Search results

The purpose of this paper is to propose the use of graph theoretic structural modeling for assessing the possible reduction in complexity of the work flow procedures in an organization due to lean initiatives. A tool to assess the impact of lean initiative on complexity of the system at an early stage of decision making is proposed.

First, the permanent function-based graph theoretic structural model has been applied to understand the complex structure of a manufacturing system under consideration. The model helps by systematically breaking it into different sub-graphs that identify all the cycles of interactions among the subsystems in the organization in a systematic manner. The physical interpretation of the existing quantitative methods linked to graph theoretic methodology, namely two types of coefficients of dissimilarity, has been used to evolve the new measures of organizational complexity. The new methods have been deployed for studying the impact of different lean initiatives on complexity reduction in a case industrial organization.

The usefulness and the application of new proposed measures of complexity have been demonstrated with the help of three cases of lean initiatives in an industrial organization. The new measures of complexity have been proposed as a credible tool for studying the lean initiatives and their implications.

The paper may lead many researchers to use the proposed tool to model different cases of lean manufacturing and pave a new direction for future research in lean manufacturing.

The paper demonstrates the application of new tools through cases and the tool may be used by practitioners of lean philosophy or total quality management to model and investigate their decisions.

The proposed measures of complexity are absolutely new addition to the tool box of graph theoretic structural modeling and have a potential to be adopted by practical decision makers to steer their organizations though such decisions before the costly interruptions in manufacturing systems are tried on ground.

This paper aims to use the high-velocity oxy fuel (HVOF) spraying process for depositing 93(WC–Cr₃C₂)–7Ni, 75Cr₃C₂–25NiCr, 83WC–17C_O and 86WC–10C_O–4Cr coatings on ASME SA213 T91 to study the corrosion resistance of these coatings in an actual boiler environment.

The HVOF spraying process was used for depositing 93(WC–Cr₃C₂)–7Ni, 75Cr₃C₂–25NiCr, 83WC–17C_O and 86WC–10C_O–4Cr coatings on ASME SA213 T91. All the coatings obtained are found to be uniform, dense and having thickness between 200 and 250 μm. All the coatings were exposed in an actual boiler environment at 900°C temperature for 10 cycles. Each cycle consisted of 100 h heating followed by 1 h cooling at ambient conditions. X-ray diffraction, scanning electron microscopy and energy-dispersive spectroscopy techniques were used to analyse corrosion products.

All the coated samples were found to be having higher corrosion resistance than the uncoated samples. Among coated specimens, 93(WC–Cr₃C₂)–7Ni coating has shown maximum and 75Cr₃C₂–25NiCr coating has shown minimum resistance to corrosion.

This paper is original research.

The purpose of this paper is to study the impact of restructuring in the manufacturing system at the conceptual stage using graph theoretic model.

Some restructuring decisions are conceptualized which reflect the aim of the organization to gradually evolve the manufacturing system towards a leaner structure. This is achieved by way of defining simplified procedures so that lesser hindrance in terms of cycles of interactions is encountered. The restructuring decisions are represented by five restructured configurations of the manufacturing system, through gradual removal of appropriate interaction links. The graph theoretic models are developed for original configuration and each of the new restructured configurations and the resulting structural characterization information is used to compare the structure of restructured configurations with the original configuration. The value of the coefficient of dissimilarity of each of the new configurations with respect to the original configuration is obtained to have a quantitative estimate of the simplification that may be achieved by different contemplated restructuring decisions.

The present work shows that the restructuring decisions can be represented by different configurations in the form of schematic diagrams involving minor changes in the interaction structure among subsystems of the manufacturing system. The quantitative analysis using coefficient of dissimilarity for restructuring decisions indicated that there are varying levels of impact created by five comparable restructuring decisions considered in the study. The findings have a potential to guide the restructuring efforts by identifying a focus area that can produce greater impact of restructuring.

The findings are valid for a particular case manufacturing organization which does not involve itself in extensive design activity. The study is based on the assumption that the schematic diagram and graph theoretic model captured all the relevant influencing factors of the manufacturing system.

