Department of Mechanical engineering

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Author: search.filters.author.Sangwan, Kuldip SinghSubject: search.filters.subject.Sustainability

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Now showing 1 - 10 of 10
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    A sustainability assessment framework for cement industry – a case study
    (Emerald, 2019-02) Digalwar, Abhijeet K.; Sangwan, Kuldip Singh
    The purpose of this paper is to develop a framework and key performance indicators (KPIs) to assess the sustainability of the manufacturing organizations along the integrated supply chain.
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    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.
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    Integrated Lean Management System for Sustainable Development: A Conceptual Model
    (Excel Publishers, 2011) Sangwan, Kuldip Singh
    Sustainability manufacturing practices like lean and green manufacturing seek to optimize production efficiency while minimizing environmental impact and maintaining social equity. It is also well knowing fact that company that adopt sustainable practices are able to achieve better quality, improved productivity and profitable growth. Among these lean is an important practice that leads us towards sustainability initiatives by eliminating waste at all levels in system and using the resources efficiently. In this paper an integrated lean sustainability development model has been proposed to integrate supplier, organization and customer.
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    Supply chain resilience and its key performance indicators: an evaluation under Industry 4.0 and sustainability perspective
    (Emerald, 2023-05) Sangwan, Kuldip Singh
    Creating visibility in the supply chain (SC) helps in making it resilient. Integrating the SC with Industry 4.0 key enabling technologies creates visibility and sustainability in SCs. It also fosters intelligent decision-making, thereby making a SC smart. However, how Industry 4.0 technologies affect key performance indicators (KPIs) of a resilient SC and may help achieve sustainability is rarely studied.
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    Life Cycle Assessment of Smithy Training Processes
    (Elsevier, 2013) Sangwan, Kuldip Singh; Digalwar, Abhijeet K.
    Sustainability has long been a part of social responsibility. Today sustainability is a part of the core business strategies. It is viewed with environmental and economic perspectives. India, being a manufacturing hub has to deal with the problem of environmental and social impacts of these manufacturing operations. Smithy operations have large adverse impact on the environment. Life-cycle analysis should be applied to alleviate and reflect environmental burdens of this process. This paper presents the basic concepts of sustainability and life cycle analysis. A study has been carried out in the context of smithy training process. Software tool Umberto 5.6 with eco-invent 2.2 database is used for analysis. The effect of smithy training in term of acidification potential, climate change, eutrophication potential, freshwater aquatic, eco-toxicity, marine aquatic eco- toxicity, human toxicity, ionizing radiation, land use, photochemical Ox (smog), and stratospheric ozone depletion.
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    A Comparative Study on the Life Cycle Assessment of a 3D Printed Product with PLA, ABS & PETG Materials
    (Elsevier, 2022) Sangwan, Kuldip Singh
    Sustainability aims to meet the demands of the present generation as well as improve the quality of life, develop the economy, conserve resources, and protect the environment for the future generations. Additive manufacturing is one of the techniques to achieve sustainability in manufacturing. Life cycle assessment is a useful tool to ensure viability and applicability of new technology and assess whether it offers tangible benefits compared to conventional methods. There is hardly any comparative study on the life cycle assessment of the widely used filament materials. This research compares the environmental impacts of widely used filament materials (PLA, ABS, and PETG) for a 3D printed product from cradle to cradle that includes four phases: raw material extraction, production, use and recycling. Environmental impacts and hotspots in terms of both endpoint and midpoint categories have been estimated. The research provides decision support for stakeholders to compare the environmental impacts of different materials and accordingly select the most environmentally friendly material.
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    An integrated fuzzy multi-criteria evaluation of sustainable reverse logistics network models
    (IEEE, 2013) Sangwan, Kuldip Singh
    Reverse logistics is an environmentally and economically sound way to achieve many of the goals of sustainable development. Implementing reverse logistics is a strategic decision, requiring evaluation of a broad set of criteria. Various network models are available based on the trade off considerations at collection, sorting/testing and processing. This paper proposes an integrated fuzzy multi-criteria decision making (FMCDM) model for network selection by introducing the triple bottom line of sustainability. Fuzzy AHP is used to calculate the weight of economic, environmental, and social aspects of sustainability and fuzzy TOPSIS is used for ranking the alternative network models. The model is demonstrated by an example.
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    The Influence of Manufacturing Plant Site Selection on Environmental Impact of Machining Processes
    (Elsevier, 2019) Sangwan, Kuldip Singh
    Sustainability has become an important aspect in the strategic planning of manufacturing organizations due to rising energy cost, climate change, environmental emissions, and carbon tax policies. Most of the large manufacturing organizations have a worldwide network of factories, which is mainly driven by financial and political aspects. In past few decades, many attempts have been made to improve the sustainability of the manufacturing processes with consideration of carbon efficiency, energy efficiency, and cost effectiveness. The influence of the manufacturing plant site on the environmental sustainability of the manufacturing process is not considered in most site selection decisions despite its importance in improving the sustainability of production networks. This paper investigates the site based factors to influence the environmental sustainability of a machining process and the effect of these factors is analyzed using life cycle assessment. A case study is conducted with eight different cases based on the location of raw material, manufacturing site, and customers in India and Germany. Four key influencing factors are identified and the environmental impact of the milling process is assessed. One of the key findings is the significant influence of climate and the supply chain on the environmental sustainability of the machining process. This study can be used to include the environmental performance of the machining process into the strategic planning of new manufacturing plants.
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    Sustainability Assessment Framework for Manufacturing Sector – A Conceptual Model
    (Elsevier, 2018) Sangwan, Kuldip Singh; Digalwar, Abhijeet K.
    There is lack of structured methodological frameworks to assess sustainability of manufacturing organizations. The effective sustainability assessment is a challenge for manufacturers, researchers and governments. This paper proposes a hierarchical framework for sustainability assessment of manufacturing organizations. The proposed framework consists elements/performance measures to improve and assess the organizational policies, people, products, processes, and performance from triple bottom line perspective. The sustainability assessment captures the whole supply chain of the organization including end of life strategies for products. The framework has been tested using data from a cement manufacturing organization. A model of framework performance measures/elements has been developed using interpretive structure modelling (ISM).
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    Optimization of Machining Parameters for Improving Energy Efficiency using Integrated Response Surface Methodology and Genetic Algorithm Approach
    (Elsevier, 2017) Sangwan, Kuldip Singh; Garg, Girish Kant
    Machine tools consume enormous amount of energy during machining, build-up to machining, post machining and idling condition to drive motors and auxiliary equipments in the manufacturing system. Reduction of energy consumption during the machining phase is extremely important to improve the environmental performance over the entire life cycle. This paper presents a predictive and optimization model based on integrated response surface methodology and genetic algorithm approach to predict the energy consumption and the corresponding machining parameters during the turning of AISI 1045 steel with a tungsten carbide tool. Experiments using Taguchi design are performed to develop the predictive model. The developed predictive model is used to formulate the objective function for genetic algorithm. The confirmation experiments are performed to validate the developed model and the results are found within 4% error. The statistical significance of the developed model has been tested by the analysis of variance test. This research will be beneficial for a number of manufacturing industries for selection of machine tools on the basis of energy consumption. The reduction of peak load through optimization will results in lowering the energy consumption of the machine tools during non-cutting time