Intellectualization

Abstract: With the rapid development of Additive Manufacturing (AM) technology in the past 30 years, AM has been shifting from prototyping to advanced manufacturing of functional components in industry. Intellectualization and industrialization of AM process and equipment could be the bottlenecks to the wide industrial applications of AM technology in the future, which have been highlighted in this paper, aiming at describing the technological research roadmaps for the next 5 to 10 years. According to the data flow in the process and value chains of AM technologies, state-of-art of design methodology, material, process & equipment, smart structures, and applications in extreme scales and environments has been elaborated respectively. Some suggestions on potential challenges for research and development in AM technologies have been provided in each section, which would finally establish a critical technical platform for the future industrial innovation and entrepreneurship.

Abstract: Digital transformation increasingly gains broad attentions from all the world and particularly studies on artificial intelligence, big data, cloud, and mobile are currently conducted. In addition, research based on ambient intelligence are also performed. Everything including condition information of all objects are shared on real time in AMI environment and all locations and objects are equipped with sensors. It acts intelligently such as decision-making. As sensors are equipped in locations and objects and connected with high-performance computer networks, users can receive information at any time and anywhere. In particular, the adoption of smart factory that turns all phases into automation and intellectualization based on cyber-physical system technology is proliferating. However, unexpected problems are likely to take place due to high complexity and uncertainty of smart factory. Thus, it is very likely to end manufacturing process, trigger malfunction, and leak important information. Although the necessity of analyzing threats to smart factory and systematic management is emphasized, there is insufficient research. In this paper, machine learning and context-aware intrusion detection system was built. The established system was effective to detection rate of anomaly signs and possibility of process achievement compared to the previous system.

Abstract: The conducted analysis of the results of the modern scientific researches on the problems of adaptive management of economic systems and entrepreneurship models demonstrated that the further development of methodological approaches takes place, considering the complications of information structure of economic systems of micro level, digitalization and intellectualization of their management systems and, as a consequence, led to the integration of monoapproaches to management with modern corporate automated control systems of the MRP/ERP/BPM class. It is established that the information support of management processes is based on mathematical provision of corporate automated control systems for which the bases are complex models of economic systems of micro level. Modeling requires formalization of its structural objects-components in various aspects of analysis which raises the problem of considering such peculiarities as the multiplicity of approaches to modeling, asynchrony of model complexes and the complexity of ensuring the model compatibility of its individual components and requires justification of a new methodology for modeling adaptive control system.