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The purpose of this paper is performance enhancement of ferrite-assisted synchronous reluctance (FASR) motor using multi-objective differential evolution (MODE) algorithm, considering the significant geometric design parameters.

This work illustrates the optimization of FASR motor using MODE algorithm to enhance the performance of the motor considering barrier angular positions, magnet height, magnet axial length, flux barrier angles of the rotor and air gap length. In the optimization routine to determine the performance parameters, generalized regression neural network-based interpolation is used. The results of MODE are validated with multi-objective particle swarm optimization algorithm and multi-objective genetic algorithm.

The design optimization procedure developed in this work for FASR motor aims at achieving multiple objectives, namely, average torque, torque ripple and efficiency. With multiple objectives, it is essential to give the designer the tradeoff between different objectives so as to arrive at the best design suitable for the application. The results obtained in this work justify the application of the MODE approach for FASR motor to determine the various feasible solutions within the bounds of the design.

Analysis, design and optimization of synchronous reluctance motor has been explored in detail to establish its potential for variable speed applications. In recent years, the focus is toward the electromagnetic design of hybrid configurations such as FASR motor. It is in this preview this work aims to achieve optimal design of FASR motor using multi-objective optimization approach.

The results of this work will supplement and encourage the application of FASR motor as a viable alternate for variable speed drive applications. In addition, the application of MODE to arrive at better design solutions is demonstrated.

The approach presented in this work focuses on obtaining enhanced design of FASR motor considering average torque, torque ripple and efficiency as performance measures. The posteriori analysis of optimization provides an insight into the choice of parameters involved and their effects on the design of FASR motor. The efficacy of the optimization routine is justified in comparison with other multi-objective algorithms.

The purpose of this paper is to propose a multi-objective particle swarm optimization (MOPSO) algorithm based design optimization of Brushless DC (BLDC) motor with a view to mitigate cogging torque and enhance the efficiency.

The suitability of MOPSO algorithm is tested on a 120 W BLDC motor considering magnet axial length, stator slot opening and air gap length as the design variables. It avails the use of MagNet 7.5.1, a Finite Element Analysis tool, to account for the geometry and the non-linearity of material for assuaging an improved design framework and operates through the boundaries of generalized regression neural network (GRNN) to advocate the optimum design. The results of MOPSO are compared with Multi-Objective Genetic Algorithm and Non-dominated Sorting Genetic Algorithm-II based formulations for claiming its place in real world applications.

A MOPSO design optimization procedure has been enlivened to escalate the performance of the BLDC motor. The optimality in design has been out reached through minimizing the cogging torque, maximizing the average torque and reducing the total losses to claim an increase in the efficiency. The results have been fortified in well-distributed Pareto-optimal planes to arrive at trade-off solutions between different objectives.

The rhetoric theory of multi objective formulations has been reinforced to provide a decisive solution with regard to the choice of the design obtained from Pareto-optimal planes.

The incorporation of a larger number of design variables together with an orientation to thermal and vibration analysis will still go a long way in bringing on board new dimensions to the fold of optimality in the design of BLDC motors.

The proposal offers a new perspective to the design of BLDC motor in the sense it be-hives the facility of a swarm based approach to optimize the parameters in order that it serves to improve its performance. The results of a 120 W motor in terms of lowering the losses, minimizing the cogging torque and maximizing the average torque emphasize the benefits of the GRNN based multi-objective formulation and establish its viability for use in practical applications.

This study aims to offer an overview of the models of clinical care of the patients with dual disorders in India.

All the members of the Dual Diagnosis India Network (DDIN) who shared the clinical care delivery at their center were invited to share the details of their model. In addition, an invite was also sent to those members who could not attend the online session but were interested in contributing the required information about their model. The information shared by the respondents was collated. The different models were then categorized based on their features.

Following the categorization of the clinical care services organization across different settings, five different models emerged. These were specialized dual diagnosis clinic; services for dual disorders offered as substance use disorder (SUD) treatment services within general psychiatry care; services for dual disorders in general psychiatry care; services for dual disorders offered as SUD treatment services separated from general psychiatry care; and services for dual disorders offered in general psychiatry services combined with exclusive SUD treatment services.

Currently, there is limited literature on models of dual disorders from the low- and middle-income countries. The authors believe that the documentation of these models from India shall be of help while setting up services for dual disorders in other health-care settings. This study can be a valuable resource for making informed choices while setting up new services.

The purpose of this paper is to persuade a hybrid framework, which can be used to assess the performance of various supply chains and can be further used to segregate supply chains concerning critical KPMs. The KPMs have been selected in the COVID-19 pandemic condition.

A real case of e-commerce is presented to illustrate the working of the proposed framework comprising a hybrid methodology of BWM and Fuzzy TOPSIS to measure the performance of the e-commerce supply chains by identifying the critical key performance metrics (KPMs) and measuring the performance of the considered supply chains against these.

The proposed framework is illustrated using real-time data from experts, collected through interviews and discussions. It is found that rate of return on investment (SCPM 27), flexibility of service systems to meet particular customer needs (SCPM 23) and supplier lead time against industry norm (SCPM 33) are significantly weighed in assessing performance of the selected supply chains, with weights 0.07764, 0.06863 and 0.0547, respectively. Amazon and Flipkart are seen to stand out among the other supply chains taken for the present study with closeness coefficients as 0.945 and 0.516, respectively.

