Search results

Better membrane oxygenators need to be developed to enable efficient gas exchange between venous blood and air.

Optimal design and analysis of such devices are achieved through mathematical modeling tools such as computational fluid dynamics (CFD). In this study, a control volume-based one-dimensional (1D) sub-channel analysis code is developed to analyze the gas exchange between the hollow fiber bundle and the venous blood. DIANA computer code, which is popular with the thermal hydraulic analysis of sub-channels in nuclear reactors, was suitably modified to solve the conservation equations for the blood oxygenators. The gas exchange between the tube-side fluid and the shell-side venous blood is modeled by solving mass, momentum and species conservation equations.

Simulations using sub-channel analysis are performed for the first time. As the DIANA-based approach is well known in rod bundle heat transfer, it is applied to membrane oxygenators. After detailed validations, the artificial membrane oxygenator is analyzed for different bundle sizes (L/W) and bundle porosity (epsilon) values, and oxygen saturation levels are predicted along the bundle. The present sub-channel analysis is found to be reasonably accurate and computationally efficient when compared to conventional CFD calculations.

This approach is promising and has far-reaching ramifications to connect and extend a well-known rod bundle heat transfer algorithm to a membrane oxygenator community. As a variety of devices need to be analyzed, simplified approaches will be attractive. Although the 1D nature of the simulations facilitates handling complexity, it cannot easily compete with expensive and detailed CFD calculations.

This work has high practical value and impacts the design community directly. Detailed numerical simulations can be validated and benchmarked for future membrane oxygenator designs.

Future membrane oxygenators can be designed and analyzed easily and efficiently.

The DIANA algorithm is popularly used in sub-channel analysis codes in rod bundle heat transfer. This efficient approach is being implemented into membrane oxygenator community for the first time.

The purpose of this paper is to optimize the performance for complex repairable system of paint manufacturing unit using a new hybrid bacterial foraging and particle swarm optimization (BFO-PSO) evolutionary algorithm. For this, a performance model is developed with an objective to analyze the system availability.

In this paper, a Markov process-based performance model is put forward for system availability estimation. The differential equations associated with the performance model are developed assuming that the failure and repair rate parameters of each sub-system are constant and follow the exponential distribution. The long-run availability expression for the system has been derived using normalizing condition. This mathematical framework is utilized for developing an optimization model in MATLAB 15 and solved through BFO-PSO and basic particle swarm optimization (PSO) evolutionary algorithms coded in the light of applicability. In this analysis, the optimal input parameters are determined for better system performance.

In the present study, the sensitivity analysis for various sub-systems is carried out in a more consistent manner in terms of the effect on system availability. The optimal failure and repair rate parameters are obtained by solving the performance optimization model through the proposed hybrid BFO-PSO algorithm and hence improved system availability. Further, the results obtained through the proposed evolutionary algorithm are compared with the PSO findings in order to verify the solution. It can be clearly observed from the obtained results that the hybrid BFO-PSO algorithm modifies the solution more precisely and consistently.

There is no limitation for implementation of proposed methodology in complex systems, and it can, therefore, be used to analyze the behavior of the other repairable systems in higher sensitivity zone.

The performance model of the paint manufacturing system is formulated by utilizing the available uncertain data of the used manufacturing unit. Using these data information, which affects the performance of the system are parameterized in the input failure and repair rate parameters for each sub-system. Further, these parameters are varied to find the sensitivity of a sub-system for system availability among the various sub-systems in order to predict the repair priorities for different sub-systems. The findings of the present study show their correspondence with the system experience and highlight the various availability measures for the system analyst in maintenance planning.

The purpose of this paper is to identify the criticality of various sub-systems through the behavioral study of a multi-state repairable system with hot redundancy. The availability of the system is optimized to evaluate the optimum combinations of failure and repair rate parameters for various sub-systems.

The behavioral study of the system is conducted through the stochastic model under probabilistic approach, i.e., Markov process. The first-order differential equations associated with the stochastic model are derived with the use of mnemonic rule assuming that the failure and repair rate parameters of all the sub-systems are constant and exponentially distributed. These differential equations are further solved recursively using the normalizing condition to obtain the long-run availability of the system. A particle swarm optimization (PSO) algorithm for evaluating the optimum availability of the system and supporting computational results are presented.

