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Enzymatic desizing using α-amylase is the conventional and eco-friendly method of removing starch based size. Conventionally, enzymes are drained after completion of process; being catalysts, they retain their activity after reaction and need to be reused. Immobilization allows the recovery of enzymes to use them as realistic biocatalyst. This study aims to recover and reuse of α-amylase for desizing of cotton via immobilization.

This paper investigates the application of α-amylase immobilized on Chitosan and Eudragit S-100 for cotton fabric desizing. A commercial α-amylase was immobilized on reversibly soluble-insoluble polymers to work out with inherent problems of heterogeneous reaction media. The immobilization process was optimized for maximum conjugate activity, and immobilized amylases were applied for grey cotton fabric desizing.

The desizing performance of immobilized amylases was evaluated in terms of starch removal and was compared to free enzyme. The immobilized amylases showed adequate desizing efficiency up to four cycles of use and were recovered easily at the end of each cycle. The amylase immobilized on Eudragit is more efficient for a particular concentration than chitosan.

Immobilization associates with insolubility and increased size of enzymes which lead to poor interactions and limited diffusion especially in textiles where enzymes have to act on macromolecular substrates (heterogeneous media). The selection of support materials plays a significant role in this constraint.

The commercial α-amylase was covalently immobilized on smart polymers for cotton fabric desizing. The target was to achieve immobilized amylase with maximum conjugate activity and limited constraints. The reversibly soluble-insoluble polymers support provide easy recovery with efficient desizing results in heterogeneous reaction media.

The purpose of this paper is to present a sensitivity analysis of fault-tolerant redundant repairable computing systems with imperfect coverage, reboot and recovery process.

In this investigation, the authors consider the computing system having a finite number of identical working units functioning simultaneously with the provision of standby units. Working and standby units are prone to random failure in nature and are administered by unreliable software, which is also likely to unpredictable failure. The redundant repairable computing system is modeled as a Markovian machine interference problem with exponentially distributed failure rates and service rates. To excerpt the failed unit from the computing system, the system either opts randomized reboot process or leads to recovery delay.

Transient-state probabilities have been determined with which the authors develop various reliability measures, namely reliability/availability, mean time to failure, failure frequency, and so on, and queueing characteristics, namely expected number of failed units, the throughput of the system and so on, for the predictive purpose. To spectacle the practicability of the developed model, a numerical simulation, sensitivity analysis and so on for different parameters have also been done, and the results are summarized in the tables and graphs. The transient results are helpful to analyze the developing model of the system before having the stability of the system. The derived measures give direct insights into parametric decision-making.

The conclusion has been drawn, and future scope is remarked. The present research study would help system analyst and system designer to make a better choice/decision in order to have the economical design and strategy based on the desired mean time to failure, reliability/availability of the systems and other queueing characteristics.

Different from previous investigations, this studied model provides a more accurate assessment of the computing system compared to uncertain environments based on sensitivity analysis.

The purpose of this paper is to study the analytical hierarchy process (AHP) based on assessment of sustainability indicators for public transportation system including pedestrians and feeder services in developing country.

A hybrid approach based on the AHP is considered for assessment of the sustainability of public transportation system including pedestrians and feeder services. Sustainability related indicators for public transportation system (namely for metro, bus and feeder bus) and pedestrians based on past data were reviewed and subsequently, more important indicators catering needs of developing country have been added to achieve significant sustainability score and a total of 17 indicators were selected for assessment of comprehensive sustainability (seven indicators under economic, six under social and four under environmental categories).

For quantifying the assessment, specific user interview surveys are performed in south Delhi region and accordingly perception of user and transportation-related operational characteristics of the public transport system were also collected. Preliminary result shows air pollution in environmental category, public health in social category and productivity in economic category is most influential parameters in developing country.

AHP method is applied for rating the criteria and setting out the priority of designed sustainable indicators. Subsequently sustainable mitigation measures and scenarios for the study area can be evaluated utilizing developed comprehensive sustainability indicator for public transportation system including pedestrian and feeder services available in developing country.

This paper aims to provide relevant knowledge about entrepreneurship and women’s leadership in the Indian context. More specifically, it unleashes the veiled challenges as well as success stories of select women entrepreneurs of a developing country to bridge the gap between entrepreneurship theory and practice. It aims to provide directions to the policymakers, educationists, society and families in creating a conducive environment that is essential for the success of women entrepreneurs.

With a qualitative case study approach, data were collected from Tamil Nadu, a southern Indian state which has a maximum number of women entrepreneurs. Face-to-face interviews were conducted to explore the supportive as well as challenging dimensions of their entrepreneurial journey.

Content analysis of the interview transcripts indicated that successful entrepreneurs are opportunity-driven and they focus on innovation, service, generation of wealth and employment. Support from family, especially from fathers or husbands, is as important as the entrepreneurial drive, skills and abilities of an entrepreneur. Success for them is being happy, thriving work, having a happy family, having a great work-life balance and the satisfaction to have served society apart from being independent (economically/ financially). Among India’s societal and cultural realities, women have to conquer many hurdles (both implicit and explicit) in their way concerning the societal attitudes toward women stepping out of the home boundaries and traditional gender role expectations. The silver line is societal attitudes are changing, especially in urban India. There are enough support and encouragement from the family, which helps these women pursue their passion and eventually become a successful leader.

