Search results

Dynamic business environment has a deep influence on production and management related exercises. In order to remain competitive, organization needs to coordinate with continuous and unpredictable changes taking place in the market. Globalization of markets is posing competitive pressure on firms, which leads them to adopt a new manufacturing paradigm termed agile manufacturing (AM). The purpose of the present case study is to explore the contribution of AM towards agility and productivity enhancements in an Indian manufacturing company.

The study is carried out at forging industry which has been assessed on certain key business performance indicators. The assessment highlighted various issues which had scope for improvement to enhance the agility of the organization. Therefore, a phase-wise implementation of AM is carried to reap the significant benefits as a result of AM implementation in the case study company. The methodology has been applied to decrease the inline rejection, increase the productivity and responsiveness of the organization.

The results revealed an improvement in performance score from 77.5 to 100. Further, an increase in productivity and reduction in line rejection has been achieved through the systematic implementation of AM.

The study highlights the contributions of strategic AM implementation to organizational performance and highlights the need for successful management of AM practices for establishing sustained performance of the organization.

The contribution of the present work is the phase-wise implementation of AM in the case studied company.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

This study examined the impact of the Glasgow Climate Pact on the abnormal returns of global clean energy stocks. Further, this study examines which country-specific and firm-specific variables drive the cumulative abnormal returns (CARs) of clean energy stocks.

The authors used the event study method and cross-sectional multivariate regression model. The clean energy stocks in this study are limited to 81 constituent firms of the S&P Global Clean Energy Index across 17 nations. The final sample includes 80 firms and the sample period ranges from January 26, 2021, to December 07, 2021.

The study finds that the Glasgow Climate Pact negatively affects the stock returns of clean energy firms. Moreover, the climate change performance index (CCPI) positively impacts cumulative abnormal returns (CARs), signifying that clean energy investors react positively to firms in nations with good CCPI scores. The environmental, social and governance (ESG) measure for the shorter window (−1, +1) exhibited a negative relationship with CARs. The firm-specific variables (BTM, stock liquidity, size and past returns) exhibit a negative relationship with CARs in different event windows.

The authors use the CCPI as a proxy for the stringency of environmental policies in any nation. The authors extend the existing literature by employing firm-specific variables and supporting previous findings. Their findings have policy implications for clean energy investors, policymakers and other market participants.

Climate risks impact the global financial market, so the findings have implications for global regulatory bodies. Currently, there are bankruptcy cases due to climate risks. Because financial markets must play a critical role in shifting the economy toward a green one, regulators can use the cross-sectional drivers of this study to shape policy. It is also critical for regulators to reduce stock price volatility in the event of the implementation of environmental regulations and improve environmental disclosures by publicly traded companies. Furthermore, governments are interested in researching the effects of environmental regulations to protect stakeholders' interests. These regulations significantly impact emerging markets because they lack the same solid institutional frameworks as developed markets.

The authors provide evidence that firms with better ESG scores and larger firm sizes have experienced fewer abnormal returns, as these firms have stable financial and non-financial fundamentals. This timely study on the ongoing regulatory shift in environmental policy will help investors, policymakers, firms and other stakeholders make relevant decisions.

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.

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.

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.

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.

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

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.

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).

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.

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.

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).

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.

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.

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.

Agility addresses vibrant solutions for running companies to meet the dares of customers asking for high quality and low- cost goods and services. The purpose of this study is to identify the practices for the successful implementation of agile manufacturing and measure their relationship with business performance measures of the manufacturing industry.

The data for the pilot study were collected from 26 respondents through a questionnaire survey. After confirming the normality and reliability of the data, it was analyzed to examine the relationship between agile manufacturing practices and business performance measures.

The results show that there are strong relationships between agile manufacturing practices and business performance. Further, these attributes significantly contribute to delivering better business performance.

The study signifies the need for agile manufacturing in enhancing business performance for the growth and sustainability of the organization.

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.

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.

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.

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.