Department of Mechanical engineering

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Author: search.filters.author.Digalwar, Abhijeet K.

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    Risk assessment of electric vehicle supply chain in India using fuzzy analytical hierarchical process
    (Elsevier, 2025) Digalwar, Abhijeet K.
    The shift to electric vehicles (EVs) in India is a key step toward sustainable mobility as the transportation sector greatly contributes to greenhouse gas emissions. However, this transition demands a revised supply chain associated with various EV components such as batteries, motors, etc. Despite the ongoing efforts in the electrification of the transportation sector, numerous complexities and uncertainties in the EV supply chain have a bearing impact on its efficiency. The authors have conducted the research work to find out and rank the risk factors associated with the EV supply chain specific to India. A detailed literature review has been done and feedback from the industry stakeholders and academicians has been taken to identify the risk factors. The fuzzy analytical hierarchy process which is a multicriteria decision-making technique has been used to study the multidimensional effects of various decisions. The fuzzy analytical hierarchy process, a combined approach of analytical hierarchy process and fuzzy logic theory is effective in conducting risk assessment of a complex system that involves multiple uncertainties similar to the Indian EV supply chain.
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    Driving synergy: can TOC, lean, and six sigma integration work without flexibility?
    (Academy of Management, 2025-06) Digalwar, Abhijeet K.
    This study aims to empirically assess the combined impact of Theory of Constraints (TOC), Lean Manufacturing (LM), and Six Sigma (SS) – collectively known as TLS – on business performance in Indian manufacturing companies. Importantly, it investigates the role of manufacturing flexibility in influencing this relationship. Using a structured survey, data were collected from a diverse sample of Indian manufacturing companies. The study employs statistical techniques including Partial Least Square-Structural Equation Modelling (PLS-SEM) for model measurement, multiple regression analysis to test the influence of TLS on various performance metrics and hierarchical regression analysis to explore the moderating role of manufacturing flexibility. The results indicate that the implementation of TLS significantly improves business performance across several dimensions, including productivity, quality, and operational efficiency. Companies that have effectively integrated TLS into their operations report greater performance gains compared to those using individual or partial methodologies. Moreover, manufacturing flexibility is found to strengthen the relationship between TLS implementation and business performance, suggesting that companies with higher flexibility can better leverage TLS for enhanced operational outcomes. This study is among the first to empirically validate the impact of TLS integration on business performance in the context of Indian manufacturing. It also contributes to the existing literature by exploring the role of manufacturing flexibility, a factor that has received limited attention in previous research. The findings provide a robust framework for manufacturing companies seeking to implement TLS and highlight the strategic importance of flexibility in achieving operational excellence.
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    Towards sustainable transportation: factors influencing electric vehicle charging stations development
    (Elsevier, 2025-05) Digalwar, Abhijeet K.; Routroy, Srikanta
    The Indian transportation sector, reliant on fossil fuels, is predominantly accountable for the emergence of critical challenges such as greenhouse gas emissions, reliance on foreign energy sources, economic strain, and persistent health repercussions. In order to mitigate these urgent challenges, electric vehicles (EVs) are conceptualised as a viable, sustainable and ecologically sound technological solution, capable of successfully transitioning towards a sustainable low-carbon emission transportation framework and preserving finite natural resources. EVs encounter significant challenges in achieving rapid assimilation into the commercial landscape, and one of the most frequently referenced impediments to the accelerated adoption of EVs is the insufficiency of charging infrastructure along with the resultant range anxiety. Nevertheless, expanding the charging infrastructure network is financially burdensome and necessitates careful and strategic planning. Despite identifying essential factors, the inquiry “In what manner do these factors engage and interact?” has predominantly remained unaddressed in empirical investigations. Examining the interactions between these variables will empower producers and regulatory authorities to participate in systematic planning and devise suitable measures to govern these variables. The prime objective of this research is to execute an exhaustive assessment and furnish insights into the multifaceted factors/criteria influencing the establishment and development of EV charging infrastructure within a developing nation such as India. Factors are extracted from previous studies through literature reviews and expert interviews. The study also validates the identified factors empirically. Subsequently, a mixed-method approach is utilised to implement a combination of Interpretive Structural Modeling (ISM) and Decision-Making Trial and Evaluation Laboratory (DEMATEL). This methodology enables a methodical exploration of the hierarchical structures and interconnections among the variables, thereby enhancing the comprehension of their influence on the implementation and efficacy of charging infrastructure. The study identifies technological, economic, political, geographical, environmental, geopolitical, and socio-technical factors as key drivers influencing EV charging infrastructure development, highlighting the interdependencies between critical variables and providing a structured framework to enhance accessibility, scalability, and sustainability in alignment with global Sustainable Development Goals (SDGs) 7 and 13.