The maintenance priorities for various sub-systems can easily be set up, as it is clearly identified in the behavioral analysis that the sub-system (A) is the most critical component which highly influences the system availability as compared to other sub-systems. The PSO technique modifies input failure and repair rate parameters for each sub-system and evaluates the optimum availability of the system.

A bottom case manufacturing system is under the evaluation, which is the main component of front shock absorber in two-wheelers. The input failure and repair rate parameters were parameterized from the information provided by the plant personnel. The finding of the paper provides the various availability measures and shows the grate congruence with the system behavior.

The purpose of this paper is to understand the scholarly contributions to the field of marketing by analyzing top ten journals of marketing.

The marketing journals were selected using SciMago marketing journal list, and SCOPUS database was used to identify the publications of the journals. A total of 9,190 articles were analyzed having 562,322 citation references. Methodologies like Wordle and Gephi were used to understand the most researched keywords and co-citation analysis among top five researchers. This paper also captured the information on most cited article along with author, most published author, most publishing country, most publishing university, the year with maximum publications and most used keywords.

The analysis indicates that “Kumar, V.” is most published author, that is, 68 publications, the most cited article is “On the evaluation of structural equation models” by Bagozzi and Yi (1988) with 6989 citations. The USA contributed the highest 6,720 publications, while University of Pennsylvania, Wharton School topped the list with 235 articles. In 2009, highest publication work was done by publishing 382 articles. “Game theory”, “Pricing” and “Advertising” are most used keywords which have been discussed in the literature.

This analysis will help researchers in understanding the growth in the field of the marketing in recent years and possible direction it could take in future. However, this paper considered only top ten marketing journals as listed in SciMago marketing journal list; therefore, future researchers may incorporate more research journals to get a clearer picture of the field of marketing.

This paper is one of the first attempts in recent time to understand the research work in the field of marketing considering top ten journals.

The purpose of this paper is to estimate the locational marginal price (LMP) at each distributed generation (DG) bus based on DG unit contribution in loss reduction. This LMP value can be used by distribution company (DISCO) to control private DG owners and operate network optimally in terms of active power loss.

This paper proposes proportional nucleolus game theory (PNGT)-based iterative method to compute LMP at each DG unit. In this algorithm, PNGT has been used to identify the share of each DG unit in loss reduction. New mathematical modeling has been incorporated in the proposed algorithm to compute incentives being given to each DG owner.

The findings of this paper are that the LMP and reactive power price values for each DG unit were computed by the proposed method for the first time. Network can be operated with less loss and zero DISCO’s extra benefit, which is essential in deregulated environment. Fair competition has been maintained among private DG owners using the proposed method.

PNGT has been used for the first time for computation of LMP in distribution system based on loss reduction. Incentives to each DG unit has have been computed based on financial savings of DISCO due to loss reduction. Share of active and reactive power generation of each DG unit on change in active power loss of network due to that DG unit has been computed with new mathematical modeling. The proposed method provides LMP value to each DG unit in such a way that the network will be operated with less loss.

An amalgamation of Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Analytical Network Process (ANP) has been performed to develop a decision-making framework for improving the overall performance of the microfinance institutions. A primary survey was conducted to collect real-time data from the heterogeneous stakeholders of microfinance institutions across India. The validation of the proposed framework is performed by comparing the results against the conventional method of Analytical Hierarchy Process (AHP).

This study identifies various dimensions and indicators for measuring the performance of Indian microfinance institutions. Additionally, the ranking and prioritisation of the performance dimensions and indicators is obtained by considering the mutual interrelation between them.

The study indicates that there exists a significant dyadic relationship between financial performance and social performance for improving the overall performance of the microfinance institutions. Governance is found to unidirectionally influence both financial and social performance. Among all the considered dimensions, financial performance of a microfinance institution is the most critical dimension for improving the overall performance. The top five performance indicators of the Indian microfinance institutions are funding source, borrowing and overhead cost, size of the firm, end-use of the money and depth of outreach.

The study was conducted in the context of Indian microfinance institutions; hence the scope of generalisation of the results is limited. This research considers both subjective and objective aspect of the performance dimensions and indicators from the perspective of multiple stakeholders (i.e. firm, society and regulator). The integrated framework is expected to aid in improving overall performance of microfinance institutions by focusing on the most critical (high prioritised) performance indicators.

An integrated DEMATEL-ANP framework is used in the domain of microfinance to assess the performance dimensions. This study is unique in terms of analysing performance of microfinance institutions from the perspective of heterogeneous stakeholders.

