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.     

金选别工艺的发展与深化

本文阐述了充分考虑矿石性质,探索出混合浮选的分步流程,恰当的施用多元扑收剂所产出的“协同效应”,稳定和强化选别工艺,收到提高选金技术指标的效果。     

过程控制计算机系统在热轧中的应用

在冶金生产中,热轧是自动化程度高、各种高新技术应用最为广泛的领域.针对过程控制计算机系统在热轧中的应用情况,联系过程控制系统在宝钢热轧发展过程的实际情况,从系统功能的组成及模型、系统接口的实现等方面,对热轧过程控制系统的开发与应用情况,进行了详细的分析.     

面向多商户的第三方电子券系统设计与实现

电子券正成为商家促销的一种新技术手段.在一个已有的定制化电子券系统的基础上,针对服务于多商户的应用背景,对系统的需求进行了重新梳理和流程优化,给出了改造后的系统架构.同时,还对新系统的权限管理与访问控制问题进行了重点分析和设计,引入基于角色的访问控制模型,使之能支持面向多商户的管理.     

零库存流程管理在医院成本核算中的应用

随着各类医用耗材、消毒品数量和种类的增加,医院物资管理在医院运营中的作用越来越显著。在提倡以患者为中心,提高患者满意度的宗旨下,与患者直接接触的HIS、LIS、PACS、CIS等医疗系统发展十分迅速,而医院内部使用的物资管理系统却比较落后。针对在医院实际医用物资管理中,时常发生医疗物资积压和医疗耗材缺货导致医疗时机延误等问题,对现有物资管理系统中的不足进行分析,并提出一种以零库存管理为基础的新工作流程,以解决现有的一些问题,并在继续深入探讨和研究。     

基于特征的派生式车身覆盖件冲压CAPP的研究

本文介绍了一种基于特征的派生式车身覆盖件冲压工艺ＣＡＰＰ系统。通过建立特征模型，引入成组技术，建立工艺数据库，系统的功能得以实现。该系统保证了车身开发中ＣＩＭＳ的信息集成。