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"Gupta, Surendra M"
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Remanufacturing Modeling and Analysis
Providing a solid foundation of knowledge in modeling remanufacturing systems, this book addresses the design, planning, and processing issues faced by decision-makers in the field. With easy-to-use mathematical or simulation modeling to demonstrate solutions for each remanufacturing issue, it helps practitioners understand how a particular issue can be effectively modeled and how to choose the appropriate solution methodology. The book also discusses how increasingly stringent environmental regulations and decreasing natural resources influence manufacturers toward more environmentally conscious manufacturing and product recovery initiatives.
eBook
Status of BIPV and BAPV System for Less Energy-Hungry Building in India—A Review
The photovoltaic (PV) system is one of the most promising technologies that generate benevolent electricity. Therefore, fossil fuel-generated electric power plants, that emit an enormous amount of greenhouse gases, can be replaced by the PV power plant. However, due to its lower efficiency than a traditional power plant, and to generate equal amount of power, a large land area is required for the PV power plant. Also, transmission and distribution losses are intricate issues for PV power plants. Therefore, the inclusion of PV into a building is one of the holistic approaches which reduce the necessity for such large land areas. Building-integrated and building attached/applied are the two types where PV can be included in the building. Building applied/attached PV(BAPV) indicates that the PV system is added/attached or applied to a building, whereas, building integrated PV (BIPV) illustrates the concept of replacing the traditional building envelop, such as window, wall, roof by PV. In India, applying PV on a building is growing due to India’s solar mission target for 2022. In 2015, through Jawaharlal Nehru National Solar Mission, India targeted to achieve 100 GW PV power of which 40 GW will be acquired from roof-integrated PV by 2022. By the end of December 2019, India achieved 33.7 GW total installed PV power. Also, green/zero energy/and sustainable buildings are gaining significance in India due to rapid urbanization. However, BIPV system is rarely used in India which is likely due to a lack of government support and public awareness. This work reviewed the status of BIPV/BAPV system in India. The BIPV window system can probably be the suitable BIPV product for Indian context to reduce the building’s HVAC load.
Journal Article
Designing a sustainable green closed-loop supply chain under uncertainty and various capacity levels
The ever-increasing concerns of the growth in the volume of waste tires and new strict government legislations to reduce the environmental impact of the end-of-life (EOL) tires have increased interest among companies to design a sustainable and efficient closed-loop supply-chain (CLSC) network. In the real world, the CLSC network design is subject to a variety of uncertainties, such as random and fuzzy (epistemic) uncertainties. Designing a reliable and environmentally cautious CLSC with consideration of risks and the uncertainty of the parameters in the network is necessary for a successful supply-chain network. This study proposes a sustainable and environmentally cautious closed-loop supply-chain network for the tire industry, by considering several recovery options, including retreading, recycling, and energy recovery. This study aims to design and develop a robust multi-objective, multi-product, multi-echelon, multi-cycle, multi-capacity, green closed-loop supply-chain network under hybrid uncertainty. There are two types of uncertainties associated with the parameters in the network. There is an uncertainty associated with the demand, which is expressed in some future scenarios according to the probability of their occurrences, as well as fuzzy-based uncertainty associated with return rates, retreading rates, recycling rates, procurement, and production costs, which are expressed with possibilistic distributions. In order to deal with this hybrid uncertainty, a robust fuzzy stochastic programming approach has been proposed, and the proposed mixed integer programming model is applied to a case study in the tire industry to validate the model. The result indicates the applicability of the proposed model and its efficiency to control the hybrid uncertainties and the risk level in the network.
Journal Article
A Robotic-Driven Disassembly Sequence Generator for End-Of-Life Electronic Products
In this study, we propose an intelligent automated disassembly cell for online (real time) selective disassembly. The cell is composed of an industrial robotic manipulator, a camera, range sensing and component segmentation visual algorithms. The cell prototype allows for robotic sensory-driven disassembly under uncertainty. An online genetic algorithm model for selective disassembly is also proposed for optimal and near/optimal disassembly sequencing.
Journal Article
A hybrid genetic algorithm for sequence-dependent disassembly line balancing problem
For remanufacturing or recycling companies, a reverse supply chain is of prime importance since it facilitates in recovering parts and materials from end-of-life products. In reverse supply chains, selective separation of desired parts and materials from returned products is achieved by means of disassembly which is a process of systematic separation of an assembly into its components, subassemblies or other groupings. Due to its high productivity and suitability for automation, disassembly line is the most efficient layout for product recovery operations. A disassembly line must be balanced to optimize the use of resources (viz., labor, money and time). In this paper, we consider a sequence-dependent disassembly line balancing problem (SDDLBP) with multiple objectives that requires the assignment of disassembly tasks to a set of ordered disassembly workstations while satisfying the disassembly precedence constraints and optimizing the effectiveness of several measures considering sequence dependent time increments. A hybrid algorithm that combines a genetic algorithm with a variable neighborhood search method (VNSGA) is proposed to solve the SDDLBP. The performance of VNSGA was thoroughly investigated using numerous data instances that have been gathered and adapted from the disassembly and the assembly line balancing literature. Using the data instances, the performance of VNSGA was compared with the best known metaheuristic methods reported in the literature. The tests demonstrated the superiority of the proposed method among all the methods considered.
