Browsing by Author "Sangwan, Kuldip Singh"

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21st-century competencies in engineering education: initiation, evolution, current, and now whither to
(Universitat Politècnica de Catalunya, 2022) Sangwan, Kuldip Singh; Sangwan, Devika
The fibre of engineering education has evolved from knowledge to competencies. This is a logical consequence of the technologically advanced and multifaceted learning environment where engineers are expected to be technically acute along with a set of essential non-technical competencies. This change is referred to as a ‘paradigm shift’ in engineering education. Hence, the vision of learning is to immerse a progressive, learner-centric, and competency-based learning environment to face the uncertainties of the 21st century
Adoption of green practices throughout the supply chain: an empirical investigation
(Emerald, 2019-07) Sangwan, Kuldip Singh
There is a dichotomy in the actual and expected environmental performances of the Indian enterprises even though the Indian enterprises have aligned their businesses with intended nationally determined contributions (INDC) targets. The purpose of this paper is to analyze the supply chain of Indian enterprises to understand influences to adopt green practices throughout the supply chains, and how these green practices influence economic, operational and environmental performances to reveal the underlying currents explaining difference in actual and expected performance
Adoption of Integrated Lean-Green-Agile Strategies for Modern Manufacturing Systems
(Elsevier, 2017) Sangwan, Kuldip Singh
Ever increasing customer choices, environmental concerns and competitiveness among manufacturers across the globe has engaged the industry to embrace newer manufacturing strategies. Predominantly, there are three dimensions to modern manufacturing systems viz. economic, environmental and social. The integration of lean-green-agile manufacturing strategies would be a complete and comprehensive manufacturing system which is the need of the 21st century. The adoption of Lean-Green-Agile Manufacturing System (LGAMS) would be facilitated by few enablers. The influence of these enablers is a matter of investigation which is addressed by the present study. An attempt has been made to prioritize the facilitating capacity of each enabler. The outcome of the research would facilitate the policy makers in the industry and government to frame policies.
Analysis of Barriers to Industry 4.0 adoption in Manufacturing Organizations: an ISM Approach
(Elsevier, 2021) Sangwan, Kuldip Singh
Industry 4.0 has enabled technological integration of cyber physical systems and internet based communication in manufacturing value creation processes. As of now, many people use it as a collective term for advanced technologies, i.e. advanced robotics, artificial intelligence, machine learning, big data analytics, cloud computing, smart sensors, internet of things, augmented reality, etc. This substantially improves flexibility, quality, productivity, cost, and customer satisfaction by transforming existing centralized manufacturing systems towards digital and decentralized one. Despite having potential benefits of industry 4.0, the organizations are facing typical obstacles and challenges in adopting new technologies and successful implementation in their business models. This paper aims to identify potential barriers which may hinder the implementation of industry 4.0 in manufacturing organizations. The identified barriers, through comprehensive literature review and on the basis of opinions collected from industry experts, are: poor value-chain integration, cyber-security challenges, uncertainty about economic benefits, lack of adequate skills in workforce, high investment requirements, lack of infrastructure, jobs disruptions, challenges in data management and data quality, lack of secure standards and norms, and resistance to change. Interpretive Structural Modeling (ISM) is used to establish relationships among these barriers to develop a hierarchical model and MICMAC analysis for further classification of identified barriers for better understanding. An analysis of driving and dependence of the barriers may help in clear understanding of these for successful implementation of Industry 4.0 practices in the organizations.
