Digital Twin-driven machining process for thin-walled part manufacturing

Thin-walled parts are widely used in the aerospace, shipbuilding, and automotive industry, but due to its unique structure and high accuracy requirements, which leads to an increase in scrapped parts, high cost in production, and a more extended period in the trial machining process. However, to adapt to fast production cycles and increase the efficiency of thin-walled parts machining, this paper presents a Digital Twin-driven thin-walled part manufacturing framework to allow the machine operator to manage the product changes, make the start-up phases faster and more accurate. The framework has three parts: preparation, machining, and measurement, driven by Digital Twin technologies in detail. By establishing and updating the workpiece Digital Twin under a different status, various manufacturing information and data can be integrated and available to machine operators and other Digital Twins. It can serve as a guideline for establishing the machine tool and workpiece Digital Twin and integrating them into the machining process. It provides the machine operator opportunities to interact with both the physical manufacturing process and its digital data in real-time. The digital representation of the physical process can support them to manage the trial machining from different aspects. In addition, a demonstrative case study is presented to explain the implementation of this framework in a real manufacturing environment.     

Real-time integrated production-scheduling and maintenance-planning in a flexible job shop with machine deterioration and condition-based maintenance

The introduction of modern technologies in manufacturing is contributing to the emergence of smart (and data-driven) manufacturing systems, known as Industry 4.0. The benefits of adopting such technologies can be fully utilized by presenting optimization models in every step of the decision-making process. This includes the optimization of maintenance plans and production schedules, which are two essential aspects of any manufacturing process. In this paper, we consider the real-time joint optimization of maintenance planning and production scheduling in smart manufacturing systems. We have considered a flexible job shop production layout and addressed several issues that usually take place in practice. The addressed issues are: new job arrivals, unexpected due date changes, machine degradation, random breakdowns, minimal repairs, and condition-based maintenance (CBM). We have proposed a real-time optimization-based system that utilizes a modified hybrid genetic algorithm, an integrated proactive-reactive optimization model, and hybrid rescheduling policies. A set of modified benchmark problems is used to test the proposed system by comparing its performance to several other optimization algorithms and methods used in practice. The results show the superiority of the proposed system for solving the problem under study. The results also emphasize the importance of the quality of the generated baseline plans (i.e., initial integrated plans), the use of hybrid rescheduling policies, and the importance of rescheduling times (i.e., reaction times) for cost savings.     

智能家居系统中的短信收发程序设计

针对智能家居系统中安防报警信息实时收发及家电远程控制的需求,提出使用3G模块收发短信的方法,并设计了实现短信同时收发功能的软件架构。实验结果表明,该方法简单实用,能够满足智能家居系统的要求。     

物联网概述第6篇:物联网的前沿技术与国家工程建设

物联网/云计算时代是一个无人化的普适服务时代。物联网的前沿技术,有RFID的智能化与普适化、智能手机的归一化交互、专家系统的软件集成、智能电网的物联技术等等。物联网时代的国家工程建设,有标准时空参数的国家工程建设、有效证券电子化的国家工程建设、重大的民生公共工程建设与物联网医院的示范工程建设等。     

物联网智能家居系统的研究与设计

智能家居有广阔的应用前景.针对传统家居控制上的缺陷,采用B/S架构设计了智能家居管理系统,采用ZigBee无线网络实现对各类家居设备的信息采集和指令控制.用SQL Server 2005数据库管理系统与家庭网关,进行数据的传递与接收.通过Web浏览器,用户可以实现对智能家居系统的管理.     

智能家居的发展方向与新技术

智能家居是人们对家居生活的一种理想。随着高新技术的不断发展,各技术领域智能程度的提高,智能家居也有了新的发展方向。本文首先给出了智能家居的发展方向,接着根据这些发展方向介绍了与此相关的信息技术、通信技术和无线射频技术等等,为智能家居的发展提供了有益的参考。     

A review of the use of human factors classification frameworks that identify causal factors for adverse events in the hospital setting

Various human factors classification frameworks have been used to identified causal factors for clinical adverse events. A systematic review was conducted to identify human factors classification frameworks that identified the causal factors (including human error) of adverse events in a hospital setting. Six electronic databases were searched, identifying 1997 articles and 38 of these met inclusion criteria. Most studies included causal contributing factors as well as error and error type, but the nature of coding varied considerably between studies. The ability of human factors classification frameworks to provide information on specific causal factors for an adverse event enables the focus of preventive attention on areas where improvements are most needed. This review highlighted some areas needing considerable improvement in order to meet this need, including better definition of terms, more emphasis on assessing reliability of coding and greater sophistication in analysis of results of the classification.

Practitioner Summary: Human factors classification frameworks can be used to identify causal factors of clinical adverse events. However, this review suggests that existing frameworks are diverse, limited in their identification of the context of human error and have poor reliability when used by different individuals.     

Smart pricing scheme: A multi-layered scoring rule application

Defining appropriate pricing strategy for smart environment is important and complex task at the same time. It holds the primal fraction in Demand Response (DR) program. In our work, we devise an incentive based smart dynamic pricing scheme for consumers facilitating a multi-layered scoring rule. The proposed strategy characterizes both incentive based DR and price based DR programs facilities. This mechanism is applied between consumer agents (CA) to electricity provider agent (EP) and EP to Generation Company (GENCO). Based on the Continuous Ranked Probability Score (CRPS), a hierarchical scoring system is formed among these entities, CA–EP–GENCO. As CA receives the dynamic day-ahead pricing signal from EP, it will schedule the household appliances to lower price period and report the prediction in a form of a probability distribution function to EP. EP, in similar way reports the aggregated demand prediction to GENCO. Finally, GENCO computes the base discount after running a cost-optimization problem. GENCO will reward EP with a fraction of discount based on their prediction accuracy. EP will do the same to CA based on how truthful they were reporting their intentions on device scheduling. The method is tested on real data provided by Ontario Power Company and we show that this scheme is capable to reduce energy consumption and consumers’ payment.     

基于Xbee的智能窗控制系统设计

介绍了一种智能开窗系统,为了达到窗体智能监控及远程控制的目的,设计引入了多种传感器、Zigbee模块和GSM模块,用以实现室内外对智能窗体的控制。详细说明了系统的软硬件实现,并对传感器选型以及各个功能的具体实现进行了说明。此款智能窗能够很好地解决一些现实生活中的实际问题,为人们的生活提供方便。     

智能电网的安全可控性

计算机与信息技术在电力系统中的广泛应用提高了电网的自动化、智能化水平,同时也将传统IT领域的众多安全隐患引入了电网。智能电网是社会域、信息域、物理域多域交互、渗透形成的大规模新型融合网络,其安全威胁具有多域渗透、跨域攻击的特点。文中描述了智能电网基本安全需求及其与传统IT安全需求的不同;分析了智能电网中多域渗透攻击并且对信息-物理安全威胁进行分类;基于分域防护、多域协同、边界防护的思想提出了智能电网多域协同安全防护模型。