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Article

Rahul Kumar, Kanwarpreet Singh and Sanjiv Kumar Jain

In the past, the insufficiency of the traditional business practices to meet vibrant customer demands in continuously changing business environment has severely affected…

Abstract

Purpose

In the past, the insufficiency of the traditional business practices to meet vibrant customer demands in continuously changing business environment has severely affected organizational competitiveness. The purpose of this paper is to develop and propose a new framework for smoother and effective implementation of agile manufacturing by identifying and integrating a set of significant agility principles and techniques.

Design/methodology/approach

The present work proposed a framework for agile manufacturing by deploying the comparative analysis of 17 frameworks published in peer-reviewed journals.

Findings

The proposed conceptual framework constitutes of eight pillars for agile manufacturing implementation. The proposed framework relies on a strong foundation of leadership support. The roof of the proposed framework of agile manufacturing is supported by the pillars constituted of seven elements, an industry must deploy for successfully implementing agile manufacturing, namely, human resource-related issues, organizational culture-related issues, supplier-related issues, customer-related issues, innovation, concurrent engineering and information technology.

Originality/value

This work is the first attempt, in the best knowledge of the authors, to employ comparative analysis for critically analyzing a wide range of agile manufacturing frameworks. The findings of this study will assist researchers and managers in agile manufacturing implementation in more a smoother and effective way in manufacturing industries.

Details

World Journal of Science, Technology and Sustainable Development, vol. 16 no. 4
Type: Research Article
ISSN: 2042-5945

Keywords

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Article

Rahul Kumar, Mohammad Sikandar Azam, Subrata Kumar Ghosh and Hasim Khan

The aim of this paper is to study the effect of deterministic roughness and small elastic deformation of surface on flow rates, load capacity and coefficient of friction…

Abstract

Purpose

The aim of this paper is to study the effect of deterministic roughness and small elastic deformation of surface on flow rates, load capacity and coefficient of friction in Rayleigh step bearing under thin film lubrication.

Design/methodology/approach

Reynolds equation, pressure-density relationship, pressure-viscosity relationship and film thickness equation are discretized using finite difference method. Progressive mesh densification (PMD) method is applied to solve the related equations iteratively.

Findings

The nature and shape of roughness play a significant role in pressure generation. It has been observed that square roughness dominates the pressure generation for all values of minimum film thickness. Deformation more than 100 nm in bounding surfaces influences the film formation and pressure distribution greatly. Divergent shapes of film thickness in step zone causes a delay of pressure growth and reduces the load capacity with decreasing film thickness. The optimum value of film thickness ratio and step ratios have been found out for the maximum load capacity and minimum coefficient of friction, which are notably influenced by elastic deformation of the surface.

Practical implications

It is expected that these findings will help in analysing the performance parameters of a Rayleigh step bearing under thin film lubrication more accurately. It will also help the designers, researchers and manufacturers of bearings.

Originality/value

Most of the previous studies have been limited to sinusoidal roughness and thick film lubrication in Rayleigh step bearing. Effect of small surface deformation due to generated pressure in thin film lubrication is significant, as it influences the performance parameters of the bearing. Different wave forms such as triangular, sawtooth, sinusoidal and square formed during finishing operations behaves differently in pressure generation. The analysis of combined effect of roughness and small surface deformation has been performed under thin film lubrication for Rayleigh step bearing using PMD as improved methods for direct iterative approach.

Details

Industrial Lubrication and Tribology, vol. 69 no. 6
Type: Research Article
ISSN: 0036-8792

Keywords

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Article

Rahul Kumar and Pradip Kumar Bala

Collaborative filtering (CF), one of the most popular recommendation techniques, is based on the principle of word-of-mouth communication between other like-minded users…

Abstract

Purpose

Collaborative filtering (CF), one of the most popular recommendation techniques, is based on the principle of word-of-mouth communication between other like-minded users. The process of identifying these like-minded or similar users remains crucial for a CF framework. Conventionally, a neighbor is the one among the similar users who has rated the item under consideration. To select neighbors by the existing practices, their similarity deteriorates as many similar users might not have rated the item under consideration. This paper aims to address the drawback in the existing CF method where “not-so-similar” or “weak” neighbors are selected.

