基于数字孪生的畲族文创设计研究

目的 结合数字孪生原理来辅助文创产品的设计过程,借由智能图像处理技术发散更多艺术创意,从而减少文创产品设计的艺术内耗,提升设计效率,并从数字孪生角度审视文创产品效果,辅助产品的孵化。方法 在数字孪生原理的指导下,以数据处理技术提取文化特征,丰富畲族文化资源数据库,并从中选取畲族设计元素以智能数字图像处理方法进行批量化图像生成,最后在keyshot中对概念产品的数字孪生模型进行数字图像的UV映射,以构建文创产品的仿真造型效果。结果 获取畲族文化图像孪生数据,组成畲族纹样文化资源库,构建数字孪生辅助的畲族文创设计方法。结论 基于数字孪生的文创产品设计中,借助了多种人工智能和数字图像处理手段,对文创中的图像设计工作起到了有效的辅助产出作用。为文创与科技融合的设计方法提供了新思路。     

Operational flexibility in hospitals: Scale development and validation

The purpose of this paper is to develop and validate an operational flexibility construct that can serve as a general theory in operations management in the context of the hospital industry. The effects of management capability and competitive intensity on operational flexibility and performance relationships are also explored. We used data collected from a sample of 152 administrators of hospitals in the mid-west region of the USA and performed a systematic series of analyses. Following the transformation model, grounded in the fundamental and powerful concept of operations management, we develop a psychometrically validated, 11-item, three-dimensional (input, process, output) scale of operational flexibility (OF) construct for the hospital industry. As the degree of operational flexibility allowed in any transformation system is influenced by management capability, it is established as a complementary mediator in strengthening the OF-performance relationship in the presence of competitive intensity (i.e. moderator). The paper concludes with limitations and directions for future research.     

基于设计任务的概念设计中产品数字孪生模型的构建

在产品概念设计过程中,明确设计任务,应用数字孪生技术,可以更好地处理大量用户数据、监测功能运行和分析目标产品,促进设计方案的产生。首先,以设计任务为切入点,引入用户因素,集成任务分析法和情景分解法来分解设计任务,构建任务域任务流模型;其次,利用模糊综合评价法量化设计任务,明确设计任务,并对设计任务进行进一步分解,构建物理域实体任务情景模型;基于任务流的走向分析交互通道与虚拟域数据类型,构建虚拟域任务情景模型,完成基于设计任务的数字孪生模型的构建。最后,将这一方法应用于智能分类垃圾桶数字孪生模型的构建,拓展了数字孪生在概念设计中的应用。在产品概念设计阶段将用户因素融入设计任务中,可提高产品的设计质量。     

Real-time digital optical matrix multiplication with a joint-transform correlator

Joint-transform correlation architecture is employed for digital matrix multiplication. Real-valued matrix-vector, complex-valued matrix-vector, real-valued matrix-matrix, and complex-valued matrix-matrix multiplication operations can all be realized simply by programming of the data arrangement in the input plane of a multiple-input joint-transform correlator. The proposed method benefits from the advantages of speed because of the real-time processing capability of the joint-transform correlator and of high accuracy because of the digital representation of the multiplied numbers. Computer-simulation results are provided in which the negative binary encoding method is used to encode matrix elements.     

A new muscle fatigue and recovery model and its ergonomics application in human simulation

Although automatic techniques have been employed in manufacturing industries to increase productivity and efficiency, there are still lots of manual handling operations, especially for assembly and maintenance operations. In these operations, musculoskeletal disorder (MSD) is one of the major health problems due to overload and cumulative physical fatigue. With combination of conventional posture analysis techniques, digital human modeling and simulation (DHM) techniques have been developed and commercialized to evaluate the potential physical exposures. However, those ergonomic analysis tools are mainly based on posture analysis techniques, and until now there is still no fatigue index available in commercial software to evaluate the physical fatigue effectively. In this paper, a new muscle fatigue and recovery model is used to evaluate joint fatigue level in manual handling operations. The physical fatigue in a special application case is described and analyzed using digital human simulation techniques.     

Framework based on building information modeling,mixed reality,and a cloud platform to support information flow in facility management

The quality of information flow management has a remarkable effect on the entire life cycle of buildings. Manual retrieval of technical specifications and features of building components and their performance assessment leads to increased cost and time and efficiency reduction, especially during the facility management (FM) stage. The introduction of building information modeling (BIM) in the construction industry can provide a valuable means of improving the organization and exchange of information. BIM tools integrate multiple levels of information within a single digital model of a building. Nevertheless, the support given by BIM to FM is far from being fully effective. Technicians can benefit from real-time communication with the data repository whenever the need for gathering contextual information and/or updating any data in the digital model arises. The framework proposed in this study aims to develop a system that supports on-site operations. Information requirements have been determined from the analyses of procedures that are usually implemented in the building life cycle. These studies set the standard for the development of a digital model of a building, which will be shared among various actors in charge of FM and accessed via a cloud platform. Moreover, mixed reality is proposed to support specific information that is relevant to geometric features and procedures to be followed by operators. This article presents three use-cases supported by the proposed framework. In addition, this research article describes the first proof of concept regarding real-time support for FM.     