The contemporary world has seen the drastic attack of COVID-19 on many firms worldwide, and hence measuring the performance of the supply chains has become necessary so as to understand the critical factors affecting performance, their relative importance and the firm's relative standings. There have been studies in the recent past where researchers worked on similar motives to generate a framework to measure performance of supply chains, but it is seen that the methodologies lack flexibility with respect to effectively handling large data, uncertainty in human emotions, consistency, etc. This is where the current study stands out in effectively measuring the performance of supply chains so as to aid many firms affected by the pandemic.

Smart devices like fully automated smart refrigerators can simplify customers' shopping processes. However, despite the advantages, such as saving time and effort, these devices are rarely used in private households. Therefore, this study aims to investigate the influence of various aspects on the usage intention of automated purchase processes and how these can be established in the long term.

For examining the given topic, an online experiment was conducted in which the experimental factors automation (not given vs given) and product type (utilitarian vs hedonic) were systematically manipulated.

The findings show a decreasing usage intention for automated shopping processes and no significant results for the utilitarian and hedonic product types. In addition, trust and behavioural control mediate the effect of automation on usage intention, and this effect is further moderated by inherent novelty seeking.

The study investigates the usage intention of automated buying processes in a business-to-consumer retail context and highlights the importance of trust and behavioural control. Retailers offering automated buying processes should further focus on customers that seek novelty. In general, this study offers new insights into establishing automated buying processes in the long term.

The purpose of this paper is to conceptualise and develop a scale for measuring employees’ perception on the sustainability of service organisations. With several companies adopting sustainability initiatives, it is prudent to measure the sustainability performance of those companies. Given the multidisciplinary nature of the sustainability measures and its associated challenges, this paper attempts to develop a scale to measure employees’ perception of sustainability of an organisation.

A structured questionnaire was developed and 977 samples were collected based on snowball sampling method. For scale development, this study randomised 586 samples to conduct exploratory factor analysis (EFA) and used the remaining samples for validation using confirmatory factor analysis (CFA).

The existing literature on sustainability focusses on three dimensions, namely, economic, social and environmental sustainability measures. This paper explored the similarities of the three dimensions to serve as critical determinants for measuring employees’ perception of sustainability with the collected data from service industries. The EFA revealed that there were six factors for organisational sustainability with 26 questionnaire items. The six factors are as follows: environment management, employee-related sustainability, public related sustainability, financial sustainability, pollution control measures and governance sustainability. The identified factors were tested using CFA and the results are discussed.

This paper will be beneficial for the academicians in sustainability and the policy-makers as it provides a scale to measure employees’ perception on the sustainability of an organisation. This paper adds value to the research by providing a six-factor measurement model for organizational sustainability of selected service industries.

The paper is highly beneficial to the organisations to measure employees’ perception on sustainability and ascertain their position in supporting the holistic development of environment and society, thereby improving the goodwill and reputation of the organisation.

This paper provides insights about measuring employees’ perception on organizational sustainability. A six-factor measurement model has been proposed for organisational sustainability.

Previous studies on hospital supply chain performance have attempted to measure the performance of the hospital supply chain either by the measurement of performance indicators or the performance of specific activities. This paper attempts to measure the internal hospital supply chain's performance indicators to find their interdependencies to understand the relationship among them and identify the key performance indicators for each of those aspects of the logistics process toward improvement.

In this research, a systematic assessment and analysis method under vagueness is proposed to assess, analyze and measure the internal health care performance aspects (HCPA). The proposed method combines the group Decision-Making and Trial Evaluation Laboratory (DEMATEL) method and rough set theory.

The study results indicate that the most critical aspects of hospital supply chain performance are completeness of treatment, clinical care process time and no delay in treatment.

The causal relationship from rough-DEMATEL can advise management officials that to improve the completeness of treatment toward patient safety, clinical care process time should be addressed initially and with it, patient safety aspects such as free from error, clinical care productivity, etc. should be improved as well. Improvement of these aspects will improve the other aspects they are related to.

The purpose of this study is to investigate the relationship between investments in quality and lean practices, and their impact on factory fitness. Using concepts originating in the theory of swift even flow, this study asserts that manufacturers, in order to improve their production swiftness and evenness, must leverage the potential synergetic effects between quality and lean practices.

This research uses data from the Global Manufacturing Research Group (GMRG) survey project (with data collected from 922 manufacturing plants, across 18 countries). The constructs and measurement model were assessed using confirmatory factor analysis (CFA) and the hypotheses were tested using ordinary least square (OLS) models.

This study highlights that both investments in quality and lean practices have direct impact factory fitness. The results provide insights into the efficacy of the investments in manufacturing practices and their role in augmenting the operational performance. The investments in quality practices were found to enhance the efficacy of investments in lean practices, which in turn impact the factory fitness.

From a practical perspective, the study informs managers on how to leverage investment in quality practices to enhance the impact of lean practice on performance. The results provide empirical evidence to support management decision-making concerning the development of competences in quality and lean practices, which may create competitive advantage.

This study contributes to the quality and lean literature and provides empirical evidence of the synergetic effects between investments in quality and lean practices. The analysis offers a greater understanding of the mechanisms that can be used to maximise the impact of investments in lean practices, from a global perspective. The findings are important to the advancement of theory in operations management, as it integrates three research streams: quality practices, lean practices and swift even flow research.