Design/methodology/approach

The new approach proposed here selects neighbors only on the basis of highest similarity coefficient, irrespective of rating the item under consideration. Further, to predict missing ratings by some neighbors for the item under consideration, ordinal logistic regression based on item–item similarity is used here.

Findings

Experiments using the MovieLens (ml-100) data set prove the efficacy of the proposed approach on different performance evaluation metrics such as accuracy and classification metrics. Apart from higher prediction quality, coverage values are also at par with the literature.

Originality/value

This new approach gets its motivation from the principle of the CF method to rely on the opinion of the closest neighbors, which seems more meaningful than trusting “not-so-similar” or “weak” neighbors. The static nature of the neighborhood addresses the scalability issue of CF. Use of ordinal logistic regression as a prediction technique addresses the statistical inappropriateness of other linear models to make predictions for ordinal scale ratings data.

Details

Journal of Modelling in Management, vol. 12 no. 2
Type: Research Article
ISSN: 1746-5664

Keywords

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Article

Rahul Kumar, Kanwarpreet Singh and Sanjiv Kumar Jain

The study aims at empirically investigating and prioritizing the critical barriers for the successful implementation of agile manufacturing in the medium- and large-scale…

Abstract

Purpose

The study aims at empirically investigating and prioritizing the critical barriers for the successful implementation of agile manufacturing in the medium- and large-scale Indian manufacturing industries.

Design/methodology/approach

A literature review of peer-reviewed journals and discussion with experts is used to identify 17 barriers to the implementation of agile manufacturing. An empirical survey is then conducted to collect data regarding the agile manufacturing barriers and is further analyzed using the factor analysis and vlsekriterijumska optimizacija i kompromisno resenje (VIKOR).

Findings

Based on the survey of empirical data, the investigated critical barriers were reduced in five critical categories, as follows: Managerial constraints, technological constraints, human resource–related constraints, operational constraints and organizational culture-related constraints, which are further ranked in terms of their severity using VIKOR. This research advocates the development of a strategy for addressing the most critical barriers instead of focusing on all for the successful implementation of agile manufacturing.

Originality/value

This work contributes to agile manufacturing literature by the structured presentation of the barriers to implement agile manufacturing in the Indian manufacturing industry. It also extends the integrated factor analysis and VIKOR method to investigate and rank the barriers.

Details

The TQM Journal, vol. 33 no. 1
Type: Research Article
ISSN: 1754-2731

Keywords

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Article

Rahul Kumar, Kanwarpreet Singh and Sanjiv Kumar Jain

The purpose of this paper is to investigate the effects of agile manufacturing practices on business performance of Indian medium and large-scale manufacturing industry.

Abstract

Purpose

The purpose of this paper is to investigate the effects of agile manufacturing practices on business performance of Indian medium and large-scale manufacturing industry.

Design/methodology/approach

A survey questionnaire was designed to attain the research objectives. Agile manufacturing questionnaire was sent to around 500 randomly selected manufacturing organizations in the northern spectrum of India through e-mails and posts, out of which 154 usable responses have been received. This study investigates the inter-relationships between various agile manufacturing implementation practices and business performance measures using various statistical techniques. This paper deploys Games–Howell hoc test to establish the statistical significance of business performance improvements, progressively accrued over a reasonable period of time, through holistic agile manufacturing implementation.

Findings

The paper validates the contribution of agile manufacturing toward realization of the significant improvements in various business performance measures such as customer-related achievements, financial achievements, business-related achievements, operational achievements, employee-related achievements, and supplier-related achievements. Further, the discriminant validity test has been used in this paper for classifying highly successful and moderately successful organizations.

Research limitations/implications

The paper only concentrated on manufacturing organizations in northern India. The results of this paper cannot generalize across all the sectors and spectrum of Indian manufacturing organizations.

Originality/value

This paper develops an insight into the strong potential of agile manufacturing implementation practices in affecting business performance measures.

