Smart manufacturing is critical in improving the quality of the process industry. In smart manufacturing, there is a trend to incorporate different kinds of new-generation information technologies into process-safety analysis. At present, green manufacturing is facing major obstacles related to safety management, due to the usage of large amounts of hazardous chemicals, resulting in spatial inhomogeneity of chemical industrial processes and increasingly stringent safety and environmental regulations. Emerging information technologies such as artificial intelligence (AI) are quite promising as a means of overcoming these difficulties. Based on state-of-the-art AI methods and the complex safety relations in the process industry, we identify and discuss several technical challenges associated with process safety: ① knowledge acquisition with scarce labels for process safety; ② knowledge-based reasoning for process safety; ③ accurate fusion of heterogeneous data from various sources; and ④ effective learning for dynamic risk assessment and aided decision-making. Current and future works are also discussed in this context.
We outline the smart manufacturing challenges for formulated products, which are typically multicomponent, structured, and multiphase. These challenges predominate in the food, pharmaceuticals, agricultural and specialty chemicals, energy storage and energetic materials, and consumer goods industries, and are driven by fast-changing customer demand and, in some cases, a tight regulatory framework. This paper discusses progress in smart manufacturing—namely, digitalization and the use of large datasets with predictive models and solution-finding algorithms—in these industries. While some progress has been achieved, there is a strong need for more demonstration of model-based tools on realistic problems in order to demonstrate their benefits and highlight any systemic weaknesses.
Safe, efficient, and sustainable operations and control are primary objectives in industrial manufacturing processes. State-of-the-art technologies heavily rely on human intervention, thereby showing apparent limitations in practice. The burgeoning era of big data is influencing the process industries tremendously, providing unprecedented opportunities to achieve smart manufacturing. This kind of manufacturing requires machines to not only be capable of relieving humans from intensive physical work, but also be effective in taking on intellectual labor and even producing innovations on their own. To attain this goal, data analytics and machine learning are indispensable. In this paper, we review recent advances in data analytics and machine learning applied to the monitoring, control, and optimization of industrial processes, paying particular attention to the interpretability and functionality of machine learning models. By analyzing the gap between practical requirements and the current research status, promising future research directions are identified.
Based on the analysis of the present situation and problems in application of Internet of Things(IoT) technology in Chinese aquaculture, this paper puts forward some key technical issues and policy suggestions for the development of the IoT. At the moment, IoT technology has been used in the aquaculture industry for water quality monitoring, breeding area monitoring and management, livestock germination monitoring, aquaculture product storage and transport, and supervision of processing procedures. During this early development stage, China is faced with a number of challenges in the application of this technology, including: Backward extensive aquaculture practice and poor infrastructures; lack of advanced equipment and unified standards; and the need of large sum investment and high costs. A number of key technological issues should be solved in order to improve IoT application in this industry, including: precise aquaculture sensor technology for precise breeding simulation technology, precise intelligent control technology for aquaculture equipment, precise aquaculture management technology, and precise integrated production technology for large-scale aquaculture. Finally, this paper makes suggestions to relevant government agencies on the formulation of an comprehensive development plan for China aquaculture IoT technology to enhance industrial informatization and optimize the application facilities for IoT, initiate a research and development program for precise aquaculture environmental sensor technology, advance the implementation of aquaculture IoT demonstration projects, and upgrade the government’s capacity for promoting the commercialization of aquaculture IoT.
With the world energy crisis and environmental protection issues, countries around the world are actively engaged in exploring the new way of the future energy development. In recent years, Jeremy Rifkin, the famous American economist, proposed the idea of the third industrial revolution and the energy internet which caused widespread concern. Following this trend, countries put forward their own development strategies of industrial technology which are driven by internet respectively, such as: the third industrial revolution and industrial Internet of American, industry 4.0 of Germany, smart grid and “Internet + energy” of China. Based on energy efficiency theory in the system, the ubiquitous energy Internet has a stereoscopic structure which consists of three levels: information network, energy network and physical network. By using the optimization control based on the coupling between information and energy to adjust measures to local conditions and fully exploit the multiple grade energy, the ubiquitous energy Internet can give the solution to the integration stability of the renewable energy and the dynamic matching between demand and supply, and become a representative internet of the new energy.
The internet of things (IoT) enabling things connects things, is very hot and provides technical support and development opportunities to China´s growing transportation industry. This paper puts forward the concept and structure of the intelligent transportation system(ITS) under IoT; discusses the difference and changes of traditional ITS with ITS under IoT; analysis of our country´s basic condition and the breakthrough focus to develop ITS under IoT; put forward our country´s development strategy of ITS under IoT. So as to promote China´s rapid development of intelligent transportation industry and IoT industry.