A CAMAC based real-time noise analysis system for nuclear reactors

A CAMAC based real-time noise analysis system was designed for the TRIGA MARK II nuclear reactor at the Institute for Nuclear Energy, Istanbul. The input analog signals obtained from the radiation detectors are introduced to the system through CAMAC interface. The signals converted into digital form are processed by a PDP-11 computer. The fast data processing based on auto/cross power spectral density computations is carried out by means of assembly written FFT algorithms in real-time and the spectra obtained are displayed on a CAMAC driven display system as an additional monitoring device. The system has the advantage of being software programmable and controlled by a CAMAC system so that it is operated under program control for reactor surveillance, anomaly detection and diagnosis. The system can also be used for the identification of nonstationary operational characteristics of the reactor in long term by comparing the noise power spectra with the corresponding reference noise patterns prepared in advance.     

高温超导电缆实时监测系统及试验

介绍了用于10米长10．5kV／1．5kA三相交流高温超导电缆的实时监测系统。该系统采用NI分布式测量模块和数字电压表,通过计算机采集数据,能够在高温超导电缆的预冷和长时间通电运行时实时监测超导电缆中超导体的温度和循环冷却液氮的压力,能够监测超导电缆的通电电流和超导体上的电压,可以完成交流损耗试验。测量结果为研究高温超导电缆性能与相关参数变化的关系、研究高温超导电缆运行的最优条件奠定了一定的基础。     

Defining a Digital Twin-based Cyber-Physical Production System for autonomous manufacturing in smart shop floors

Smart manufacturing is the core idea of the fourth industrial evolution. For a smart manufacturing shop floor, real-time monitoring, simulation and prediction of manufacturing operations are vital to improve the production efficiency and flexibility. In this paper, the Cyber-Physical System (CPS) and Digital Twin technologies are introduced to build the interconnection and interoperability of a physical shop floor and corresponding cybershop floor. A Digital Twin-based Cyber-Physical Production System (DT-CPPS) is further established, and the configuring mechanism, operating mechanism and real-time data-driven operations control of DT-CPPS are discussed in detail. It is expected that DT-CPPS will provide the basis for shop floors to march towards smart manufacturing.     

Real-time sea-level gauge observations and operational oceanography

The contribution of tide-gauge data, which provide a unique monitoring of sea-level variability along the coasts of the world ocean, to operational oceanography is discussed in this paper. Two distinct applications that both demonstrate tide-gauge data utility when delivered in real-time are illustrated. The first case details basin-scale operational model validation of the French Mercator operational system applied to the North Atlantic. The accuracy of model outputs in the South Atlantic Bight both at coastal and offshore locations is evaluated using tide-gauge observations. These data enable one to assess the model's nowcasts and forecasts reliability which is needed in order for the model boundary conditions to be delivered to other coastal prediction systems. Such real-time validation is possible as long as data are delivered within a delay of a week. In the second application, tide-gauge data are assimilated in a storm surge model of the North Sea and used to control model trajectories in real-time. Using an advanced assimilation scheme that takes into account the swift evolution of model error statistics, these observations are shown to be very efficient to control model error, provided that they can be assimilated very frequently (i.e. available within a few hours).     

Widely Linear Temperature-to-Frequency Converters

In this article a square-wave generator, which employs an operational amplifier and is easy in construction, is considered for converting temperature to frequency so that the advantages of digital measurement of any physical quantity are utilized. A new procedure is suggested for obtaining linearity over a wide range of temperature for a specified value of deviation. Theoretical deviation curves have been obtained to show that the new procedure gives a wide range of temperature.     