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    Assessment of optimal fuel and drive mix for automobile sector decarbonization in India: a scenario analysis of 2035
    (Springer, 2025-08) Digalwar, Abhijeet K.
    The rapid growth of predominantly fossil fuels powered automobiles in India results in harmful greenhouse gas emissions (GHG), environmental challenges like air pollution and health hazards. Hence, India is adopting alternate low-emission fuels like compressed natural gas (CNG), biofuels, promoting zero-emission technologies like fully electric vehicles (FEVs), pursuing options like hybrid vehicles (HEVs), and hydrogen-powered vehicles (HPVs). These solutions must encompass reliability, cost-effectiveness, circularity, and mainly optimality. This study addresses above challenges, aligns with India’s upcoming nationally determined contribution (NCD 3.0) and decarbonization policy till 2035 and derives an optimal alternate fuels/drive mix, It adopts a time-series forecasting and machine learning (ML) for vehicle inventory projections, constructs a scientific model, includes six relevant cost and benefit factors, evaluates eleven scenarios using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, derives an optimal mix and verifies its robustness through sensitivity analysis. The optimal mix for 2035 indicates a reduction in the share of fossil fuels (50%) with healthy improvement in the adoption of FEVs (40%), BFVs (8.4%), CNGVs (0.6%), HEVs (0.5%), and HFVs (0.5%). This shift toward cleaner solutions will enable reduction of around Rs 3.6 trillion in fuel imports and 54% of GHG emissions compared to current levels, enabling mitigating environmental challenges. Unlike energy sector, India lags in studies of optimal fuel / drive mix for automobile sustainability. This study addresses above gap, providing critical insights to policymakers, industry, and academia for fine tuning automotive decarbonization policies, toward achieving net zero by 2070.
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    Value Network Mapping for Productivity Improvement: A Case Study
    (IUP, 2013) Digalwar, Abhijeet K.
    The paper aims at improving the production performance of a transaxle assembly line by lean manufacturing implementation. The production performance has been increased by identifying and eliminating non-value added activities through value network mapping. To achieve maximum productivity while producing 200 pieces per shift instead of 150 pieces per shift, the assembly line will need only 13 operators instead of 17 and the productivity can be enhanced by 62.3% as compared to the current state. On the other hand, while producing 125 pieces per shift instead of 150 pieces per shift, the assembly line will need only 9 operators instead of 17 and productivity can be enhanced by 30.05% as compared to the current state. Both the production plans can be implemented with the minimum setup and changeover times
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    Modeling the Critical Success Factors for Sustainable Growth of Mining Industry in India
    (IUP, 2017) Digalwar, Abhijeet K.
    India has long been recognized as a nation well endowed in natural mineral resources. India is ranked fourth amongst the mineral producer countries, behind China, United States and Russia, on the basis of volume of production, as per the report on mineral production by International Organizing Committee for the World Mining Congress. It is however ranked eighth on the basis of the value of mineral production. Earth is moved by mining activity more than any other human endeavor. The mining sector therefore is one of the most important sectors in India’s economy and contributes about 2% to our GDP. However the contribution of the sector to India’s GDP has been on the decline due to increasing issues of pollution and global warming which lead to the concept of sustainable practices in most of the organizations. Many researchers are of the opinion that mining industries are major contributor to pollution of air, water and land; hence, it is important for the mining industries to develop environmentally conscious practices. This paper presents a detailed study of current mining practices in India and finding of different drivers/enablers to develop sustainable practices in mining industry in India. A Multi-Criteria Decision Making (MCDM) approach has been adopted to prioritize the drivers for sustainable development of mining industry.
