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Author: search.filters.author.Sangwan, Kuldip SinghSubject: search.filters.subject.Decision support systems

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    Uncertainty analysis of workpiece orientation: a mathematical decision support system for circular geometry measurements
    (Elsevier, 2025-06) Sangwan, Kuldip Singh
    The article aims at quantifying and controlling the measurement uncertainties contributed by the workpiece orientation during the automated inspection of a circular geometry by using Coordinate Measuring Machines. The paper proposes a mathematical model to compute angular error and circular variance to quantify and minimize the measurement uncertainty associated with the workpiece orientation. The proposed methodology involves part programming, acquisition of the raw coordinate data points through experiments, identification of the potential factors influencing measurement results, development of the mathematical model to estimate and correct measurement uncertainties, and finally supports the user to minimize the variations in the measurement results. It was found that diameter, circularity and centroid measurements are affected by the workpiece orientation and probe start position has a significant effect on the measurement results. The proposed model reduced uncertainties as the data tends to spread uniformly along the geometric feature. The overall measurement results improved by 12 %.
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    Development of a Decision Support System for 3D Printing Processes based on Cyber Physical Production Systems
    (Elsevier, 2021) Sangwan, Kuldip Singh
    3D printing, an additive manufacturing (AM) technology, potentially provides sustainability advantages such as less waste generation, lightweight geometries, reduced material and energy consumption, lower inventory waste, etc. This paper proposes a decision support system for the 3D printing process based on Cyber Physical Production System (CPPS). The user is enabled to dynamically assess the carbon footprint based on the energy and material usage for their 3D printed object. A CPPS framework for the environmental sustainability of the 3D printing process is presented, which supports the derivation of improved strategies for product design and production. A physical world for 3D printing is used with the internet of things (IoT) devices like sensor node, webcam, smart plugs, and raspberry pi to host printer Management Software (PMS) for real-time monitoring and control of material and energy consumption during the printing process. Experiments have been conducted based on Taguchi L9 orthogonal array with polylactic Acid (PLA) as a filament material to estimate the product-related manufacturing energy consumption with the carbon footprint. The proposed framework can be effectively used by the users to supports the decision-making process for saving resources and energy; and minimizing the effect on the environment.
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    Evaluation of manufacturing systems based on environmental aspects using a multi-criteria decision model
    (Inder Science, 2013-04) Sangwan, Kuldip Singh
    With growing awareness of environmental issues, business and government have come under increasing pressure to reduce the environmental impacts involved in the production and consumption of goods and services. However, the evaluation of manufacturing systems from environmental perspective has often been neglected partly because of multifaceted criteria. This paper presents a criteria catalogue and a multi-criteria decision model for the evaluation of manufacturing systems based on environmental aspects of the manufacturing system. The methodology has been validated by a case study of Indian industry.
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    A fuzzy-based decision support framework for product recovery process selection in reverse logistics
    (Inder Science, 2016-11) Sangwan, Kuldip Singh
    Owing to the increasing attention to sustainability and green manufacturing as well as the legislations and competition, product recovery management has become an important issue to extend the product's life. It is an environmentally, economically and socially sound way to achieve many of the goals of sustainable development. In this paper, a fuzzy-based multi-criteria decision making framework has been proposed for the evaluation of alternate product recovery processes. The evaluation has been done based on the criteria of operating cost, value added recovery, environmental impact, market demand, technical/operational feasibility, and corporate social responsibility. The five alternative product recovery processes identified in the study are repair, refurbishing, remanufacturing, cannibalising, and recycling. The novelty of the framework is that it takes care of the inherent uncertainties in reverse logistics environment; and managers can provide different weights to different criteria depending upon the company strengths, weaknesses, opportunities and threats in the business environment.