The success stories of women will bring a wave of positive developmental change in India by fostering respect for women in a male-dominated society and flashing the importance of women’s entrepreneurship.

This paper provides a new examination of women entrepreneurs that significantly further the debate about the underrepresentation of women in leadership roles, especially in entrepreneurship in an emerging economy context like India. Apart from the deterrents, it aims to highlight the enablers and motivations to choose this unconventional profession.

The case describes the internal growth workshop initiative at Vedanta Group. Anil Agarwal in 1976 founded Vedanta as a scrap-metal dealership in Mumbai (then Bombay). Over the years, Anil pursued a very aggressive growth journey with a vision to create a leading global natural resource company. The principal objective of discussing this case is to understand how Vedanta introduced this initiative and how it fits within the strategic human resource management at the group.

The purpose of this paper is twofold: to explain access to formal and informal credit in agriculture of Vietnam; and to compare the effectiveness between regular econometrics and machine learning techniques.

The multinomial logit (MNL) regression model and the random forest (RF) technique are employed for comparison purposes. To avoid heteroskedasticity, the robust covariance matrix is computed to estimate the sandwich estimator which in turn provides an asymptotic covariance matrix for biased estimators. Additionally, multicollinearity is tested among independent variables with variance inflation factors less than 3. Adequacy approach and sensitivity analysis are used to determine relevant levels of predictors. For models comparison, statistical evaluation metrics including Cohen’s κ, mean absolute error, root mean squared error and relative absolute error are employed.

The discrepancy between sensitivity analysis and adequacy approach revealed that MNL is more compatible for explaining determinants of credit participation. Due to insignificant differences in the evaluation metrics between models, the winner of choice is undetermined. Among other determinants, collateral, farmsize, income, procedure, literacy and all risk variables stand out to be critical factors when deciding borrowing schemes. While financially literate farmers tend to acquire loans from both sources, borrowing decisions against different risk sources depend on risk type and famers’ own desire to borrow.

Results of the MNL model are more consistent with literatures, which reinforce the role of collateral in the local credit scheme. Besides, financial literacy and farmers’ perception on different risk sources also influence how farmers’ borrowing strategies vary among sources.

It is difficult for anyone to implement all the lean tools simultaneously. One of the core issues is identifying critical criteria for the successful implementation of lean manufacturing (LM) and evaluating them. The purpose of this paper is to analyze the causal relationships of LM criteria in a machine tool manufacturing firm located in national capital region of India using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method.

The research paper presents a blend of theoretical framework and practical applications. Based on literature review, 17 LM criteria were extracted that were validated by experts. A questionnaire was developed that was answered by experts serving in the XYZ machine tool manufacturing firm. Then, the DEMATEL method was applied to analyze the importance of criteria and the casual relations among the criteria were developed.

Using DEMATEL, the lean criteria were divided into cause group and effect group. In this study, information technology, computer-integrated manufacturing, enterprise resource planning, training, fixed position layout, smart processes and automation and concurrent engineering were classified in the cause group. Just in time, value stream mapping, 5-S, single minute exchange of die, visual control, job scheduling, standardized work, cellular manufacturing, poka-yoke, and total quality management were categorized in the effect group. The DEMATEL framework indicates that “training” is the most influencing factor for the lean implementation process in machine tool sector.

To know the key lean criteria and relationship among them can help many organizations to develop lean competencies. If the authors want to obtain high performance in terms of the effect group factors, it would be necessary to control and pay a great deal of attention to the cause group factors beforehand. This study is perhaps among the first few with focus on segmenting the set of lean criteria into some meaningful portions in order to effectively facilitate its implementation. The paper provides useful insights to the lean production implementers, consultants, and researchers.

The purpose of this research paper is to identify the enablers for Lean implementation in the manufacturing sector, to establish a relationship among them using interpretive structural modeling (ISM) and to rank them using interpretive ranking process (IRP).

The research paper presents a blend of theoretical framework and practical applications. In the paper, eight enablers of Lean production are identified from literature survey and experts’ opinion. These include 5S, value stream mapping (VSM), just in time, single minute exchange of die, computer-integrated manufacturing, concurrent engineering, training and enterprise resource planning. ISM is used to obtain a structural relationship among these enablers of Lean. MICMAC analysis is used to identify the driving power and dependence of the variables. Further, IRP is used to rank the lean enablers with respect to key performance areas.

The ISM- and IRP-based models indicate that “training” is the most significant factor for the Lean implementation process in manufacturing sector. The MICMAC analysis also shows that “training” has the maximum driving power and the least dependence and hence has strong managerial significance. The management should place high priority on tackling this criterion. VSM occupies the top level in the ISM hierarchy, indicating that all other Lean enablers should act in unison to make VSM implementation a success.

Enablers are the building blocks for deployment of the Lean concept. To know the key enablers and relationship among them can help many organizations to develop Lean competencies. This study is perhaps among the first few that focuses on two modeling procedures based on interpretive logic, i.e. ISM and IRP. The paper provides useful insights to the Lean production implementers, consultants and researchers.