{"title":"通过控制副产品的可持续和灵活的生产来减少污染","authors":"D. Yadav, R. Singh, A. Kumar, B. Sarkar","doi":"10.3808/jei.202200476","DOIUrl":null,"url":null,"abstract":"Every manufacturing system produces toxic by-products that cause a hazardous impact on society and the environment. As a result, pollution control authorities’ role has gained importance for the betterment of society and the preservation of a clean and green environment. As a result, one of the goals of this research is to develop a sustainable smart manufacturing model with less waste and controlled pollution. Here, a flexible production process is discussed under imprecise market conditions with partial backlogging and rework. Two different sustainable production models are presented here by considering pollution control costs. A sustainable production model with variable pollution costs is examined under the influence of three pollution control mechanisms to improve the model’s applicability. A solution methodology, including three critical theorems, is provided to obtain the optimal production rate, length, and total cost per cycle. The paper’s novelty lies in introducing pollution control costs and pollution control mechanisms together in a flexible, sustainable production system with uncertainty. In comparison to the other models, the model with a variable pollution cost appears to be more sustainable as, in this case, there is a 25.5% reduction in the pollution level compared to the other models. Implementing three pollution-controlling strategies, such as pollution cap, pollution cap and trade, and pollution tax, resulted in reductions of 34.37, 0.83, and 0.62% in pollution levels, respectively. A sensitivity analysis of the obtained results is carried out to show the model’s strength and robustness.\n","PeriodicalId":54840,"journal":{"name":"Journal of Environmental Informatics","volume":"47 2","pages":""},"PeriodicalIF":6.0000,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reduction of Pollution through Sustainable and Flexible Production by Controlling By-Products\",\"authors\":\"D. Yadav, R. Singh, A. Kumar, B. Sarkar\",\"doi\":\"10.3808/jei.202200476\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Every manufacturing system produces toxic by-products that cause a hazardous impact on society and the environment. As a result, pollution control authorities’ role has gained importance for the betterment of society and the preservation of a clean and green environment. As a result, one of the goals of this research is to develop a sustainable smart manufacturing model with less waste and controlled pollution. Here, a flexible production process is discussed under imprecise market conditions with partial backlogging and rework. Two different sustainable production models are presented here by considering pollution control costs. A sustainable production model with variable pollution costs is examined under the influence of three pollution control mechanisms to improve the model’s applicability. A solution methodology, including three critical theorems, is provided to obtain the optimal production rate, length, and total cost per cycle. The paper’s novelty lies in introducing pollution control costs and pollution control mechanisms together in a flexible, sustainable production system with uncertainty. In comparison to the other models, the model with a variable pollution cost appears to be more sustainable as, in this case, there is a 25.5% reduction in the pollution level compared to the other models. Implementing three pollution-controlling strategies, such as pollution cap, pollution cap and trade, and pollution tax, resulted in reductions of 34.37, 0.83, and 0.62% in pollution levels, respectively. A sensitivity analysis of the obtained results is carried out to show the model’s strength and robustness.\\n\",\"PeriodicalId\":54840,\"journal\":{\"name\":\"Journal of Environmental Informatics\",\"volume\":\"47 2\",\"pages\":\"\"},\"PeriodicalIF\":6.0000,\"publicationDate\":\"2022-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Environmental Informatics\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.3808/jei.202200476\",\"RegionNum\":1,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Environmental Informatics","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.3808/jei.202200476","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Reduction of Pollution through Sustainable and Flexible Production by Controlling By-Products
Every manufacturing system produces toxic by-products that cause a hazardous impact on society and the environment. As a result, pollution control authorities’ role has gained importance for the betterment of society and the preservation of a clean and green environment. As a result, one of the goals of this research is to develop a sustainable smart manufacturing model with less waste and controlled pollution. Here, a flexible production process is discussed under imprecise market conditions with partial backlogging and rework. Two different sustainable production models are presented here by considering pollution control costs. A sustainable production model with variable pollution costs is examined under the influence of three pollution control mechanisms to improve the model’s applicability. A solution methodology, including three critical theorems, is provided to obtain the optimal production rate, length, and total cost per cycle. The paper’s novelty lies in introducing pollution control costs and pollution control mechanisms together in a flexible, sustainable production system with uncertainty. In comparison to the other models, the model with a variable pollution cost appears to be more sustainable as, in this case, there is a 25.5% reduction in the pollution level compared to the other models. Implementing three pollution-controlling strategies, such as pollution cap, pollution cap and trade, and pollution tax, resulted in reductions of 34.37, 0.83, and 0.62% in pollution levels, respectively. A sensitivity analysis of the obtained results is carried out to show the model’s strength and robustness.
期刊介绍:
Journal of Environmental Informatics (JEI) is an international, peer-reviewed, and interdisciplinary publication designed to foster research innovation and discovery on basic science and information technology for addressing various environmental problems. The journal aims to motivate and enhance the integration of science and technology to help develop sustainable solutions that are consensus-oriented, risk-informed, scientifically-based and cost-effective. JEI serves researchers, educators and practitioners who are interested in theoretical and/or applied aspects of environmental science, regardless of disciplinary boundaries. The topics addressed by the journal include:
- Planning of energy, environmental and ecological management systems
- Simulation, optimization and Environmental decision support
- Environmental geomatics - GIS, RS and other spatial information technologies
- Informatics for environmental chemistry and biochemistry
- Environmental applications of functional materials
- Environmental phenomena at atomic, molecular and macromolecular scales
- Modeling of chemical, biological and environmental processes
- Modeling of biotechnological systems for enhanced pollution mitigation
- Computer graphics and visualization for environmental decision support
- Artificial intelligence and expert systems for environmental applications
- Environmental statistics and risk analysis
- Climate modeling, downscaling, impact assessment, and adaptation planning
- Other areas of environmental systems science and information technology.