An analysis of energy consumption and carbon footprints of cryptocurrencies and possible solutions
(Elsevier, 2023-02) Chamola, Vinay; Sangwan, Kuldip Singh
There is an urgent need to control global warming caused by humans to achieve a sustainable future. CO2 levels are rising steadily, and while countries worldwide are actively moving toward the sustainability goals proposed during the Paris Agreement in 2015, we are still a long way to go from achieving a sustainable mode of global operation. The increased popularity of cryptocurrencies since the introduction of Bitcoin in 2009 has been accompanied by an increasing trend in greenhouse gas emissions and high electrical energy consumption. Popular energy tracking studies (e.g., Digiconomist and the Cambridge Bitcoin Energy Consumption Index (CBECI)) have estimated energy consumption ranges from 29.96 TWh to 135.12 TWh and 26.41 TWh to 176.98 TWh, respectively for Bitcoin as of July 2021, which are equivalent to the energy consumption of countries such as Sweden and Thailand. The latest estimate by Digiconomist on carbon footprints shows a 64.18 MtCO2 emission by Bitcoin as of July 2021, close to the emissions by Greece and Oman. This review compiles estimates made by various studies from 2018 to 2021. We compare the energy consumption and carbon footprints of these cryptocurrencies with countries around the world and centralized transaction methods such as Visa. We identify the problems associated with cryptocurrencies and propose solutions that can help reduce their energy consumption and carbon footprints. Finally, we present case studies on cryptocurrency networks, namely, Ethereum 2.0 and Pi Network, with a discussion on how they can solve some of the challenges we have identified.
Antecedents of a Resilient Sustainable Supply Chain
(Elsevier, 2023) Sangwan, Kuldip Singh
These days resilience and sustainability have become critical supply chain measures. Supply chain resiliency is being given top priority by the industry as well as the governments due to prolonged disruptions because of Covid-19 pandemic and geo-political uncertainties. The literature on this topic is largely focused on supply chain network design taking resiliency and sustainability into consideration. Even some researchers have found the antecedents of resilient sustainable supply chains (RSSC), but this research is largely segregated for a single or a few elements. There is a need to amalgamate the various antecedents of RSSC, find their weightage and interrelationship among them. This paper identifies seven antecedents of a RSSC from literature – visibility, flexibility, collaboration, control, circularity, digitalization, and network design. A fuzzy DEMATEL approach is used to find the causal relationship among these seven antecedents. Further, the weightage and ranks of these antecedents were found using multi criteria decision models. The findings of the study can be used by various researchers and practitioners for determining the importance and interrelationship of these elements in their organizations, which can be leveraged for strategic and operational decisions for effective management of supply chain disruptions.
An application of value stream mapping in auto-ancillary industry: A case study
(Emerald, 2020-01) Sangwan, Kuldip Singh; Jasti, Naga Vamsi Krishna; Kota, Srinivas
Lean manufacturing (LM) plays a major role in eliminating wastes (activities/resources) in a manufacturing organization. Value stream mapping (VSM) is one of the critical tools in LM which will help in identifying wastes in materials and information flow in a specific product family. The purpose of this paper is to illustrate the significance of VSM in the auto-ancillary industry in enhancing the productivity and the quality.
Assessment of Alternative Propulsion Systems for Vehicles
(Springer, 2011-01) Sangwan, Kuldip Singh
Concern for the environment, the approaching end of fossil fuels and the dependence on oil exporting countries has revived the interest in alternative propulsion systems for vehicles. However, an assessment of alternative propulsion systems with respect to sustainability is very complex due to the variety of technologies as well as unsecure and conflicting economic, ecological and social consequences. This study provides a framework for assessing alternative propulsion systems for vehicles using the AHP methodology. A criteria catalogue is derived from existing approaches and the analysis of propulsion systems, their market situation and surrounding conditions. Its application is illustrated by the assessment of two exemplary propulsion systems.
Assessment of hierarchy and inter-relationships of barriers to environmentally conscious manufacturing adoption
(Emerald, 2013-10) Sangwan, Kuldip Singh
The purpose of this paper is to develop hierarchy and inter-relationship among barriers to environmentally conscious manufacturing (ECM) adoption using an interpretive structural modeling (ISM) technique. The paper will demonstrate how ISM supports policy makers in the government and industry in identifying and understanding interdependencies among barriers to ECM. Interdependencies among barriers will be derived and structured into a hierarchy in order to derive subsystems of interdependent elements with corresponding driving power and dependency.
Benchmarking environmental performance of electric insulator supply chain in India using life cycle assessment
(Springer, 2018-03) Sangwan, Kuldip Singh
This study aims at finding the environmental impacts generated by an electric disk insulator supply chain, used for the distribution of electricity by an open wire system, through a case study. This study also aims at benchmarking the environmental impacts of an electric insulator manufacturing process by taking ideal condition of zero waste as reference.