Real-Time Hand-Held Ultrasound Medical-Imaging Device Based on a New Digital Quadrature Demodulation Processor

A fully hardware-based real-time digital wideband quadrature demodulation processor based on the Hilbert transform is proposed to process ultrasound radio frequency signals. The presented architecture combines 2 finite impulse response (FIR) filters to process in-phase and quadrature signals and includes a piecewise linear approximation architecture that performs the required square root operations. The proposed implementation enables flexibility to support different transducers with its ability to load on-the-fly different FIR filter coefficient sets. The complexity and accuracy of the demodulator processor are analyzed with simulated RF data; a normalized residual sum-of-squares cost function is used for comparison with the Matlab Hilbert function. Three implementations are integrated into a hand-held ultrasound system for experimental accuracy and performance evaluation. Real-time images were acquired from a reference phantom, demonstrating the feasibility of using the presented architecture to perform real-time digital quadrature demodulation of ultrasonic signal echoes. Experimental results show that the implementation, using only 2942 slices and 3 dedicated digital multipliers of a low-cost and low-power field-programmable gate array (FPGA) is accurate relative to a comparable software- based system; axial and lateral resolution of 1 mm and 2 mm, respectively, were obtained with a 12-mm piezoelectric transducer without postprocessing. Because the processing and sampling rates are the same, high-frequency ultrasound signals can be processed as well. For a 15-frame-per-second display, the hand-held ultrasonic imaging-processing core (FPGA, memory) requires only 45 mW (dynamic) when using a 5-MHz single-element piezoelectric transducer.     

A review of condition-based maintenance: Its prognostic and operational aspects

Condition-based maintenance (CBM) detects early signs of failure and dictates when maintenance should be performed based on the actual condition of a system. In this paper, we first review some of the recent research on CBM under various physical structures and signal data. Then, we summarize several kinds of prognostic models that use monitoring information to estimate the reliability of complex systems or products. Monitoring information also facilitates operational decisions in production planning, spare parts management, reliability improvement, and prognostics and health management. Finally, we suggest some research opportunities for the reliability and operations management communities to fill the research gap between these two fields.     

Enterprise resource planning (ERP) operations support system for maintaining process integration

A successfully adopted and implemented enterprise resource planning (ERP) system does not automatically guarantee full benefits. It is important that ERP is operated as planned and thus provides the real-time information with a desired level of process integration. Any ERP system pushes a company toward full process integration and solves the fragmentation of information. However, the tight process integration involves operational issues that must be carefully managed. Thus, a conjecture can be made that a centrally coordinated support system is required to assist ERP users and administrators find problems, perform tedious validation and verification, and maintain the process integration of ERP with great consistency. This paper proposes an ERP operations support system (EOSS) that aims to achieve and maintain the process integration of ERP. EOSS monitors the operational status of process integration, prevents anomalies as early as possible and conducts repairs as soon as possible.     

Big data and machine learning: A roadmap towards smart plants

Industry 4.0 aims to transform chemical and biochemical processes into intelligent systems via the integration of digital components with the actual physical units involved. This process can be thought of as addition of a central nervous system with a sensing and control monitoring of components and regulating the performance of the individual physical assets (processes, units, etc.) involved. Established technologies central to the digital integrating components are smart sensing, mobile communication, Internet of Things, modelling and simulation, advanced data processing, storage and analysis, advanced process control, artificial intelligence and machine learning, cloud computing, and virtual and augmented reality. An essential element to this transformation is the exploitation of large amounts of historical process data and large volumes of data generated in real-time by smart sensors widely used in industry. Exploitation of the information contained in these data requires the use of advanced machine learning and artificial intelligence technologies integrated with more traditional modelling techniques. The purpose of this paper is twofold: a) to present the state-of-the-art of the aforementioned technologies, and b) to present a strategic plan for their integration toward the goal of an autonomous smart plant capable of self-adaption and self-regulation for short- and long-term production management.     

Parallel modified signed-digit arithmetic using an optoelectronic shared content-addressable-memory processor

Addition is the most primitive arithmetic operation in digital computation. Other arithmetic operations such as subtraction, multiplication, and division can all be performed by addition together with some logic operations. With the binary number system, addition speed is inevitably limited by the carry-propagation schemes. On the other hand, carry-free addition is possible when the modified signed-digit (MSD) number representation is used. We propose a novel optoelectronic scheme to handle the parallel MSD addition and subtraction operations. An optoelectronic shared content-addressable memroy is introduced. The shared content-addressable memory uses free-space optical processing to handle the large amount of parallel memory access operations and uses electronics to postprocess and derive logic decisions. We analyze the accuracy that the required optical hardware can deliver by using a statistical cross-talk-rate model that we propose. We also evaluate other important device and system performanceparameters, such as the memory capacity or the maximum number of parallel bits the adder can handle in terms of a given cross-talk rate at a certain repetition rate, the corresponding diffraction-limited memory density, and the system's power efficiency. To confirm the underlining operational principles of the proposed optoelectronic shared content-addressable-memory MSD adder, we design and perform initial experiments for handling 8-bit MSD number addition and subtraction and present the results.     

