Showing papers on "Process architecture published in 2020"

Business process improvement using Object-Process Methodology

Abstract: For decades, business process improvement (BPI) has been a persistent and expensive concern that spans across many industry sectors. We present OPM‐BPI—a model‐based method to improve business processes using ISO 19450—Object‐Process Methodology (OPM). The approach compares favorably to state‐of‐the‐art business process languages and approaches, such as Business Process Modeling Notation (BPMN). An aviation manufacturing company case study of safely removing a part from an aircraft and reinstalling it demonstrates the method. We show how using OPM‐BPI enables removing a large portion of the supporting objects, and how related processes can be eliminated or merged, achieving considerable model simplification that represents a significantly improved, more effective and less wasteful business process.

The Value of Integrating Power and Process in the Petrochemical Industry: Saving Money With One Visualization and Reporting Environment

Abstract: The coord ination of large distributed measurement and control systems, like supervisory control and data acquisition (SCADA) systems and other process control implementations, require networks that connect thousands of remote devices. Demand for infrastructures to deliver a full spectrum of control and monitoring capabilities within global operations is increasing. The conventional infrastructures and process automation domains don't commonly communicate. The advancement of industrial communications provides value to the industry when logically integrated to combat rising costs. Unifying power and process systems within an operation gives value by creating one visualization and reporting environment. This article outlines a convergent use of the International Electrotechnical Commission (IEC) Standard 61850 within process control networks to provide enhanced process control, monitoring, and energy management. It discusses the benefits of unified power and process architecture with enhancements provided by visualization, archiving, and reporting.

Performance prediction based on neural architecture features

Abstract: Neural Architecture Search (NAS) usually requires to train quantities of candidate neural networks on a dataset for choosing a high-performance network architecture and optimising hyperparameters, which is very time consuming and computationally expensive. In order to resolve the issue, the authors try to use a performance prediction method to predict the model performance with little or even no training steps. They assume that the performance is determined once the architecture and other hyperparameters are chosen. So they first extract the sequence features of the chain-structured neural architecture by introducing the N-grams model to process architecture textual description. Subsequently, based on the extracted neural architecture features, they use the appropriate regression model to predict validation accuracies for a modelling learning curve. Through a series of experimental comparisons, they verify the effectiveness of the authors’ proposed performance prediction method and the effective acceleration of the NAS process.

Conversation process customization method and device

Abstract: The invention discloses a dialogue process customization method and a device. In the dialogue process customization method, a dialogue resource customization request is acquired by a customization server, a target dialogue resource from a pre-configured dialogue resource library is determined according to dialogue resource customization information, and then the target dialogue resource is sent, so that a customization client can configure the target dialogue resource into a dialogue process architecture to determine a dialogue process. By means of the dialogue process customization method, non-professional users can customize the dialogue process more freely, and the dialogue process customization method can be suitable for numerous dialogue customizing scenes.

Reference Exascale Architecture (Extended Version)

Abstract: While political commitments for building exascale systems have been made, turning these systems into platforms for a wide range of exascale applications faces several technical, organisational and skills-related challenges. The key technical challenges are related to the availability of data. While the first exascale machines are likely to be built within a single site, the input data is in many cases impossible to store within a single site. Alongside handling of extreme-large amount of data, the exascale system has to process data from different sources, support accelerated computing, handle high volume of requests per day, minimize the size of data flows, and be extensible in terms of continuously increasing data as well as an increase in parallel requests being sent. These technical challenges are addressed by the general reference exascale architecture. It is divided into three main blocks: virtualization layer, distributed virtual file system, and manager of computing resources. Its main property is modularity which is achieved by containerization at two levels: 1) application containers - containerization of scientific workflows, 2) micro-infrastructure - containerization of extreme-large data service-oriented infrastructure. The paper also presents an instantiation of the reference architecture - the architecture of the PROCESS project (PROviding Computing solutions for ExaScale ChallengeS) and discusses its relation to the reference exascale architecture. The PROCESS architecture has been used as an exascale platform within various exascale pilot applications. This paper also presents performance modelling of exascale platform with its validation.