人水关系学的学科体系及发展布局

人水关系是人类与自然界关系中最重要的关系之一,也是人类一出现就始终存在且复杂程度不断加深的一类关系。在对人水关系分析总结的基础上,提出了人水关系学的概念和思考,论述了人水关系学的提出背景和重要意义;构建了人水关系学的学科体系框架,阐述了人水关系学的主要内容,包括人水关系学的理论基础、方法论、应用实践;在分析学科发展趋势的基础上,对人水关系学未来全面、系统的研究进行了展望,并从科学研究、学科建设、学术交流与国际合作3个方面对人水关系学的发展进行战略布局。为进一步研究人水关系、丰富人水关系学内容、发展人水关系学学科体系及制定学科发展战略提供参考。     

The application of the methodology for secure cyber–physical systems design to improve the semi-natural model of the railway infrastructure

The paper suggests a new methodology for secure cyber–physical systems design. The proposed methodology consists of two main cycles. The main goal of the first cycle is in design of the system model, while the second one is about development of the system prototype. The key idea of the methodology is in providing of the most rational solutions that are improving the security of cyber–physical systems. Such solutions are called alternatives and built according to functional requirements and non-functional limitations to the system. Each cycle of the methodology consists of the verification process and seven stages that are associated with the used cyber–physical system model. The objective of the verification process is in checking of constructed models and prototypes in terms of their correctness and compatibility. The model represents cyber–physical systems as sets of building blocks with network between them, takes elements internal structure into account and allows direct and reverse transformations. The novelty of the suggested methodology is in the combination of design, development and verification techniques within a single approach. To provide an example of the design methodology application, in this paper it is used to improve the semi-natural model of the railway infrastructure.     

DETECTOR: A knowledge-based system for injection molding diagnostics

A knowledge-based system (KBS) for diagnosis of multiple defects in injection molding is presented. The general scheme for knowledge representation based on fuzzy set theory has been shown useful in representing inexact and incomplete information for developing the KBS. An optimality criterion is created for selecting a simple and best cover to explain the given problem. An efficient search algorithm for finding such cover is also discussed.     

Effects of computers on Japanese schools

In this paper I consider how the computer can or should be accepted in Japanese schools. The concept of teaching in Japan stresses learning from a long-term perspective. Whereas in the instructional technology, on which the CAI or the Tutoring System depends, step-by-step attainments in relatively short time are emphasized. The former is reluctant in using the computer, but both share the Platonic perspective which are goal-oriented. However, The Socratic teacher, who intends to activate students' innate disposition to be better, would find another way of teaching and use of the computer.     

New Paradigm of Data-Driven Smart Customisation through Digital Twin

Big data is one of the most important resources for the promotion of smart customisation. With access to data from multiple sources, manufacturers can provide on-demand and customised products. However, existing research of smart customisation has focused on data generated from the physical world, not virtual models. As physical data is constrained by what has already occurred, it is limited in the identification of new areas to improve customer satisfaction. A new technology called digital twin aims to achieve this integration of physical and virtual entities. Incorporation of digital twin into the paradigm of existing data-driven smart customisation will make the process more responsive, adaptable and predictive. This paper presents a new framework of data-driven smart customisation augmented by digital twin. The new framework aims to facilitate improved collaboration of all stakeholders in the customisation process. A case study of the elevator industry illustrates the efficacy of the proposed framework.     

A fuzzy hierarchical reinforcement learning based scheduling method for semiconductor wafer manufacturing systems

Scheduling semiconductor wafer manufacturing systems has been viewed as one of the most challenging optimization problems owing to the complicated constraints, and dynamic system environment. This paper proposes a fuzzy hierarchical reinforcement learning (FHRL) approach to schedule a SWFS, which controls the cycle time (CT) of each wafer lot to improve on-time delivery by adjusting the priority of each wafer lot. To cope with the layer correlation and wafer correlation of CT due to the re-entrant process constraint, a hierarchical model is presented with a recurrent reinforcement learning (RL) unit in each layer to control the corresponding sub-CT of each integrated circuit layer. In each RL unit, a fuzzy reward calculator is designed to reduce the impact of uncertainty of expected finishing time caused by the rematching of a lot to a delivery batch. The results demonstrate that the mean deviation (MD) between the actual and expected completion time of wafer lots under the scheduling of the FHRL approach is only about 30 % of the compared methods in the whole SWFS.     

