Sustainable Manufacturing Systems Using Big Data

Dear Colleagues,

Nowadays, there is a great deal of concern and interest in environmental sustainability with regard to carbon emissions, global warming and toxic hazes. In addition to environmental pollution, the social sustainability agenda of improving the quality of human life is particularly important. Simultaneous consideration of environmental and social factors, in addition to the financial costs, aims to meet the standards of global sustainable development. A sustainable design and manufacturing process for the manufacturing industry not only reduces financial costs, but also minimizes massive amounts of carbon emissions and waste energy in addition to maximizing the social factors. The problem of large amounts of carbon emissions and energy waste caused by the design and manufacturing industry is a wide concern across the world and deciding how to find a sustainable design to address the financial, environmental and social factors is one of the primary issues in modern society.

Currently, many new technologies, such as energy-efficient cloud computing, energy internet, big data and knowledge management, have been integrated and widely applied to facilitate many national advanced design and manufacturing strategies. One of their common aims is to achieve smart design and manufacture, which is of great significance for sustainable development. However, without data support, and the support of data science and technology, “smart” cannot be achieved. However, the type of design and manufacturing that big data will generate in the entire lifecycle of a product is still unclear. Furthermore, deciding how to collect the useful data, as well as the extraction and utilization of useful information from such huge and dynamic databases for “big data”, is frightening. This has motivated researchers and practitioners to explore new methods and technologies for industrial applications of big data in sustainable design and manufacture.

This Special Issue of Applied Science solicits high-quality contributions that focus on the design and development of novel algorithms, technologies, and tools to address sustainable design and manufacture using big data. Topics of interest include but are not limited to:

• Sustainable design methodologies and manufacturing technologies using big data;
• Data collection and knowledge representation for sustainable design and manufacture using big data;
• Analyzing, capturing and evaluating consumer requirements and concepts for sustainable design and manufacture through big data;
• Impact of uncertainty on generation and evaluation of sustainable design and manufacture using big data;
• Modeling analysis and control of a product’s sustainable design and manufacture;
• Using big data for correlating consumer satisfaction, engineering characteristics and design attributes for sustainable design and manufacture;
• Using big data to develop smart systems for sustainable design and manufacture;
• Development of machine learning/artificial intelligence techniques for sustainable design and manufacture based on big data;
• Incorporating decision-making within the development process of sustainable design and manufacture using big data;
• Sustainable logistics and service quality management using big data;
• For energy internet use: data mining and knowledge discovery, intelligent algorithms and optimization, and machine learning and deep learning;
• Energy efficient hardware, devices and designs for cloud-computing platforms;
• Modeling and control of manufacturing systems using big data;
• Security analysis and design of manufacturing system.

Prof. Dr. Yixiong Feng
Prof. Dr. Guangdong Tian
Prof. Dr. Amir M. Fathollahi-Fard
Prof. Dr. Zhiwu Li
Prof. Dr. Kamel Barkaoui
Guest Editors

Manuscript Submission Information

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• sustainable design
• manufacturing systems
• big data analytics
• system modeling and simulation
• optimization
• sustainable development