETHEE and GRA.

An efficient pair‐wise comparison process and ranking of alternatives can be achieved for WWT technology selection through the integration of FAHP and PROMETHEE, FAHP and GRA.

The paper highlights a new insight into MCDM techniques to select an optimum WWT technology selection for the paper manufacturing industry.

The purpose of this paper is to identify the dimensions of service quality in the context of Islamic higher education (IHE); explain the determinant dimensions of overall perceived service quality (PSQ) according to students; and explains the difference in the level of quality felt by students in each dimension based on gender, year of study and level of education of students in Indonesia.

A survey method from 384 questionnaires collected from students in four major cities in Indonesia; 378 questionnaires were declared valid for explanatory analysis using SEM-PLS and t-test.

The new model called Islamic Higher Education Service Quality (i-HESQUAL) with seven dimensions of quality that are considered important by students i.e. teaching capability and competence of academic staff (TCC), reliability of service (ROS), reputation of university (REP), responsiveness of employees (RES), empathy of employees (EMP), internalization of Islamic values (IIV) and library service support (LSS). The dimensions that influence the overall PSQ are the IIV and LSS. In addition, students based on the year of study have differences in assessing the dimensions of quality, namely the dimensions of TCC, ROS, IIV, LSS, while the level of education also has differences, especially on the dimensions of ROS, REP and LSS.

This research was only carried out at four public Islamic universities, for that there is a need for further research in the form of longitudinal studies with different geographical samples e.g. in the perspective of private universities to generalize research results.

The i-HESQUAL dimensions can be used by IHE managers to measure their performance according to students' perspectives. The two dimensions that determine the overall PSQ should be IHE's strategic advantages and the dimensions that do not affect the overall PSQ are feedback to identify weaknesses.

These findings contribute to PSQ research in the context of IHE, which operates on the values and culture that surrounds it (Islamic culture), while most of the previous research was conducted in the context of developed countries with a secular education system.

This paper aims to enable the analysts of reliability and safety system to assess the criticality and prioritize failure modes perfectly to prefer actions for controlling the risks of undesirable scenarios.

To resolve the challenge of uncertainty and ambiguous related to the parameters, frequency, non-detection and severity considered in the traditional approach failure mode effect and criticality analysis (FMECA) for risk evaluation, the authors used fuzzy logic where these parameters are shown as members of a fuzzy set, which fuzzified by using appropriate membership functions. The adaptive neuro-fuzzy inference system process is suggested as a dynamic, intelligently chosen model to ameliorate and validate the results obtained by the fuzzy inference system and effectively predict the criticality evaluation of failure modes. A new hybrid model is proposed that combines the grey relational approach and fuzzy analytic hierarchy process to improve the exploitation of the FMECA conventional method.

This research project aims to reflect the real case study of the gas turbine system. Using this analysis allows evaluating the criticality effectively and provides an alternate prioritizing to that obtained by the conventional method. The obtained results show that the integration of two multi-criteria decision methods and incorporating their results enable to instill confidence in decision-makers regarding the criticality prioritizations of failure modes and the shortcoming concerning the lack of established rules of inference system which necessitate a lot of experience and shows the weightage or importance to the three parameters severity, detection and frequency, which are considered to have equal importance in the traditional method.

This paper is providing encouraging results regarding the risk evaluation and prioritizing failures mode and decision-makers guidance to refine the relevance of decision-making to reduce the probability of occurrence and the severity of the undesirable scenarios with handling different forms of ambiguity, uncertainty and divergent judgments of experts.

The purpose of this paper is to explore a multi-criteria decision-making (MCDM) methodology to determine an optimal combination of process parameters that is capable of generating favorable dimensional accuracy and product quality during turning of commercially pure titanium (CP-Ti) grade 2.

The present paper recommends an optimal combination of cutting parameters with an aim to minimize the cutting force (F_c), surface roughness (R_a), machining temperature (T_m) and to maximize the material removal rate (MRR) after turning of CP-Ti grade 2. This was achieved by the simultaneous optimization of the aforesaid output characteristics (i.e. F_c, R_a, T_m, and MRR) using the MCDM-based TOPSIS method. Taguchi’s L₉ orthogonal array was used for conducting the experiments. The output responses (cutting force: F_c, surface roughness: R_a, machining temperature: T_m and MRR) were integrated together and presented in terms of a single signal-to-noise ratio using the Taguchi method.

