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Presents a methodology for calculating the availability of a refining system in a sugar plant. The refining system consists of a number of subsystems including a filter, heating sulphitor and clarifier, each having series and parallel elements. The mathematical modelling of the failures and repairs of the subsystems is based on the birth and death process and the use of Chapman‐Kolmogorov equations. During the analysis of an actual sugar plant, it has been found that the clarifier unit of the refining system is the most critical component and requires immediate corrective action. Other critical components included are: filter and sulphonation units.

The purpose of this paper is to exploit the fullest potential and capability of different non-traditional machining (NTM) processes, it is often recommended to operate them at their optimal parametric combinations. There are several mathematical tools and techniques that have been effectively deployed for identifying the optimal parametric mixes for the NTM processes. Amongst them, grey relational analysis (GRA) has become quite popular due to its sound mathematical basis, ease to implement and apprehensiveness for multi-objective optimization of NTM processes.

In this paper, GRA is integrated with fuzzy logic to present an efficient technique for multi-objective optimization of three NTM processes (i.e. abrasive water-jet machining, electrochemical machining and ultrasonic machining) while identifying their best parametric settings for enhanced machining performance.

The derived results are validated with respect to technique for order preference by similarity to ideal solution (TOPSIS), and analysis of variance is also performed so as to identify the most significant control parameters in the considered NTM processes.

This grey-fuzzy logic approach provides better parametric combinations for all the three NTM processes with respect to the predicted grey-fuzzy relational grades (GFRG). The developed surface plots help the process engineers to investigate the effects of various NTM process parameters on the predicted GFRG values.

The adopted approach can be applied to various machining (both conventional and non-conventional) processes for their parametric optimization for achieving better response values.

This paper presents an analysis of the problem of Assembly Facility Assignment in a Mixed Model Assembly Line. Poisson arrivals and exponential service time distribution have been assumed. On the basis of the analysis presented it is possible to choose a particular facility on economic considerations, further, optimum service rate for such facilities has also been evaluated.

The current trend of modern industry is to use machineries which rotate at high speed along with the capability of carrying heavy rotor loads. This paper aims at static thermal analysis of two different profiles of non-circular journal bearings – a true elliptical bearing and orthogonal bearing.

The Reynolds equation has been solved through finite difference method to compute the oil film pressure. Parabolic temperature profile approximation technique has been used to solve the energy equation and thus used for computation of various bearing performance characteristics such as thermo-hydrodynamic oil film pressure, temperature, load capacity, Sommerfeld number and power loss characteristics across the bearing. The effect of ellipticity ratio on the bearing performance characteristics has also been obtained for both the elliptical and vertical offset bearing using three different commercially available grades of oil (Hydrol 32, 68 and 100).

It has been observed that the thermo-hydrodynamic pressure and temperature rise of the oil film is less in orthogonal bearing as compared to the true elliptical bearing for same operating conditions. The effect of ellipticity ratio of non-circularity on bearing performance parameters have been observed to be less in case of elliptical bearing as compared to orthogonal bearing. It has been concluded that though the rise in oil film temperature is high for true elliptical bearing, but still it should be preferred over orthogonal profile under study, as it has comparably good load-carrying capacity.

The performance parametric analysis will help the designers to select such kind of non-circular journal bearing for various applications.

Based on the Natural resource-based view (NRBV), this study aims to analyze the association between the Sustainable Development Goals related to Gender Equality, Decent Work, Innovation, and Climatic Action in the Food Industry.

A quantitative study is adopted based on the 2019 World Bank Enterprise Survey microdata. The database includes 1,242 food enterprises from 16 European Union countries. We applied logistic regression with cluster robust standard errors.

Despite global efforts to promote decent work and gender equity, the anticipated results have not yet been achieved, suggesting varying performance in different contexts. Food firms, characterized by significant environmental impacts and seasonal tasks, employ diverse Human Resource Management (HRM) strategies based on whether they pursue innovation or environmental objectives. Grounded in the NRBV, our findings underscore the importance of investing in qualified workers and offering attractive wages to meet environmental goals, as well as providing stable contracts for female workers. The NRBV framework also highlights the crucial role of product and process innovations, whether green or not, in achieving climate action objectives.

European policies must be adapted to the human resources characteristics in the food industry, providing specific training on environmental and innovation issues and contributing to more work stability and gender equality.

Our study applies the NRBV to analyze how human resources and product/process innovations can boost environmental preservation in an industry characterized by strong environmental impacts, seasonal tasks, and financial constraints.

The purpose of this study is to better understand consumers’ overall perceptions of “being green” in an attempt to address the green attitude–behavior gap.