The study provides an easy to use methodology for the practical decision makers in manufacturing industry striving to improve the performance of their organization. It can provide the analysis of restructuring decisions at the conceptual stage itself without the necessity of disturbing the normal functioning of the organization. There is a scope for identifying focus areas where the restructuring may yield comparatively greater dividends.

The study of restructuring by representing it in the form of changes in interactions among subsystems of a manufacturing system and investigation of the impact of such restructuring efforts at the conceptual stage using graph theoretic model has been carried out for the first time.

The need for structural health monitoring systems is continuously growing to maintain existing civil infrastructure. For the purpose of assuring seismic safety, it is necessary to monitor the damage for its occurrence, its location and the extent of damage. Information on the damage may be utilized to make decisions on maintenance and structural safety of existing buildings, rapid evaluation of condition of damaged structure after future earthquakes, estimation of residual life of structures, feasibility of repair and retrofitting of structures, partial replacement or demolition of structure and financial planning for renovation and rehabilitation. The purpose of this paper is to present a four‐level scheme of damage detection.

In the first stage of the four‐level scheme, finite element model has been developed and dynamic parameters are calculated. In the second stage, change in the dynamic properties of farmed reinforced concrete building model is identified from vibration measurements under different level of controlled damage. In the third stage, search for the damaged stories containing the damaged components is carried out of the damaged model by making use of the change in modal properties. Finally, the extent of damage is evaluated by using its frequency response function (FRF).

The magnitude of FRF decreases with the increase in the level of damage in the RCC building model. The damage index for different levels of damage as calculated from the FRF magnitude indicates that damage index increases with increase in damage. The magnitude of FRF varies with the level of damage in the storey.

Three storey RCC building model without infill wall have been considered. Damage has been induced in the building model by applying static horizontal load at the roof level.

The paper contains only unpublished Information derived from other publications is strictly referenced. Therefore, most of the concepts and experiences presented are new.

The purpose of this paper is to attempt to integrate manufacturing system analysis to obtain system‐wide optimized solutions and to increase the level of comprehensiveness of the manufacturing system modelling and to develop method of characterization of manufacturing systems based on its structure.

Elements constituting the manufacturing plant and the interactions between them have been identified through a literature survey and have been represented by graph‐based model. The matrix models and the variable permanent function models are developed for carrying out decomposition, characterization and the total analysis.

Structural patterns and combination sets of subsystems interacting in various ways have been recognized as capabilities of manufacturing system in different performance dimensions. The permanent function of the manufacturing system matrix has been proposed as a systematic technique for structural analysis of manufacturing system. Also, the terms of permanent multinomial characterize the manufacturing systems uniquely and are highly useful for computational storage, retrieval, communication as well as analysis of the structural information of manufacturing system.

The structure‐based characterization technique developed has the potential of aiding the ongoing research activities in the field of benchmarking, and business process reengineering. The graph theory‐based methodology will serve as a framework to develop composite performance measures building on the performance measures of the individual elements of the manufacturing system graph in various dimensions.

Through the use of proposed methodology, a manufacturing manager will be able to make better informed decisions towards organizational efforts of improving the productivity and speed. For aiding several decisions, different “what‐if” scenarios may be generated with several structural modifications.

This graph theory‐based methodology is a novel mechanism to seamlessly integrate manufacturing system giving way to system wide optimization. The paper is an attempt to address the need for comprehensive and integrated analysis of the manufacturing system.

This study aims to investigate the connection between digital literacy and women’s empowerment in the rural Himachal Pradesh. It explores how improved digital skills contribute to increased empowerment among women with a specific focus on the role of education in enhancing digital literacy.

This study included 250 rural participants who completed structured questionnaires. Analytical tools, including independent-sample t-tests and partial least squares structural equation modeling, were applied to the data to gain insights into the relationship between digital literacy and women’s empowerment.

This study revealed a significant positive link between digital literacy and women’s empowerment in the rural Himachal Pradesh context. Education has emerged as a key factor that influences women’s digital skills and empowerment levels.

This research adds novelty by examining the digital literacy–women’s empowerment nexus in rural Himachal Pradesh and emphasizing the impact of education. The combination of statistical methods offers a robust approach to understanding this relationship and underscores the importance of digital inclusion and education for gender equality and women’s progress.

