近终形薄带连铸工艺技术比较

近终形薄带连铸是钢铁工业简化工序，节能降耗，降低成本最具有竞争能力的一项重大新工艺技术，本文报导了世界各先进工业国近年来开展研究的最新成果，分析比较了诸多机型的优缺点，并提出了突破工艺技术的技术关键和建议。     

计算机在热处理工艺编制中的应用

利用计算机强大的数据处理功能 ,对热处理工艺中的各种数据进行记录和处理 ,并制成各种图表 ,掌握其中的各种规律。使热处理工艺的编制不再是一种经验积累式的工作 ,而是依照其规律制定一次合格的规范的热处理工艺卡片 ,并为将来计算机工艺自动生成的工作打下基础     

优化《光纤通信》的教学方法

本文主要介绍了在光纤通信教学过程中，为实现教学目标、优化教学效果采取的一些方法和措施。     

Energy and resources as production factors in process industries

It is shown that, when the mean productivity of some factors, such as energy or materials, is upperly bounded (a condition usually arising in energy production or in the process industries where energy takes part in physico-chemical processes), the production function may not be convex and, under some further conditions, is concave. Consequences of this model on the economics of energy savings are examined, and it is shown that energy savings may be considered at three levels: in the short run, by action on labour factors: in the medium run, by investment and action on labour factors; in the long run, by technological innovation, investment in new technologies and action on labour factors. Empirical findings along these lines are thus confirmed.     

多陀螺自动化测试系统研究

针对动力调谐挠性陀螺大批量生产中存在的性能调试和参数标定工作量大的问题，我们专门研制了一套多陀螺自动化测试系统，该系统主要包括多陀螺真空恒温安装基准体、测控台、计算机程控自动化数据采集和仪器等部分，本文着重介绍该系统的组成原理，设计特点和研制成果。     

《后期制作》实践教学中基于工作过程的教学改革与探索

根据《后期制作》课程的特点,结合学院的课程教学改革项目,对本课程实践教学过程中存在的问题进行剖析,提出实践教学要以工作过程系统化教学理念为指导．阐述从项目课程向工作过程系统化课程发展的主要任务。     

Automated manufacturing system discovery and digital twin generation

The latest developments in industry involved the deployment of digital twins for both long and short term decision making, such as supply chain management, production planning and control. Modern production environments are frequently subject to disruptions and consequent modifications. As a result, the development of digital twins of manufacturing systems cannot rely solely on manual operations. Recent contributions proposed approaches to exploit data for the automated generation of the models. However, the resulting representations can be excessively accurate and may also describe activities that are not significant for estimating the system performance. Generating models with an appropriate level of detail can avoid useless efforts and long computation times, while allowing for easier understanding and re-usability. This paper proposes a method to automatically discover manufacturing systems and generate adequate digital twins. The relevant characteristics of a production system are automatically retrieved from data logs. The proposed method has been applied on two test cases and a real manufacturing line. The experimental results prove its effectiveness in generating digital models that can correctly estimate the system performance.     

Toward in-situ flaw detection in laser powder bed fusion additive manufacturing through layerwise imagery and machine learning

Process monitoring in additive manufacturing may allow components to be certified cheaply and rapidly and opens the possibility of healing defects, if detected. Here, neural networks (NNs) and convolutional neural networks (CNNs) are trained to detect flaws in layerwise images of a build, using labeled XCT data as a ground truth. Multiple images were recorded after each layer before and after recoating with various lighting conditions. Classifying networks were given a single image or multiple images of various lighting conditions for training and testing. CNNs demonstrated significantly better performance than NNs across all tasks. Furthermore, CNNs demonstrated improved generalizability, i.e., the ability to generalize to more diverse data than either the training or validation data sets. Specifically, CNNs trained on high-resolution layerwise images from one build showed minimal loss in performance when applied to data from an independent build, whereas the performance of the NNs degraded significantly. CNN accuracy was also demonstrated to be a function of flaw size, suggesting that smaller flaws may be produced by mechanisms that do not alter the surface morphology of the build plate. CNNs demonstrated accuracies of 93.5 % on large (>200 μm) flaws when testing and training on components from the same build and accuracies of 87.3 % when testing on a previously unseen build. Finally, evidence linking the formation of large lack-of-fusion defects to the presence of process ejecta is presented.     

Decision-based process planning for wire and arc additively manufactured and machined parts

The conventional manufacturing of aircraft components is based on the machining from bulk material and the buy-to-fly ratio is high. This, in combination with the often low machinability of the materials in use, leads to high manufacturing costs. To reduce the production costs for these components, a process chain was developed, which consists of an additive manufacturing process and a machining process. To fully utilize the process chain’s capabilities, an integrated process planning approach is necessary. As a result, the work sequence can be optimized to achieve the economically most suitable sequence. In this paper, a method for a joint manufacturing cost calculation and subsequent decision-based cost minimization is proposed for the wire and arc additive manufacturing (WAAM) & milling process chain. Furthermore, the parameters’ influence on the results and the magnitude of their influence are determined. These results make it possible to design an economically optimal work sequence and to automate the process planning for this process chain.     

Analysis of information exchange activities to actualize and validate situation awareness during shift changeovers in nuclear power plants

Shift work situations occur in almost all safety‐critical organizations, and the investigations of some catastrophes like Chernobyl, Exxon Valdez, and the Gol/Legacy mid‐air collision indicated that shift work information exchange played an important role during the evolution of the situation before the accidents. Inadequate communications during shift changeovers challenged operators' work in the moments that preceded these accidents, because they got inadequate information about the current situation. Our research focuses on the information exchange activities (verbal, written, and nonverbal) of nuclear power plant control operators during shift changeovers. Our aim is to investigate how verbal exchanges and other representations enable operator crews to share information regarding the events that occurred in the previous shift to achieve adequate situation awareness. Our findings indicated the importance and richness of the information exchange during the shift changeover process to update and validate individual and collective situation awareness, showing that information adequately shared enables the ad hoc configurations of regulation loops and a safer use of simplified strategies that can be understood and be validated by other operators, reducing the occurrence of cognitive overloads and contributing to the construction of a common cognitive ground that enhances system resilience. © 2010 Wiley Periodicals, Inc.