Waste generated from electrical and electronic equipment, collectively known as E-waste, remains a persistent environmental, economic and social problem. Sustainable E-waste management (EWM) has numerous benefits, such as preventing electronic waste from entering landfills, reducing the need for virgin materials by recovering valuable materials from recycling and lowering greenhouse gas emissions. Circular economy (CE) practices are considered the initial steps toward sustainable EWM, but some hurdles have been reported in the adoption of these practices. Therefore, the current study aims to identify the common CE practices, sustainability of the EWM process and the challenges in EWM, and to develop a conceptual framework for effective EWM.

Very few studies have proposed frameworks that acknowledge the challenges and CE practices of EWM. To fill this gap, a systematic literature review (SLR) was performed, and 169 research articles were explored.

A total of seven challenges in the adoption of effective EWM were identified: rules and policy, infrastructure, consumer behaviour, informal sectors, community culture, technology and economy. Eight common CE practices were also found for effective EWM: reuse, recycle, remanufacturing, refurbishment, repair, reduce, recover and repurpose.

A conceptual framework guiding sustainable EWM was proposed, which includes solutions for the identified challenges, and CE practices with sustainable benefits.

The purpose of this paper is to empirically examine how different supply chain attributes as determinants of the openness of supply chain affect organizational performance (OP).

Data were collected from 259 supply chain executives in Pakistan. Structural equation modeling was used to test the hypotheses.

The findings indicate that organizations may take the selective view of their supply chains resulting in a varying focus on different SC attributes. The results show that though all identified supply chain attributes positively relate to OP, some attributes such as combined agility and cooperation among supply chain partners have a weak correlation coefficient. This indicates that overall the relative openness of supply chain among selected sample of Pakistani organizations is low.

Supply chain executives may not have a selective focus on some attributes; rather, they may consider to have a broader perspective drawing upon a wider range of supply chain attributes as identified in the current study. In order to remain competitive, Pakistani manufacturing organizations need to learn more about opening up their boundaries and enhance the openness of their supply chain.

The contribution of the current study is two folds. First, drawing upon the current literature, it proposes the instrument to measure the relative openness of supply chain. Second, it empirically tests the selected conceptual model which highlights the relevance of supply chain attributes and their role in the resulting relative degree of supply chain openness. The empirical examination of the selected conceptual model of supply chain openness tends to make contribution to the wider literature on supply chain management.

Global competition has intensified pressure on small- and medium-sized enterprises (SMEs) to implement lean. Recently, the debate has converged to the role of lean implementation barriers (LIBs). The purpose of this paper is to contribute to this debate by exploring the LIBs in SMEs through three case studies.

A case study approach was employed followed by interpretive structural modelling (ISM) to model the interrelationship among the LIBs.

This study reveals that lack of management commitment, leadership and resources are the key barriers to lean implementation in SMEs in India. Furthermore, poor communication between different levels of the organisation and inadequate dissemination of the knowledge of lean benefits also creates hindrance in lean implementation. Managerial implications of the identified barriers for lean implementation in SMEs have been discussed.

The research regarding lean implementation in SMEs is scarce. This study is the first attempt of its kind to identify the lean barriers in a small industry setup through mathematical analysis.

This paper aims to discuss the concept of leanness and provide an effective assessment tool for measuring leanness of small and medium enterprises (SMEs).

A hybrid interpretive structural modelling–analytical network process (ISM-ANP) approach is used to develop leanness index for SMEs. The parameters for leanness are extracted from the literature survey, and the inter-relationships among them are identified through ISM approach. Further, the ANP tool is used to derive the weights of the parameters, and the leanness index is developed for SMEs.

A leanness assessment model is developed, which considers the interdependencies among leanness parameters. Continuous improvement, Just in Time and active management participation, respectively, get first, second and third ranks for leanness measurement in SMEs.

This study is based on the expert’s opinion, and it may tend to be biased. However, future study will be performed as empirical research to catch more explicit concept and more insights of leanness in context of SME sector.

This paper provides guidelines to the managers of SMEs for measuring the leanness index and planning for future. This leanness index gives information regarding the degree of lean adoption in the organization.

The proposed model has been developed by the expert opinion of academicians and practitioners. The proposed model can provide guidelines and directions for managers for leanness assessment in SME context.