BITS Faculty Publications
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Item Modelling factors influencing charging station location selection to accelerate ev adoption in India: an ISM-MICMAC analysis(Springer, 2023-12) Digalwar, Abhijeet Kumar; Routroy, SrikantaElectric vehicles (EVs) are rising fast to prominence as a key component of the effort to meet sustainable energy goals. The research and mass manufacturing of new energy vehicles, especially electric vehicles, offer several benefits over conventional energy vehicles, such as zero exhaust emissions, zero pollution, cleanliness, and low cost. As a result, more and more nations are paying attention and placing importance over the development of EV-fleet, but EV sales are still a modest part of all vehicle sales. The protruding reason highlighted by the literature and researchers is underdeveloped charging infrastructure. To get the most out of an EV, an appropriate charging station with optimum configuration needs to be placed in a specific location with all the infrastructure to make it supportive and sustainable hotspot for EVs. This study aims to identify all the factors that needs to be considered while selecting a location for setting up a sustainable charging station for EVs in semi-urban areas. A deeper understanding of factors is explored, using interpretive structural modelling (ISM) and MICMAC analysis. A total of 17 factors are considered for the analysis which are crucial in developing the configurations for an EV charging station. The outcomes of the paper will support the policymakers to locate, determine and decide the suitable locations, and configuration for constructing EV charging stations and escalate the EV adoption.Item A data-driven framework for optimizing multi-period ev charging infrastructure deployment(IEEE, 2024-12) Digalwar, Abhijeet Kumar; Routroy, SrikantaThe rise of electric vehicles represents a transformative shift in the automotive industry, signaling the dawn of a new era of clean, sustainable transportation, but their operation requires a distributed rapid-charging infrastructure. Building such rapid charging networks is currently capital-intensive and therefore, requires careful planning and the development of the charging infrastructure must be maintained. However, infrastructure construction is not a one-off investment but a multi-period plan. A multi-period location and capacity expansion model of the charging stations will be needed. This study proposes a novel data-driven framework for deploying suitable rapid-charging infrastructure for EVs in large urban areas. This study combines an iterative clustering technique with a geographical information system analysis tool to determine the suitable regions for developing an optimized EV charging service. The analysis intends to plan a case study for Gurugram City of India and suggest the locations that should be the potential points for consideration of charging station development.Item An integrated modelling and optimization approach for the selection of process parameters for variable power consumption machining processes(Springer, 2023-08) Routroy, Srikanta; Garg, Girish KantManufacturing industries are under intense pressure to reduce the energy usage of the machining processes without sacrificing productivity, owing to the fast-rising worldwide market and environmental issues. Variable-power consumption machining processes are highly complex than constant-power consumption machining processes, owing to change in one of the process parameters, i.e. cutting speed during end facing. Besides, integrated modelling and optimization of the variable power consumption machining processes for energy-saving have not received attention, consequently, industry deployment of energy-saving solutions is impeded. To bridge these gaps, in this work, the empirical model developed by the author is integrated for the formulation of a multi-objective optimization model of cutting energy consumption (Ecdry) and average-material removal rate (MRR¯¯¯¯¯¯¯¯¯¯¯¯) expressed by process parameters. First, the optimal parameters are determined for Ecdry and MRR¯¯¯¯¯¯¯¯¯¯¯¯ by mono-objective optimization using the Taguchi technique. Second, Grey relational analysis coupled with the Taguchi method is used to obtain the cumulative performance index of the Ecdry and MRR¯¯¯¯¯¯¯¯¯¯¯¯, and to determine their common optimal parameters, resulting in better-compromised decisions. The MRR¯¯¯¯¯¯¯¯¯¯¯¯ improves to 99.97% with only a 10.08% increase in Ecdry on common optimal parameters compared to optimal parameters with mono optimization of Ecdry. Further, analysis of variance revealed that all considered process parameters have statistical significance, and depth of cut is the most significant parameter followed by spindle speed, feed rate and tool nose radius. It was found that energy consumption values predicted by the integrated modelling and optimization approach are close to the experimental values.Item Application of Optimization and Statistical Techniques in Post-Harvest Supply Chain: A Systematic Literature Survey(CRC Press, 2021) Garg, Girish Kant; Routroy, SrikantaThe objective of this literature survey is to address the utility and potential of optimization, statistical surveys and mathematical research into post-harvest supply chains (PHSCs) to reduce losses. Empirical approaches have always helped to understand a generic issue with a specific perspective to highlight the shortcomings with the existing practice. The optimization approaches are used in the PHSC literature to design an optimum system to enhance revenues and to minimize losses. The existing PHSCs in developing countries such as India suffer enormous losses – e.g., revenue losses, physical damage of produce, microbial losses, qualitative losses, quantitative losses, etc. – in the absence of market prospects due to inefficient packaging for transportation and handling. This study covers a systematic literature survey covering the mathematical, statistical and optimization research performed in the field of PHSC and critical analysis to highlight the key aspects covered in the