Mathematical model and discrete artificial Bee Colony algorithm for distributed integrated process planning and scheduling

With the development of the globalization of economy and manufacturing industry, distributed manufacturing mode has become a hot topic in current production research. In the context of distributed manufacturing, one job has different process routes in different workshops because of heterogeneous manufacturing resources and manufacturing environments in each factory. Considering the heterogeneous process planning problems and shop scheduling problems simultaneously can take advantage of the characteristics of distributed factories to finish the processing task well. Thus, a novel network-based mixed-integer linear programming (MILP) model is established for distributed integrated process planning and scheduling problem (DIPPS). The paper designs a new encoding method based on the process network and its OR-nodes, and then proposes a discrete artificial bee colony algorithm (DABC) to solve the DIPPS problem. The proposed DABC can guarantee the feasibility of individuals via specially-designed mapping and switching operations, so that the process precedence constraints contained by the network graph can be satisfied in the entire procedure of the DABC algorithm. Finally, the proposed MILP model is verified and the proposed DABC is tested through some open benchmarks. By comparing with other powerful reported algorithms and obtaining new better solutions, the experiment results prove the effectiveness of the proposed model and DABC algorithm successfully.     

Building a right digital twin with model engineering

In recent years, the concept of digital twin (DT) is attracting more and more attention from researchers and engineers. But there is still no consensus on what a right DT is. On one hand, some common models are renamed as DTs. On the other hand, some DTs extremely pursue ‘the same’ as physical objects, which bring unnecessary complexities to them. In this paper, we try to answer two questions from the point of view of model engineering: how to define a right digital twin, and how to build a right digital twin. The concept and related technologies of model engineering are introduced. Some basic principles and a set of metrics for a right DT are given. An evolutionary concurrent modeling method for DT (ECoM4DT) is proposed not only inheriting the theory from classic M&S methods but also highlighting the characteristics of DT compared with traditional models to systemically guide the DT modeling process.     

A CALPHAD-type Young's modulus database of Ti-rich Ti–Nb–Zr–Mo system

Accurate Young's modulus is the necessity for the design of biomedical Ti alloys. A combinatorial method of the diffusion couple, nanoindentation, electron probe microanalysis (EPMA), and CALculation of PHAse Diagrams (CALPHAD) techniques has been utilized to construct the Young's modulus database of Ti alloys with various compositions in the present work. Two groups of body-centered cubic (bcc) Ti–Nb–Zr–Mo quaternary diffusion couples annealed at 1273 K for 25 h were experimentally prepared. Subsequently, the composition-dependent mechanical properties in the wide compositional range of Ti-based alloys were obtained by using EPMA and nanoindentation probes. Finally, on the basis of the measured Young's moduli in the present and previous work and the modeling parameters of Young's modulus of Ti–Nb–Zr system, the Young's modulus database of bcc Ti–Nb–Zr–Mo system was established through the CALPHAD approach. The CALPHAD-type database of bcc Ti–Nb–Zr–Mo system can provide the accurate Young's moduli of Ti alloys with wide compositions.     

A novel vision-based method for 3D profile extraction of wire harness in robotized assembly process

Automating stages for deformable objects in the production line, in which assembling a wire harness into a predefined position is a complex task owing to the specialized characteristics of the objects. Besides a few automatized systems proposed in the other studies to implement this task under simplified setup conditions, a significant portion of this process remains to be completed manually in industrial environments. To construct an automatic wire harness assembly system, the development of a method that can automatically detect the wire harness profile in a 3D environment and, consequently, guide robot arms to implement assembly tasks is indispensable. Therefore, this study presents an approach that satisfies this requirement, which not only proposes a deep learning-based system to detect the wire profile, but also improves the accuracy of the detected results through a correction method according to the depth values of contiguous areas. The verification of the approach in a robot system that highlights its usefulness and practicality demonstrates the potential of the proposed method to replace people and consequently, reduce labour costs in factory environments.