This study features a qualitative study that uses a projective technique to tap into consumers’ underlying perceptions of those who purchase green products. A follow-up, quantitative study tests the mediation effects of perceived judgment and self-congruity perceptions on the green attitude–behavior gap.

The key finding of the first study suggests that consumers tend to “judge” others based on their degree of greenness. The second study confirmed both perceptions of judgment and self-congruity mediate the relationship between green attitudes and behaviors.

This study explores the elusive green attitude–intention gap with both a qualitative and quantitative approach. Perceived consumer judgment emerges as a new variable to consider in better understanding green consumer behaviors.

Articulation errors substantially reduce speech intelligibility and the ease of spoken communication. Moreover, the articulation learning process that speech-language pathologists must provide is time consuming and expensive. The purpose of this paper, to facilitate the articulation learning process, is to develop a computer-aided articulation learning system to help subjects with articulation disorders.

Facial animations, including lip and tongue animations, are used to convey the manner and place of articulation to the subject. This process improves the effectiveness of articulation learning. An interactive learning system is implemented through pronunciation confusion networks (PCNs) and automatic speech recognition (ASR), which are applied to identify mispronunciations.

Speech and facial animations are effective for assisting subjects in imitating sounds and developing articulatory ability. PCNs and ASR can be used to automatically identify mispronunciations.

Future research will evaluate the clinical performance of this approach to articulation learning.

The experimental results of this study indicate that it is feasible for clinically implementing a computer-aided articulation learning system in learning articulation.

This study developed a computer-aided articulation learning system to facilitate improving speech production ability in subjects with articulation disorders.

The most simple equivalent frame system with reduced degrees of freedom is proposed for handling multi‐story multi‐bay infilled frames. The system is composed of homogenized continuum for the reinforced concrete members braced with unilateral diagonal struts for each bay, which are only activated in compression. Identification of the equivalent system characteristics and nonlinear material properties are accomplished from the concepts of inverse analysis approach along with statistical tests of hypotheses is employed to establish the appropriate filtering scheme and the proper accuracy tolerance. The suggested system allows for nonlinear finite element static and dynamic analysis of sophisticated infilled reinforced concrete frames. Sensitivity analysis is undertaken to check the suitability of the proposed system to manipulate various structural applications.

The purpose of this paper is to present a technique for analyzing the behavior of an industrial system utilizing vague, imprecise, and uncertain data. The synthesis unit of a urea plant situated in northern part of India has been considered to demonstrate the proposed approach. Sensitivity analysis of system's behaviour has also been done in it.

In the proposed approach, traditional Lambda‐Tau technique is used to analyze the behavior of a complex repairable synthesis unit of a fertilizer industry up to a desired degree of accuracy. This technique has been demonstrated by computing eight well‐known reliability indices which are used for behaviour analysis of the considered system in a more promising way.

The study of analysis of reliability, availability, maintainability etc can help in increasing the production and quality of synthesis. To ensure the system performance throughout its service life, it is necessary to set up proper maintenance, planning and control which can be done after studying the variation of reliability, availability with respect to time. Thus, it may be a more useful analysis tool to access the current system condition and involved uncertainties. The present paper suggested an approach to improve the system's performance.

The paper suggests a technique for analyzing the stochastic behavior of an industrial subsystem by computing eight well‐known reliability indices in the form of fuzzy membership function. The benefits for the methodology include the ability to model and deal with highly complex system as fuzzy sets can deal easily with approximations and it helps in improving and handling the uncertainties and possibilities.

In the current exploration, the machining of a Nimonic 90 superalloy material was carried out in a die-sinking electric discharge machine. Experimentation was performed to investigate the impact of three input machining factors – current (I), pulse on time (T_on) and pulse off time (T_off) – on various response characteristics such as material removal rate (MRR), surface roughness (R_a) and electrode wear rate (EWR).

A Taguchi L9 design and ANOVA were used to assess machine response characteristics. The study also involved a grey relational analysis (GRA) multi-objective technique of optimization.

For single-objective performance, the most appropriate machining factors for achieving the best performance were attained as: MRR (I = 20 A, T_on = 200 µs and T_off = 45 µs), R_a (I = 14 A, T_on = 100 µs and T_off = 25 µs) and EWR (I = 17 A, T_on = 150 µs and T_off = 45 µs). The proposed grey relational approach provided the optimal settings (i.e. 14 A I, 100 µs T_on and 25 µs T_off) for the variables used to calculate the predicted and experimental results. Also, a confirmation test indicated that the final experimental grey relational grade value was enhanced when the experimentation was performed at optimal setting.

To the best of the authors’ knowledge, the present work is the first to examine the proposed machining variables (i.e. current, pulse on time and pulse off time) in relation to the optimization technique of GRA for a Nimonic 90 alloy using a die-sinking electric discharge machining method.