literature and their future scope.Item Fuzzy-TOPSIS based multi-objective optimization of machining parameters for improving energy consumption and productivity(Elsevier, 2021) Garg, Girish Kant; Routroy, SrikantaDue to the increasingly global market and environmental challenges, there is a lot of pressure on manufacturing industries to reduce the energy consumption of the machining process without compromising productivity. The objective of this work is to develop a multi-objective optimization model for the selection of optimal cutting parameters during the turning of an Aluminum workpiece using carbide inserts. Two performance characteristics: energy consumption and productivity were simultaneously optimized. The Taguchi full factorial orthogonal array L27 was used to obtain the experimental plan. The Fuzzy based Technique for Order Preference by Similarity to Ideal Solution (Fuzzy-TOPSIS) was applied to determine the optimal cutting parameters for multi-objective optimization. The optimal results obtained by Fuzzy-TOPSIS were further validated by using the Taguchi method. ANOVA results show that all the considered cutting parameters were statistically significant. Further, the depth of cut was found the most influencing cutting parameter on the energy consumption and productivity.Item Comparative analysis of environment losses in steel manufacturing supply chain using Taguchi loss function and design of experiments(Emerald, 2020-04) Routroy, SrikantaThe objective of this paper is to compare and evaluate the environmental performance of steel supply chains considering relevant environmental loss factors using Taguchi loss function (TLF) and design of experiments (DOE).Item ReValue project Report – Deliverable 1.2 - Logistics and Cold Chain Management Concepts - OC2020 A-094(SINTEF, 2020) Dasgupta, Mani Sankar; Routroy, SrikantaThis is a summarised report conveying deliverable D1.2 (i.e. Logistics and cold chain management task) of WP1 in the Revalue project. The results mentioned in this report have been derived from the proceedings communicated to the 25th IIR International Congress of Refrigeration, Montreal & 6th IIR Conference on Sustainability and the Cold Chain, Nantes. Food loss due to improper cold chain setups and underdeveloped logistics hold a significant role in any perishable food supply chain. Revamping the entire structure with a large-scale investment may provide a solution but the implementation of such a development is difficult due to highly fragmented supply chain (WP 1 report, 2019). This report explores the potentials of improving the cold chain and associated logistics which will lead to effectual improvements.Item Six Sigma Enablers for Incoming Material Quality Improvement and Their Interaction in Supplier Domain for Indian Manufacturing Scenario(Elsevier, 2021) Routroy, Srikanta; Pradhan, Sudeep Kumar; Reosekar, Ravi ShrikrishnaMaterial quality is the predominant factor in governing competition in the existing supply chain. Hence, the right quality product at a competitive price has ever existed as it is now. Though the end-users are exploiting maximum benefit from this scenario, the complete value chain is moving towards cost optimization without scarifying the product quality. Every value chain is trying to improve or at-least maintaining the status-quo by creating a strategic supplier relationship program where the close relationship with suppliers helps the organization to avoid the uncertainties related to response time, order stability and incoming material quality, which incidentally responsible for the quick product to market. The incoming materials quality from the supplier is largely governed by process capability at the supplier end with respect to the desired quality standard from the manufacturing organization. In this context, Six Sigma is a widely accepted practice used in the industry in recent days for process capability improvement. Many researchers have studied Six Sigma in various contexts as a process improvement benchmark tool. In this paper, seven Six Sigma enablers are identified and one of the major enabler related to supplier domain; i.e., Supplier management is discussed in detail. The enablers (Proximity, Supplier Performance, Leadership, External Environment, and Supplier Management) those are directly contributing towards supply management are identified, and their interaction is studied through a hypothesized model. Structural equation modeling (SEM) is performed to understand relationship strength among these enablers. The enablers like leadership and supplier performance, exhibit relationship strength at a moderate level with supplier management. The relationship strength for all other enablers is at the minor level yet significant. Mediation does not affect the relationship significantly.Item Exploitation of ReValue results - ReValue Project Deliverable 4.3(SINTEF, 2021) Routroy, Srikanta; Dasgupta, Mani Sankarhis report is a part of Deliverable 4.3 of Revalue project highlighting the exploitation potential of the solutions developed in the project to reduce losses in the surimi supply chain in India. ReValue solutions have the potential to achieve a huge market impact, drastically increasing the Surimi industry profitability. The average value of fish used for surimi will increase significantly if the Rest Raw Materials (RRM) can be utilized into food and feed ingredients. In addition, ReValue solutions contribute to quality enhancement through improvement in processes and in the cold chain, as well as the introduction of functional ingredients derived from RRM that can be used as nutritional supplements. Further exploitation should focus on the marketing of surimi derived products, increasing consumer awareness for wider acceptance of surimi and derived products from India in the European market.Item Enhancing supplier capability through Six Sigma enablers(Emerald, 2021-12) Routroy, Srikanta; Pradhan, Sudeep Kumar; Reosekar, Ravi ShrikrishnaThe purpose of this paper is to identify, analyze and orient the enablers of Six Sigma to enhance supplier capability for an Indian manufacturing supply chain (SC).