Many types of research have already investigated the lean, green or agile manufacturing systems in a discrete manner or as combinations of two of them. In today’s competitive scenario, if industry wants to perpetuate its name in the market, then it has to supervene proper thinking and smart approach. Therefore, the combination of lean, green and agile manufacturing systems can provide better and beneficial results. The purpose of this paper is to discern the barriers to the combined lean green agile manufacturing system (LGAMS), understand their interdependence and develop a framework to enhance LGAMS by using total interpretive structural modeling (TISM) and MICMAC (Matriced’ Impacts Croise’s Multiplication Appliquée a UN Classement) Analysis.

This paper uses TISM methodology and MICMAC analysis to deduce the interrelationships between the barriers and rank them accordingly. A total of 13 barriers have been identified through extensive literature review and discussion with experts.

An integrated LGAMS has been presented that balances the lean, green and agile paradigms and can help supply chains become more efficient, streamlined and sustainable. Barriers are identified while referring to all three strategies to showcase the clear relevance. TISM models the barriers in different levels showcasing direct and important transitive relations. Further, MICMAC analysis distributes the barriers in four clusters in accordance with their driving and dependence power.

The inferences have been drawn from a model developed on the basis of inputs from a small fraction of the industry and academia and may show variations when considering the whole industry.

The outcome of this research can contribute to bringing the change to the manufacturing systems used in most developing nations. Also, top managers considering adoption of LGAMS can be cautious of the most influential barriers.

A TISM-based model of the barriers to an integrated LGAMS has been proposed with evaluation of the influence of the barriers.

In developing countries such as India, it is common practice to use low‐quality building materials, the strength of such materials reduce with time, which affects the lifespan of buildings. The wind, rain, seepage, and surface runoff are other key factors responsible for building damage and exterior degradation. The increasing industrial growth in and around urban areas is responsible for increasing industrial and anthropogenic emissions that are found to accelerate degradation of the buildings that affects their physical appearance. In an area prone to natural hazards such as earthquakes, volcanoes, subsidence, floods, lightning, tornados, and cyclone/hurricanes, huge amounts of damage throughout the globe has been experienced. For the purpose of assuring safety due to natural hazards, it is necessary to monitor the damage for its existence, its location and extent. Undetected damage may potentially lead to risk of vulnerability caused by natural hazards and eventually to catastrophic failure. Hence, rapid structural damage detection is essential and important to save human life due to failure of structures or buildings. Most of the time, human loss occurs due to damage to the buildings. This paper aims to address these issues.

In the present study, numerous experiments have been carried out on two reinforced concrete building test specimens and on seven existing reinforced cement concrete structures.

The results presented here in this study show that the vibration measurements can be used to monitor the health of framed reinforced cement concrete buildings.

The present study is part of doctoral thesis of Varinder S. Kanwar, an original research work.

This article analyzes research on digital transformation in the tourism sector, providing insights into leading work, authors, journals, trends and future research opportunities. However, limited in-depth research exists on this topic, and the existing studies lack an understanding of its development, scope and relevant areas.

The study utilized the Scopus database to identify 61 articles on digital transformation in the tourism sector. The research employed VOSviewer software to analyze publication and citation structure, incorporating bibliometric variables like co-authorship, co-citation network, keywords co-occurrence network and bibliographic coupling.

The study yielded valuable insights from top-cited articles, revealing their contributions to digital transformation in tourism research. It also highlighted publication trends and the impact of authors, journals and studies and conducted co-occurrence, co-authorship and bibliographic analyses to identify key trends and issues in the tourism sector. The study calls for further examination of the digital revolution in tourism research and outlines future opportunities for researchers in this area.

To enhance the comprehensiveness of data collection, it is recommended that researchers consider including publications from databases such as WOS (Web of Science), Dimensions and PubMed in addition to the Scopus database. This broader inclusion of sources can provide different network structures and valuable insights from the field of digital transformation in the tourism sector.

The research provides substantial value to the study of digital transformation in tourism by focusing on bibliometric data from the Scopus database for the period from 2017 to 2022. By analyzing this data, it identifies significant trends in digital transformation within tourism research. Additionally, the study uncovers new areas of digitization in the tourism sector, further enhancing its value and relevance.