The results of the proposed methodology depict that the higher MRR with desirable surface quality and the lower cutting force and machining temperature were observed at a combination of cutting variables as follows: cutting speed of 105 m/min, feed rate of 0.12 mm/rev and depth of cut of 0.5 mm. The analysis of variance test was conducted to evaluate the significance level of process parameters. It is evident from the aforesaid test that the depth of cut was the most significant process parameter followed by cutting speed.

The selection of an optimal parametric combination during the machining operation is becoming more challenging as the decision maker has to consider a set of distinct quality characteristics simultaneously. This situation necessitates an efficient decision-making technique to be used during the machining operation. From the past literature, it is noticed that only a few works were reported on the multi-objective optimization of turning parameters using the TOPSIS method so far. Thus, the proposed methodology can help the decision maker and researchers to optimize the multi-objective turning problems effectively in combination with a desirable accuracy.

The oil and gas industry is a crucial economic sector for both developed and developing economies. Delays in extraction and refining of these resources would adversely affect industrial players, including that of the host countries. Supplier selection is one of the most important decisions taken by managers of this industry that affect their supply chain operations. However, determining suitable suppliers to work with has become a phenomenon faced by these managers and their organizations. Furthermore, identifying relevant, critical and important criteria needed to guide these managers and their organizations for supplier selection decisions has become even more complicated due to various criteria that need to be taken into consideration. With limited works in the current literature of supplier selection in the oil and gas industry having major methodological drawbacks, the purpose of this paper is to develop an integrated approach for supplier selection in the oil and gas industry.

To address this problem, this paper proposes a new uncertain decision framework. A grey-Delphi approach is first applied to aid in the evaluation and refinement of these various available criteria to obtain the most important and relevant criteria for the oil and gas industry. The grey systems theoretic concept is adopted to address the subjectivity and uncertainty in human judgments. The grey-Shannon entropy approach is used to determine the criteria weights, and finally, the grey-EDAS (evaluation based on distance from average solution) method is utilized for determining the ranking of the suppliers.

To exemplify the applicability and robustness of the proposed approach, this study uses the oil and gas industry of Iran as a case in point. From the literature review, 21 criteria were established and using the grey-Delphi approach, 16 were finally considered. The four top-ranked criteria, using grey-Shannon entropy, include warranty level and experience time, relationship closeness, supplier’s technical level and risks which are considered as the most critical and influential criteria for supplier evaluation in the Iranian oil and gas industry. The ranking of the suppliers is obtained, and the best and worst suppliers are also identified. Sensitivity analysis indicates that the results using the proposed methodology are robust.

The proposed approach would assist supply chain practicing managers, including purchasing managers, procurement managers and supply chain managers in the oil and gas and other industries, to effectively select suitable suppliers for cooperation. It can also be used for other multi-criteria decision-making (MCDM) applications. Future works on applying other MCDM methods and comparing them with the results of this study can be addressed. Finally, broader and more empirical works are required in the oil and gas industry.

This study is among the first few studies of supplier selection in the oil and gas industry from an emerging economy perspective and sets the stage for future research. The proposed integrated grey-based MCDM approach provides robust results in supplier evaluation and can be used for future domain applications.

This paper investigates the risks involved in the Indian foodgrain supply chain (FSC) and proposes risk mitigation taxonomy to enable decision making.

This paper used failure mode and effect analysis (FMEA) for risk estimation. In the traditional FMEA, risk priority number (RPN) is evaluated by multiplying the probability of occurrence, severity and detection. Because of some drawbacks of the traditional FMEA, instead of calculating RPN, this paper prioritizes the FSC risk factors using fuzzy VIKOR. VIKOR is a multiple attribute decision-making technique which aims to rank FSC risk factors with respect to criteria.

The findings indicate that “technological risk” has a higher impact on the FSC, followed by natural disaster, communication failure, non-availability of procurement centers, malfunctioning in PDS and inadequate storage facility. Sensitivity analysis is performed to check the robustness of the results.

The outcomes of the study can help in deriving detailed risk mitigation strategy and risk mitigation taxonomy for the improved resilience of FSC.

Specifically, this research investigates the risks for foodgrains supply chain system for a developing country such as India, an area which has received limited attention in the present literature.

A direct correlation exists between waste disposal, disease spread and public health. This article systematically reviewed healthcare waste and its implication for public health. This review identified and described the associations and impact of waste disposal on public health.

This paper systematically reviewed the literature on waste disposal and its implications for public health by searching Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA), PubMed, Web of Science, Scopus and ScienceDirect databases. Of a total of 1,583 studies, 59 articles were selected and reviewed.