Benchmarking Indian ceramic enterprises based on green supply chain management pressures, practices and performance
(Emerald, 2018-11) Sangwan, Kuldip Singh
The purpose of this paper is to identify and analyze the impact of green supply chain management (GSCM) pressures, implementation level of GSCM practices and improvement in performance of the Indian ceramic enterprises. The paper also aims at benchmarking the Indian ceramic enterprises based on enterprise size and market orientation (export activity).
Benchmarking manufacturing industries based on green practices
(Emerald, 2018-08) Sangwan, Kuldip Singh
The purpose of this paper is twofold: first, to develop a statistically reliable and valid model of performance measures (PMs) to observe the environmental behavior of different enterprises; second, at benchmarking the enterprises based on their green practices.
A bibliometric analysis of green manufacturing and similar frameworks
(Emerald, 2015-06) Sangwan, Kuldip Singh
The purpose of this paper is to review the green manufacturing and similar frameworks in order to trace the origin, definitions, scope, similarities, differences, and publications of these manufacturing frameworks.
A Bibliometric Analysis of Sustainable Supply Chain Management: Research Implications and Future Perspectives
(Springer, 2021-11) Sangwan, Kuldip Singh
Sustainable supply chain (SSC) is an emerging research area that focuses on the triple bottom line pertaining to all stakeholders and related activities. Important Business decisions relevant processes, and activities are focused on features in SSC articles. Using the bibliometric techniques, the author attempted to analyze the research area's impact, its associated eminent authors, along with their affiliated institutions and countries. Through conducting network analysis in VOSviewer software and Gephi software researchers focus on co-authorship, author specified keywords clustering, and countries-based bibliographic analysis. The research identifies the most influential research work/authors in the defined duration. Using network analysis, authors can identify knowledge groups their affiliations, and future research opportunities. In contrast to the existing literature, the author here used keywords occurrence as a criterion for clustering. The identified clusters define the research themes and keyword occurrence helps in identifying future research implications.
A Blockchain Technology based Framework for Environmental and Social Impact Authenticity of a 3D Printed Product
(Elsevier, 2023) Sangwan, Kuldip Singh; Dua, Amit
This paper proposes a conceptual framework for implementing blockchain technology to enhance traceability, transparency, and authenticity of a 3D printed product. An implementation framework is developed using blockchain technologies to record and trace critical attributes during the various life cycle phases of a 3D printing value chain, viz. raw material extraction, chemical processing, polymerization, filament production, 3D printing, and end-of-life recycling of the product. The information on critical attributes of carbon footprint, workers' age, and material flow during the entire value chain is captured to provide authentic output of carbon footprint and labour age during any of the value chain activity. The uniqueness of the current work lies in offering a series of immutable transactions using blockchain technology to comprehend the circularity of 3D printing material and account for the overall carbon footprint produced by a 3D printed product considering its whole value chain. This would improve the traceability and visibility of the material supply chain for 3D printing. On the hindsight, the proposed framework is expected to assist the manufacturing firms to act as responsible manufacturers by providing the authentic data for the computation of environmental assessment as well as social issues of child labour throughout the value chain.
Blockchain-enabled solution for transparency and waste minimization in pharmaceutical supply chains
(Elsevier, 2025) Sangwan, Kuldip Singh; Kulshrestha, Rakhee
The pharmaceutical supply chain is a complex network involving multiple stakeholders and processes, making it susceptible to various inefficiencies and challenges such as counterfeiting, drug expiry, and inefficient inventory management. These challenges may lead to compromised patient safety and financial losses. Blockchain technology is a promising solution to these problems. This study develops a blockchain-enabled mathematical model for pharmaceutical supply chains. A distributed ledger is used to acquire the real-time drug transaction status throughout the supply chain. The study uses real-time data gathered from the distributed ledgers across the supply chain, ensuring optimum inventory with the minimization of expired drugs and transportation costs. By leveraging the proposed model, stakeholders can eliminate counterfeiting, reduce drug expiry, and ultimately ensure the integrity and safety of pharmaceutical products throughout their lifecycle. This model also helps manufacturers in decision making for drug manufacturing based on real-time data. Novelty of the study lies in real-time tracing and managing the drugs across the supply chain.
