Approach to programmable controller building by its main modules synthesizing based on requirements specification for industrial automation

The article deals with the issues of improving the efficiency of production and logistics systems (PLS) of machine-building enterprises through the joint use of MES/APS systems and simulation systems for verification of production plans and decision support. The possibility of using the PlantTwin simulation system on the example of a small machine- building enterprise is considered. Simulation of the operation of the enterprise’s PLS when performing a given production program is performed. Based on the results of simulation modeling, a number of organizational and technological proposals and recommendations for improving the efficiency of the enterprise’s PLS were formed. The proposed solutions were verified by making changes to the simulation scenario and obtaining new results showing their effectiveness.

Section: Application Of the Planttwin Simulation System On The Examplmentioning

confidence: 99%

PlantTwin simulation system as a tool for verifying production plans and supporting decision-making to improve the efficiency of machine-building industries

Nikishechkin¹,

Ivashin²,

Chernenko³

et al. 2020

“…The Fig.5 shows two diagrams that are used to illustrate real-time data received from the STS-MQTT platform in the FRED cloud [14,15]. On the left is the oscillogram for the current values of positions along the X, Y, Z, C and S axes, and on the second for the current values of speed [16,17]. Also in the figure, you can see various text nodes to illustrate other received data from the CNC system in real time (File name, Feed, Program work time, etc.).…”

Section: Testing the Developed Systemmentioning

confidence: 99%

Development of a data collection system for a CNC system using cloud FRED technology and OPC UA specification

Kovalev¹,

Issa²,

Nikishechkin³

et al. 2020

Collecting data from process equipment is currently an interesting task. The use of complex SCADA systems is not always possible and is usually an expensive solution. For some tasks, in-depth analysis of the received technological information is not needed, but visualization of the necessary data is sufficient. In control systems, it is usually not possible to create custom HMI screens. The use of new approaches based on web technologies and cloud solutions allows collecting and visualizing data on web pages and screens of mobile devices. The article shows a solution for collecting data from a CNC system using the OPC UA protocol and subsequent data visualization based on the FRED cloud platform in the required format with the ability to configure HMI screens.

“…1) shows the technological equipment integrated into a single information network, the data from which are transmitted to the OPC UA server or SCADA, and then to the aggregation and provisioning information Web server, or to the upper level of enterprise management (ERP) . In the presented work, a solution was considered when the data arrives at its own information collection server [5]. This means that the server must include all the functionality of the intermediate nodes and supports the work on various communication protocols used by technological equipment [6].…”

Section: Introductionmentioning

confidence: 99%

Big data analytics of the technological equipment based on Data Lake architecture

Kovalev¹,

Nezhmetdinov²,

Kvashnin³

2019

Currently, more and more managers of medium and large industrial companies are thinking about conducting a digital transformation of their enterprise. Each company is forced to strive to find an approach to optimizing production in order to remain competitive in the market. For industrial enterprises, this approach may be a digital transformation using the ideas of Industry 4.0. The digital transformation of an enterprise is a complex and multifaceted process that affects almost all levels of production. At the head of this whole process are data. Data on the work of production must be collected, stored, aggregated, transferred to various levels. Existing methods for storing data are not always suitable for working with BigData, new solutions are needed. The paper shows a comparison of the traditional approach to data aggregation and a promising direction based on the architecture of Data Lake.