Convergence to real-time decision making

Real-time decision making reflects the convergence of several digital technologies, including those concerned with the promulgation of artificial intelligence and other advanced technologies that underpin real-time actions. More specifically, real-time decision making can be depicted in terms of three converging dimensions: Internet of Things, decision making, and real-time. The Internet of Things include tangible goods, intangible services, ServGoods, and connected ServGoods. Decision making includes model-based analytics (since before 1990), information-based Big Data (since 1990), and training-based artificial intelligence (since 2000), and it is bolstered by the evolving real-time technologies of sensing (i.e., capturing streaming data), processing (i.e., applying real-time analytics), reacting (i.e., making decisions in real-time), and learning (i.e., employing deep neural networks). Real-time includes mobile networks, autonomous vehicles, and artificial general intelligence. Central to decision making, especially real-time decision making, is the ServGood concept, which the author introduced in an earlier paper (2012). It is a physical product or good encased by a services layer that renders the good more adaptable and smarter for a specific purpose or use. Addition of another communication sensors layer could further enhance its smartness and adaptiveness. Such connected ServGoods constitute a solid foundation for the advanced products of tomorrow which can further display their growing intelligence through real-time decisions.     

Development of a BIM-based holonic system for real-time monitoring of building operational efficiency

In the wide context of facility management, several processes, such as operations, maintenance, retrofitting, and renovations, ensure that buildings comply with the principles of efficiency, cost-effectiveness, and indoor comfort. Apart from ordinary operation, facility management is responsible for the renovation of and long-term performance improvement of building facilities. In such a scenario, the cyber–physical system (CPS) paradigm with holonic architecture, which is the focus of this study, can successfully guide the operation management and long-term refurbishment processes of buildings. Analogous to the manufacturing field, the developed CPS maximizes holons’ self-configuration and self-organization and overall throughput effectiveness metrics to detect the best corrective actions toward system improvements. Consequently, suggestions and lessons learned from the evaluation of building efficiency are redirected to the building information model. Hence, the digital model acts as a repository of currently available equipment for operations management and the history of diagnoses that support decision-making during the maintenance, retrofitting, and renovation processes. Evidently, the repeated detection of a specific issue, which is unaffected by operations management, should be considered an opportunity to act and enhance the performances of existing building components. Similar to a goods-producing industry, the building management system developed in this study applies the aforementioned methodology to provide services related to indoor comfort and building health. This approach indicates that a method for automatic real-time diagnosis is tested in a case study consisting of a multi-use and large public building. The current paper, which is an extended version of the one presented in the Creative Construction Conference 2018, deepens the decision support tool and the supervision policy. Moreover, the developed system is contextualized by providing an example of use case and highlighting the step forward in the field of smart buildings.     

Constraint-based design using an operational approach

Constraint-based design, which explicitly represents and operates upon constraints, has been recognized as a promising tool for achieving intelligent support of design, particularly the design of mechanical parts or assemblies. It is essential for a constraint-based system to realize the constraint-solving capability. This paper presents an operational approach to constraint solving using incremental feature operations. The approach is based on an operational interpretation of constraints, i.e. the constraint satisfaction is carried out in terms of operations incrementally. A grammatic formalism is used for operational modeling of constraints. Each graph production within a graph grammar corresponds to an operation or a sequence of operations designated for constraint satisfaction that is related to a rule or a procedure. Therefore, a constraint satisfaction process can be represented by a graph grammar parsing process. The operation sequence is planned by graph grammar parsing and invocation of the related rules or procedures. Constraints are then evaluated by invoking the sequenced operations. Features are introduced as higher-level abstractions into the geometric constraints network. This enables reasoning about design validation from topological and manufacturing views.     

基于数字孪生与深度学习技术的制造加工设备智能化方法研究

针对传统制造加工设备在生产加工过程中存在设备与数据信息联系不紧密,设备使用维护多依赖于人工经验等问题,提出了一种新的设备智能化方法。首先,在信息层建立能反映制造加工设备真实状态的数字孪生体;其次,基于历史加工大数据,通过数字孪生体对加工过程的行为进行建模及深度学习和训练,并利用训练好的人工神经网络根据采集到的实时数据来预测制造加工设备下一时刻的状态,使制造加工设备实现物理层与信息层数据的深度融合,拥有自我感知、自我预测的能力,最终实现智能化;最后,以浆料微流挤出成型设备挤出结构系统的智能化实施过程为例,验证了所提出方法的可行性。实例结果表明该设备智能化方法可有效地对挤出结构系统的运行状态进行监测及预测,为后续提高挤出成型精度提供了有效的数据信息。研究表明数字孪生和深度学习技术能够提升制造加工设备的智能化程度,可为未来智能制造的发展提供理论支撑。