Details

World Journal of Science, Technology and Sustainable Development, vol. 17 no. 1
Type: Research Article
ISSN: 2042-5945

Keywords

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Article

Rekha Chawla, S. Sivakumar, Santosh Kumar Mishra, Harsimran Kaur and Rahul Kumar Anurag

Milk cake is a well-renowned khoa-based dairy product in India, produced either from the buffalo milk or using a specific danedar variety of khoa. Under ambient…

Abstract

Purpose

Milk cake is a well-renowned khoa-based dairy product in India, produced either from the buffalo milk or using a specific danedar variety of khoa. Under ambient conditions, shelf-life of milk cake is generally up to 3–4 days, whereas under refrigeration conditions, it can last up to 12–14 days. Therefore, the present study aims to evaluate the effect of modified atmosphere packaging (MAP) to enhance the shelf-life and keeping intact freshness of milk cake under refrigerated conditions (4 ± 2 °C).

Design/methodology/approach

Different gas concentrations of N2 and CO2 (70:30, 50:50 and 90:10) were used as a treatment, whereas control samples were kept under atmospheric air composition. The product was examined for sensory, physicochemical and microbiological parameters at weekly intervals.

Findings

The physicochemical and microbiological attributes displayed gradual elevation with progressive storage period in all the samples. However, the overall sensory profile of the product remained acceptable for a longer duration. Most of the quality parameters in control declined more rapidly with a shelf life of 14 days, in comparison to MAP packed samples, where gas flushing with the ratio 70:30 was found to be best suited for extending the shelf life of milk cake up to 28 days at refrigeration temperature.

Originality/value

To extend the shelf life of milk cake, modified atmosphere was provided with different gas ratios to reach a best-suited environment for sensory, storage life and proximate parameters.

Details

British Food Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0007-070X

Keywords

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Article

Rahul Kumar, Shubhadeep Mukherjee, Bipul Kumar and Pradip Kumar Bala

Colossal information is available in cyberspace from a variety of sources such as blogs, reviews, posts and feedback. The mentioned sources have helped in improving…

Abstract

Purpose

Colossal information is available in cyberspace from a variety of sources such as blogs, reviews, posts and feedback. The mentioned sources have helped in improving various business processes from product development to stock market development. This paper aims to transform this wealth of information in the online medium to economic wealth. Earlier approaches to investment decision-making are dominated by the analyst's recommendations. However, their credibility has been questioned for herding behavior, conflict of interest and favoring underwriter's firms. This study assumes that members of the online crowd who have been reliable, profitable and knowledgeable in the recent past will continue to be so soon.

Design/methodology/approach

The authors identify credible members as experts using multi-criteria decision-making tools. In this work, an alternative actionable investment strategy is proposed and demonstrated through a mock-up. The experimental prototype is divided into two phases: expert selection and investment.

Findings

The created portfolio is comparable and even profitable than several major global stock indices.

Practical implications

This work aims to benefit individual investors, investment managers and market onlookers.

Originality/value

This paper takes into account factors: the accuracy and trustworthiness of the sources of stock market recommendations. Earlier work in the area has focused solely intelligence of the analyst for the stock recommendation. To the best of the authors’ knowledge, this is the first time that the combined intelligence of the virtual investment communities has been considered to make stock market recommendations.

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Article

Rahul Kumar, Kanwarpreet Singh and Sanjiv Kumar Jain

The purpose of this paper is to investigate the existing literature on agile manufacturing (AM) to pinpoint critical success factors (CSFs) affecting the successful…

Abstract

Purpose

The purpose of this paper is to investigate the existing literature on agile manufacturing (AM) to pinpoint critical success factors (CSFs) affecting the successful implementation of agile manufacturing systems.

Design/methodology/approach

The study focused on empirical articles published in peer-reviewed journals from 1991 to 2019 (July). In total, 37 empirical studies were shortlisted for analysis as the reliability and validity of the constructs were critically tested using various statistical methods. Further, “Pareto analysis” tool was employed to sort and arrange the factors critical for smoother and effective implementation of AM, in descending order according to their frequency of occurrence.