Journal Article
Utilization of Free Trade Agreements to Minimize Costs and Carbon Emissions in the Global Supply Chain for Sustainable Logistics
Background: Since global warming is a crucial worldwide issue, carbon tax has been introduced in the global supply chain as an environmental regulation for the reduction of greenhouse gas (GHG) emissions. Costs, GHG emissions, and carbon tax prices differ in each country due to economic conditions, energy mixes, and government policies. Additionally, multiple countries have signed a Free Trade Agreement (FTA). While FTAs result in their economic benefit, they also increase the risk of carbon leakage, which increases GHG emissions in the global supply chain due to relocation production sites from a country with stricter emission constraints to others with laxer ones. Method: This study proposes a mathematical model for decision support to minimize total costs involving carbon taxes with FTAs. Results: Our model determines suppliers, factory locations, and the number of transported parts and products with costs, FTAs, carbon taxes, and material-based GHG emissions estimated using the Life Cycle Inventory (LCI) database. The FTA utilization on the global low-carbon supply chain is examined by comparing the constructed supply chains with and without FTAs, and by conducting sensitivity analysis of carbon tax prices. Conclusions: We found that FTAs would not cause carbon leakage directly and would be effective for reducing GHG emissions economically.
Journal Article
Money-back guarantee warranty policy with preventive maintenance strategy for sensor-embedded remanufactured products
In today's global environment, technology is constantly evolving. Being able to stay up-to-date with the very latest technological advances can be extremely hard to accomplish. As a result of these changes and developments in technology, which often come unexpectedly, consumers are frequently tempted to update their devices to the very latest model. The result is that the life cycle of a product is becoming shorter and shorter than before. Manufacturers attempt to respond to consumers' concerns involving environmental issues as well as the more governmentally stringent environmental legislations by establishing facilities which include the minimization of the totality of waste relocated to landfills by recovering materials and components from returned, or End-Of-Life products and reuse them to build a remanufactured product, and/or novel components. With the rapid growth of interest in remanufactured products' market, offering warranty for remanufactured products and components is becoming a necessity for remanufacturer in order to meet customers' requirement and as a marketing mechanism. During that process, maintenance policies are of great importance in order to reduce the warranty cost on the remanufacturer. In this paper, an optimization simulation model for remanufactured items sold with one-dimensional non-renewing money-back guarantee (MBG) warranty policy is proposed from the view of remanufacturer, in which, an End-Of-Life product is subjected to upgrade action at the end of its past life and during the warranty period, preventive maintenance actions are carried out when the remaining life of the product reaches a pre-specified value so that the remanufacturer's expected profit can be maximized. Finally, a numerical example and design of experiment analysis are provided to demonstrate the proposed approach.
Journal Article
Evaluating the impact of sensor-embedded products on the performance of an air conditioner disassembly line
Increasing consumer awareness towards environmental issues and stricter environmental legislation have forced many manufacturers to set up facilities for product recovery which involves the minimization of the amount of waste sent to landfills by recovering materials and components from returned or end-of-life (EOL) products. Disassembly is an important process in product recovery since it allows for the selective separation of desired parts and materials. EOL products involving missing and/or nonfunctional components increase the uncertainty associated with disassembly yield. Testing, a common solution method, results in high costs. Moreover, if the component is found to be defective, the disassembly time is wasted. Sensor-embedded products (SEPs) can deal with this uncertainty by providing information on the condition of components prior to disassembly. This study evaluates the impact of SEPs on the various performance measures of an air conditioner (AC) disassembly line controlled by a multikanban system which effectively manages material flows considering the stochastic behavior of the disassembly line. First, separate design-of-experiments studies based on orthogonal arrays are carried out for conventional products (CPs) and SEPs. In order to calculate the response values for each experiment, detailed discrete-event simulation models of both cases are developed, considering the precedence relationships among the components of an AC. Then, pairwise
t
tests are conducted to compare two cases based on different performance measures. The test results show that SEPs improve revenue and profit while achieving significant reductions in backorder, disassembly, disposal, holding, testing, and transportation costs.
Journal Article
A Robust Robotic Disassembly Sequence Design Using Orthogonal Arrays and Task Allocation
Disassembly sequence planning (DSP) is a nondeterministic polynomial time (NP) complete problem, making the utilization of metaheuristic approaches a viable alternative. DSP aims at creating efficient algorithms for deriving the optimum or near-optimum disassembly sequence for a given product or a product family. The problem-specific nature of such algorithms, however, requires these solutions to be validated, proving their versatility in accommodating substantial variations in the problem environment. To achieve this goal, this paper utilizes Taguchi’s orthogonal arrays to test the robustness of a previously-proposed Simulated Annealing (SA) algorithm. A comparison with an exhaustive search is also conducted to verify the efficiency of the algorithm in generating an optimum or near-optimum disassembly sequence for a given product. In order to further improve the solution, a distributed task allocation technique is also introduced into the model environment to accommodate multiple robot arms.
Journal Article