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    Experimental and Numerical Optimization based Approach for Fibre Reinforcement in Rotomolding
    (ICAME, 2011) Digalwar, Abhijeet K.
    This study deals with the experimental analysis of fiber reinforcement of rotational molding processes and its numerical model based evaluation. The experiments are carried out to get patterns, using linear low density polyethylene (LLDPE) and glass fiber, to improve its surface finish, strength and hardness. For that design of experiment (DoE) is performed and then various experiments has been conducted. The theoretical optimum value is obtained and is compared with the experimental values. The optimum value by experimental calculations i.e., the weight of LLDPE and weight of fiber, with constant time, is in the permissible error with the theoretical value. This justifies that the experimental designs obtained are of optimum/local optimum value. Furthermore using a random population of points is generated and factors, which can improve the optimum design, are identified and reported
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    On-grid system evaluation for EV charging stations using renewable sources of energy
    (IEEE, 2020) Digalwar, Abhijeet K.
    The Indian Automobile Industry is the 5 th largest in the world. India, in its effort to switch to electric vehicles and reduce its carbon emissions, launched the National Electric Mobility Mission Plan 2020 in 2013. It formulated the Faster Adoption and Manufacturing of (Hybrid &) Electric Vehicles in India (FAME India) scheme in 2015 to promote the manufacturing of electric and hybrid vehicle technology and to ensure sustainable growth of the same. However, the adoption rate was not satisfactory. One of the main reasons for the slow pace of adoption of electric vehicles by the customers was the lack of supporting charging infrastructure. In order to plan for charging stations, it is important to forecast the energy demand and design the system using renewable sources of energy. This paper proposes a renewable energy model for charging stations that can be implemented in the pilot city of New Delhi. A software tool, Hybrid Optimization of Multiple Energy Resources (HOMER) is used for the simulation and analysis.
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    System Dynamics Approach for the Assessment of Leanness of Organizations
    (IEEE, 2018) Digalwar, Abhijeet K.
    Due to highly competitive, volatile and dynamic business environment, lean manufacturing is being seen as a winning strategy by manufacturers. Successful implementation of lean manufacturing can give an edge over their competitors, but during this implementation, they often fail to identify the direction in which the implementation should proceed. In order to help the organizations to progress in the right direction, there is a need to identify the variables and factors that affect the lean implementation process. A system dynamics approach has been applied to analyze the implementation process and help an organization towards becoming an effective lean organization. In this research, 17 variables are identified, through literature review and discussion with practitioners. A causal loop has been developed among the variables using system dynamics approach which represents “enablers” and “results”. This causal loop provides a visual representation of various cause and effect relationships and feedback loops to understand various factors and variables in a better way. It is probably one of the leading attempts to provide road map for implementation and assessment of leanness of organizations.
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    A systematic review of the integration of best practices for world class manufacturing
    (Inder Science, 2021-03) Digalwar, Abhijeet K.
    Manufacturing organisations are trying to become world class by integrating best practices. While multiple authors have studied world class manufacturing (WCM), no paper consolidates these results. Further certain inconsistencies are found in existing WCM frameworks. A need was therefore felt to clearly identify and define the scope of best manufacturing practices identified from different countries and industries. 173 research papers on WCM were collected from different online databases and reviewed for the purpose of this study. A descriptive analysis was performed to understand the timeline, geographic, author and journal related trends of the papers. Papers were also classified based on content and industry settings. The best practices identified were defined and the popularity of each best practice was evaluated on the basis of number of mentions. The paper finally proposes a new framework for WCM, inspired from the functioning of the human body.