Bridging the Qualification Gap between Academia and Industry in India
(Elsevier, 2017) Sangwan, Kuldip Singh
The massive demand for complementary training of engineering graduates in India indicates a mismatch between academic education and industry requirements. This paper identifies the gap between academia and industry and presents an approach to bridge it using the concept of Learning Factories. The competencies of the newly graduate engineers and the competency requirements of Indian industry for graduates have been identified based on discussions with industry professionals and literature review. It has been found that the technical and social competency requirements match, but there is a gap regarding the methodological competency. This necessitates graduate engineer trainings at the start of employment. The additional trainings prove to be time consuming and costly for the industry. To bridge this gap a Learning Factory test bed has been implemented at a premier Indian university. It is expected that the proposed Learning Factory will make the Indian graduate engineers ready for the job at university level and the additional graduate engineer training redundant. The study also provides a roadmap of utilizing Learning Factories as an integral part for the Indian technical academic system.
Closed loop supply chain network design and optimisation using fuzzy mixed integer linear programming model
(Taylor & Francis, 2013-12) Sangwan, Kuldip Singh
Owing to the revolution in sustainable and green manufacturing the production planning and network design of closed loop supply chain concept has got the attention of researchers and managers. In this paper, a multi-product, multi-facility capacitated closed-loop supply chain framework is proposed in an uncertain environment including reuse, refurbish, recycle and disposal of parts. The uncertainty related to demand, fraction of parts recovered for different product recovery processes, product acquisition cost, purchasing cost, transportation cost, processing, and set-up cost is handled with fuzzy numbers. A fuzzy mixed integer linear programming model is proposed to decide optimally the location and allocation of parts at each facility and number of parts to be purchased from external suppliers in order to maximise the profit of organisation. The proposed solution methodology is able to generate a balanced solution between the feasibility degree and degree of satisfaction of the decision maker. The proposed model has been tested with an illustrative example.
A cognitive digital twin for process chain anomaly detection and bottleneck analysis
(Taylor & Francis, 2024-07) Sangwan, Kuldip Singh
Bottleneck detection and management plays a significant role in the context of Industry 4.0, wherein process chains have become more intricate. The dynamic nature of process chains shifts the bottleneck location, which requires an integrated methodology capable of identifying current as well as predicting future bottlenecks. The paper proposes a cognitive digital twin (CDT) with a novel explainable artificial intelligence (XAI) model. The proposed CDT is capable of (i) detecting existing bottlenecks, (ii) detecting data anomalies and process chain anomalies (iii) estimating shifting bottlenecks due to anomalies, (iv) predicting near future bottlenecks, and (v) the XAI model supports operational and strategic decision making. The usefulness of proposed CDT is demonstrated and validated experimentally on an industry 4.0 compliant learning factory. The proposed novel CDT effectively addresses the process chain bottlenecks (existing, shifting, and future) while the XAI model enhances transparency and trustworthiness for practical implementation.
Comparative Analysis for Solar Energy Based Learning Factory: Case Study for TU Braunschweig and BITS Pilani
(Elsevier, 2018) Sangwan, Kuldip Singh
Now day's solar energy is widely used for replacing the conventional sources of energy for power generation. The electrical power could be generated from photovoltaic (PV) systems. With this approach, an attempt has been made to address the possibility to use solar energy systems for running a learning factory(s) (LF) in Technische Universität (TU), Braunschweig, Germany. For this, the energy consumption of each component of learning factory has been measured experimentally at various operating conditions like idle, loading, and unloading. The same analysis has been carried out for the components of LF at BITS Pilani followed by performing a comparative analysis. It is observed that the solar energy based LF system will works better in Pilani due to higher solar insolation and 300 number of sunny days. In the end, the economic analysis to replace the conventional system with solar system is carried out followed by assessment of carbon emissions of the LF components for two types of electricity. It was found out that the payback period comes out to be 15.7 years and 9.1 years for Pilani and Braunschweig respectively with 6-hours battery backup.