Findings

The present work scrutinizes 37 research papers, resulting in 33 CSFs that affect AM implementation. Using Pareto analysis, 8 CSFs are regarded as “vital few,” which account for 82.66 percent of occurrence, and the remaining 25 CSFs are regarded as “useful many,” which account for 17.34 percent of occurrence. The managers must focus on successful deployment of “vital few” CSFs, as they are more critical in achieving business excellence through the successful implementation of AM, in comparison to other 25 “useful many” CSFs.

Originality/value

To the best knowledge of authors, this work is the first attempt to employ Pareto analysis for critically analyzing a wide range of AM CSFs studies. The findings of this study will assist researchers and managers in AM implementation in a more smoother and effective way in manufacturing industries.

Details

International Journal of Quality & Reliability Management, vol. 37 no. 2
Type: Research Article
ISSN: 0265-671X

Keywords

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Article

Rahul Kumar, Kanwarpreet Singh and Sanjiv Kumar Jain

The concept of agile manufacturing is becoming critically important to manufacturing industry due to rapid industrialization, fluctuating customer demand, and turbulent…

Abstract

Purpose

The concept of agile manufacturing is becoming critically important to manufacturing industry due to rapid industrialization, fluctuating customer demand, and turbulent business environment. The aim of this study is to prioritize the attributes for successful implementation of agile manufacturing using a combined analytical hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach in Indian manufacturing industry.

Design/methodology/approach

The current study identifies eight agile manufacturing attributes through literature review and discussion with subject experts. The experts from different manufacturing industry have been asked to provide data for pairwise comparison of attributes. Afterward, an integrated AHP and TOPSIS approach is employed. The AHP is used to drive the priority weights of the attributes, and TOPSIS is used for prioritizing the attributes for successful implementation of agile manufacturing.

Findings

“Information technology,” “human resource management-related issues,” “customer-related issues,” “leadership support,” and “organizationalc related-issues” have been ranked as the top five significant and contributing attributes, which can pave the path for top management to concentrate on the critical areas and allocate significant resources to ensure successful implementation of agile manufacturing.

Originality/value

This research integrates AHP and TOPSIS to prioritize the attributes for successful implementation of agile manufacturing, which are further validated by comparing the ranks obtained through respective approach and sensitivity analysis.

Details

International Journal of Productivity and Performance Management, vol. 69 no. 7
Type: Research Article
ISSN: 1741-0401

Keywords

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Article

Debadyuti Das, Virander Kumar, Amit Kumar Bardhan and Rahul Kumar

The study aims to find out an appropriate volume of power to be procured through long-term power purchase agreements (PPAs), the volume to be sourced from the power…

Abstract

Purpose

The study aims to find out an appropriate volume of power to be procured through long-term power purchase agreements (PPAs), the volume to be sourced from the power exchange through day-ahead and term-ahead options and also a suitable volume to be sold at different points of time within a day, which would finally lead to the optimum cost of power procurement.

Design/methodology/approach

The study has considered a Delhi-based power distribution utility and has collected all relevant data from its archival sources. A stochastic optimization model has been developed to capture the problem of power procurement faced by the distribution utility, which is modelled as a mixed integer linear programming problem. Sensitivity analyses were carried out on the important parameters including hourly demand of power, unit variable cost of power available through PPAs, maximum back-down percentage allowed under PPAs, etc., to investigate their impact on daily cost of power under PPAs, daily cost of power under day-ahead and term-ahead options, daily sales revenue and also the net total daily cost of power procurement.

Findings

The findings include the appropriate volume of power procured from different suppliers through PPAs and from the power exchange under day-ahead and term-ahead options and also the surplus volume of power sold under the day-ahead arrangement. It has also computed the total cost of power purchased under PPAs, the cost of power purchased from the power exchange under day-ahead and term-ahead options and also the revenue generated out of the sale of surplus power under the day-ahead arrangement. In addition, it has also presented the results of sensitivity analyses, which provide rich managerial insights.

Originality/value

The paper makes two significant contributions to the existing body of power procurement literature. First, the stochastic mixed-integer linear programming model helps decision makers in determining the right volume of power to be purchased from different sources. Second, based on the findings of the procurement model, a power procurement framework is developed considering the dimensions of uncertainty in power supply and the cost of power procurement. This power procurement framework would aid managers in making procurement decisions under different scenarios.

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