The review revealed the spread of infectious diseases and environmental degradation as the most typical implications of improper waste disposal to public health. The impact of waste includes infectious diseases such as cholera, Hepatitis B, respiratory problems, food and metal poisoning, skin infections, and bacteremia, and environmental degradation such as land, water, and air pollution, flooding, drainage obstruction, climate change, and harm to marine and wildlife.

Infectious diseases such as cholera, hepatitis B, respiratory problems, food and metal poisoning, skin infections, bacteremia and environmental degradation such as land, water, and air pollution, flooding, drainage obstruction, climate change, and harm to marine and wildlife are some of the public impacts of improper waste disposal.

Healthcare industry waste is a significant waste that can harm the environment and public health if not properly collected, stored, treated, managed and disposed of. There is a need for knowledge and skills applicable to proper healthcare waste disposal and management. Policies must be developed to implement appropriate waste management to prevent public health threats.

The Purpose of this study is to prove the possibility of developing low cost mechanical anti – lock braking system (ABS) for the passenger’s safety.

The design methodology of the proposed newer mechanical ABS comprises of two units, namely, the braking unit and wheel lock prevention unit. The braking unit actuates the wheel stopping as and when the driver applies the brake, whereas the wheel lock prevention unit initiates wheel release to prevent locking and subsequent slip/skidding. The brake pedal with master cylinder assembly and double-arm cylinder forms the braking unit, brake pad cylinder, movable brake pad, solenoid valve and dynamo forms the wheel lock prevention unit. The dynamo coupled with the rotor energises/de-energises the solenoid values to direct airflow for applying brake and release it, which makes the system less energy-dependent.

The braking unit aids in vehicle stops, by locking the disc with the brake pad actuated by a double-arm cylinder. The dynamo energises the solenoid valve to activate the brake pad cylinder piston for applying the brake on the disc. Instantaneously, on applying the brake the dynamo de-energises the solenoid to divert the pneumatic flow for retracting the brake pad thereby minimizing the braking torque. The baking torque reduction revives the wheel rotating and prevents slip/skidding.

Mechanical ABS preventing wheel lock by torque reduction principle is a novel method that has not been evolved so far. The system was designed with repair/replacement of the parts and subcomponents to support higher affordability on safety grounds.

This paper aims to address the magnetohydrodynamic boundary layer flow of hybrid mixture across a stretching surface under the influence of electric field.

The local similarity transformations are implemented to reformulate the governing partial differential equations into coupled non-linear ordinary differential equations of higher order. The numerical solutions are obtained for the simplified governing equations with the aid of finite difference technique.

The velocity, temperature and entropy generation are examined thoroughly for the effects of different budding parameters related to present analysis by means of graphs. It is obtained that owing to the effect of magnetic field along with slip factor, the fluid motion slowdown. However, the flow velocity enhances for the rising estimations of an electric field which tends to resolve sticky effects.

The three-dimensional plots are drawn to understand the nature of physical quantities. To ensure the precision, the obtained solutions are compared with the existing one for certain specific conditions. A good concurrence is observed between the proposed results and previously recorded outcomes.

The health-care industry has multiple stakeholders, with knowledge dispersed among clinicians, experts and patients and their families. As the adoption of health-care information technologies (HITs) depends on multiple factors, this study aims to uncover the motivators for adopting them.

The study considers 391 respondents, representing the health-care sector, to evaluate the motivators for adopting HITs for better-dispersed knowledge management. The authors analyze the responses using exploratory factor analysis (EFA) to identify the actual structure of the factors, followed by confirmatory factor analysis (CFA).

EFA categorized the factors into four classes: quality management; information sharing; strategic governance; and available technological infrastructure. CFA revealed that the strategic governance factor is most predictive of successfully adopting HITs that model the normative pressure of Institutional theory in health-care organizations. These results indicate that, along with considerations of finances, care quality and infrastructure, effective government involvement and policy-making are important for successful HIT adoption.

Results reveal that stakeholders’ motivating factors for HIT adoption in a developed economy like the United Arab Emirates are based on considering HITs as a knowledge management mechanism. These factors may help other nations in HIT implementation and drive valuable innovations in the health-care sector. This research presents the implications for health-care professionals and stakeholders in relation to adopting HITs and their role in knowledge flow for efficient care.

HITs offer an affordable and convenient platform for collaboration among diverse teams in the health-care sector. Apart from this, it helps in facilitating an interactive platform for knowledge creation and transfer for the benefit of users and providers.