The development of intelligent tire is in line with the automatic, informational, intelligent and networked trend of the tire manufacturing process, and it is the fusion result of information technology and tire technology, so the intelligent tire creates excellent opportunities for the informational, intelligent and networked development of tire intelligent manufacturing. The condition monitoring method of intelligent tires provides convenience for the information management of the whole life cycle of tire production, warehousing, transportation, sales and maintenance services. The modeling and control technology of intelligent tires facilitates the realization of digital design and virtual simulation of tires and provides convenience for the intellectualization of tire manufacturing process. Tire condition automatic regulating system can collect tire information under different road conditions and different tire pressure and different vehicle speed, so it provides networked convenience for the tire manufacturing process. However, there are some limitations on the tire materials and manufacturing technology, sensors and chip technology, test technology and intelligent application related with intelligent tires, so the intelligent tire technology also provides some challenges for the implementation of tire intelligent manufacturing.

Based on virtual manufacturing, a new paradigm of intelligent manufacturing, parallel manufacturing is proposed. It integrates the concepts of cyber-physical-social system (CPSS) and industrial IoM by considering the complexity of physical, information and social systems. Based on ACP (artificial systems, computational experiments, parallel execution) method, an intelligent system of steel manufacturing is developed to realize parallel evolution, closed-loop feedback and cooperative optimization. It consists of three parts, namely, descriptive intelligence through software defined steelworks (SDS), predictive intelligence based on computational experiment and optimization, and prescriptive intelligence using parallel execution between virtuality and reality. Through the comprehensive utilization of descriptive, predictive and prescriptive intelligence, intelligent production is realized to transparentize and digitize the manufacturing system.

This paper proposes a new intelligent plant framework, to realize integrated innovation of process technoly (PT), equipment technology (ET), operation technology (OT), automation technology (AT) and information technology (IT)to solve the comprehensive problems of production control, production management and enterprise operation by industrial integrated solution APPs, so that enterprises can always firmly control their initiatives to develop industrial big data and artificial intelligence. At the same time, an information security system of industrial control is also proposed based on deep defense, combined hardware and software to provide safety assurance for the construction of intelligent plant in process industry.

This paper addresses the basic issues in intelligent manufacturing, from fundamental concepts to planning and implementation, with respect to th technical and economic feasibility. In the process of promoting intelligent manufacturing, enterprises should take their own technical conditions into account, avoiding blindly pursuing the technology novelty. Only in this way can we ensure a sound development of the intelligent manufacturing.

The purpose of intelligent manufacturing in iron and steel industry is to optimize the structure and process of iron and steel process so as to realize dynamic, orderly, coordinated and continuous operation and multi-objective optimization in a whole. In this paper, the main contents and key technologies of structural optimization and program optimization in steelworks are introduced, including multiPDCA closed loop for quality management and control, integrated planning and scheduling, coordination between material flow and energy flow, and multi-unit coordination optimization. Some common problems are analyzed, which the steel industry needs to overcome to make breakthrough in promoting intelligent manufacturing and some promising implementation paths are proposed.

“智能制造”是人工智能等新一代信息技术与制造装备融合的集成创新和工程应用，符合中国制造强国的战略目标，是《中国制造2025》“五大工程”之一。近年来，大数据、人工智能等技术在图像、视频、语音、情报等应用方面取得巨大成功，进而逐渐应用到制造领域，得到学术界、工业界和中国政府的高度重视。智能制造是复杂的系统工程，智能产品是主体，智能生产是主线，以智能服务为中心的产业模式变革是主题，而信息物理系统（cyber-physical-systems，CPS）和工业互联网只是初步的基础设施。研究人工智能、大数据等新技术，构建新的智能制造系统，并实现行业的广泛应用，对中国的制造业具有重大意义。

This paper reviews the research progress of model-based industrial robot error parameter calibration technology to improve the end-effector control accuracy, and summarizes the key problems when industrial robot is applied to high-precision machining and manufacturing, such as incomplete error parameters, high calibration cost and calibration accuracy. Moreover, the paper analyzes the modeling method of error parameter calibration model, end-effector's pose measurement technology, error parameter identification technology and error compensation technology. And the main difficulties of model-based error parameter model calibration technology in dealing with complex calibration tasks are discussed Finally, aimed at some existing problems, a method to efficiently obtain and process the measured error data is proposed and a feasible development direction is also prospected.

Compared with the traditional manufacturing methods of orthopedic insoles, 3D printing orthopedic insoles are intensive and efficient. However, there are still some problems in design, printing, materials and so on, and there is a lack of systematic research review. Based on the manufacturing methods of orthopedic insoles, this paper summarizes the printing technology, printing materials and research status of 3D printing orthopedic insoles, and analyzes the existing problems in the research of 3D printing orthopedic insoles. The future development trend of 3D printing orthopedic insoles is forecasted in terms of the improvement of orthopedic insoles performance and the development of modern science and technology.

Scientific drilling is an effective way for human beings to explore the interior of the earth, it is also an important means to solve major problems such as resources, disasters and the environment. Scientific drilling projects in the United States, the former Soviet Union, Germany, Japan, Iceland, China and other countries are summarized. The problems in drilling and completion of 10000-meter scientific ultra-deep wells are discussed, including complex geological conditions, high formation temperature, long drilling cycle, difficult well deviation control, etc.. Future applications of geology-engineering integration technology, high-efficiency rock breaking technology, high-temperature drilling fluid technology, and many others in the drilling and completion of 10000 meter scientific ultra deep wells are also prospected.

Single strand DNA probe-graphene field effect transistor (ssDNA-GFET) nano-biosensor holds great potential in wearable or implantable clinic applications. This paper reviews the development status of ssDNA-GFET, methods on optimizing biomarker sensing performance, detection of biomarkers in human biofluids, and the development status of flexible ssDNA-GFET toward wearable or implantable clinic applications. In the end, the paper demonstrates current limitations of the sensor that hampers its real clinic applications.

This paper concerns how to apply machine vision and virtual-reality technologies into industrial robots and Internet of Things and to combine big data and cloud computing to construct a parallel manufacturing infrastructure. A worldwide flexible supply chain of footwear and garment industries is introduced to demonstrate the workflow and efficiency of parallel manufacturing. Firstly, a virtual factory is constructed in the cloud, where management policies and decision control data are synchronized with the data generated by highly automated production equipment in the workshop. The virtual factory, executing in parallel with the physical one, supplies tested and optimized decisions and guides the production process in physical factories. To provide worldwide service, a global and distributed cooperative production management platform is built based on the industrial Internet of Things, namely CIXING's cloud manufacturing platform. It operates with low production cost, high work efficiency and reduced labor numbers. It has also been listed as one of the national intelligent manufacturing pilot demonstration project by the Chinese Ministry of Industry and Information Technology.

To compare the colliders between China and Japan from the perspectives of historical development and running performance and to learn the development experience of Japan and provide references for future technological layout, especially for large research infrastructure planning, this study discovers that the parameters of Chinese collider, which was constructed earlier, are limited by funding, technology, and other factors. Its research field is charm physics, whose energy range is lower than that of B physics. Whereas Japan, which has a foundation in engineering technology, targets at the B physics with richer physics prospects. Both colliders have obtained significant scientific achievements. Japan is more prominent in the research output and the degree of international cooperation is higher. The output of Chinese collider has increased significantly in recent years, and China keeps leading in the research of charm physics.