Cherepovets Steel Mill (Cherepovets Steel Mill) Severstal (Data-Center Automation: Data-Track and Expert Base)

2018

MES (DCA, PTG). Construction and deployment of metal tracking system (production accounting) at units and sections of bent section shop No. 2

The project includes the following MES technologies (according to MES-11): the DCA (Data Collection/Acquisition) function - data collection and storage, PTG (English Product Tracking and Genealogy) - product tracking and genealogy. Provides the ability to obtain information about the status and location of an order at any time. Status information includes who is performing the task, components, materials, and their suppliers, lot number, serial number, current manufacturing conditions, process disturbance warnings, reprocessing data, and other product-related events. Real-time tracking creates historical data about the progress of production processes. This data ensures the traceability of the components and their use in each final product. The solution is based on the DATA-TRACK platform.

The created production accounting system provided:

• Real-time production data collection.
• Control of metal movement and production processes at production units.
• Filling product passports with technological parameters and events. Provision of product passports with related process information in the form of schedules. Formation of product passports and related process information.
• Transfer of information on production tasks to APCS, identification of performance of production tasks.

Project implementation date: 2017 - 2018

MES (DCA, PM). Mathematical model systems for dynamic reconfiguration of a five-year mill

The project includes the following MES technologies (according to MES-11): DCA (Data Collection/Acquisition) function - data collection and storage, PM (English Process Management) - production process management. Mathematical model systems track the production process at endless cold rolling mill 1700 and automatically determine control actions, as well as support operator decision-making to perform corrective actions and improve production activities.

Technologies for creating digital twins are no longer just a modern trend, but a standard in industry. At the same time, it is believed that there are traditional tools of world brands for designing a production system. These tools are well suited to design from scratch, but it is almost impossible to describe an existing production - too much data needs to be described, despite the fact that the current production system is constantly changing.

Knowledge of the EXPERT BASE analytical system allows DATA CENTER Automatics to solve problems of this class.

The System of Mathematical Models of Dynamic Rearrangement of the Rolling Mill was developed by DATA-CENTER Automation, and the system was successfully implemented at PAO Severstal for the five-year continuous cold rolling mill 1700.

Gusts of inter-interval seams decreased by 25%, and the length of the wedge of the diversity of the strip during the transition from one section of the strip to another decreased by an average of two times.

The system made it possible to reconfigure the mill at the speed of passing the weld in automatic mode, without the participation of the operator when switching from rolling one section of the strip to rolling another section of the strip (changing the steel grade, width and thickness of the strip - inter-interval weld), without which truly productive work is impossible. Before the introduction of the system, the reconfiguration of the five-flight mill 1700 was carried out by the operator in manual mode at reduced weld speeds.

The work was done on a turnkey basis, starting with the design and ending with the implementation of the system.

The question of developing a modern effective model of a continuous cold rolling mill in a welded joint mode is a complex theoretical task of applied mathematics. The task is complicated by an order of magnitude in the case when the work must be performed at the operating mill with minimal interference with its equipment.

The success of the created model is due to the fact that the firm has been engaged in multidimensional data analysis since 1993. It was this year that DATA-CENTER, the predecessor of DATA-CENTER Automation, delivered the STARC (Statistics, Analysis, Recognition, Clustering) system to Parsytec GmbH, Germany. Parsytec is well known in metallurgy as a developer of equipment and software for controlling the quality of rolled strip.

In 2014, the company "DATA-CENTER Automation" and the Ural Federal University decided to create a basic department "Big Data Analytics and Video Analysis Methods."

The EXPERT BASE analytical platform has been created and is developing in close cooperation with the university, which allows us to combine the scientific and production perspective.

Project implementation date: 2016 - 2018

2017: MES (DCA, PTG). Construction and deployment of metal tracking system (production accounting) at units and sections of Bent Section Shop No. 1

The project includes the following MES technologies (according to MES-11): the DCA (Data Collection/Acquisition) function - data collection and storage, PTG (English Product Tracking and Genealogy) - product tracking and genealogy. The project provides the ability to obtain information about the status and location of the order at each time. Status information includes who is performing the task, components, materials, and their suppliers, lot number, serial number, current manufacturing conditions, process disturbance warnings, reprocessing data, and other product-related events. Real-time tracking creates historical data about the progress of production processes. This data ensures the traceability of the components and their use in each final product. The solution is based on the DATA-TRACK platform.

The created production accounting system provided:

• Real-time production data collection.
• Control of metal movement and production processes at production units.
• Filling product passports with technological parameters and events. Provision of product passports with related process information in the form of schedules. Formation of product passports and related process information.
• Transfer of information on production tasks to APCS, identification of performance of production tasks.

Project implementation date: 2016 - 2017

2016: MES (DCA, PTG). Construction and deployment of metal tracking system (production accounting) in cold rolled products production

The project includes the following MES technologies (according to MES-11): the DCA (Data Collection/Acquisition) function - data collection and storage, PTG (English Product Tracking and Genealogy) - product tracking and genealogy.

Provides the ability to obtain information about the status and location of an order at any time. Status information includes who is performing the task, components, materials, and their suppliers, lot number, serial number, current manufacturing conditions, process disturbance warnings, reprocessing data, and other product-related events. Real-time tracking creates historical data about the progress of production processes. This data ensures the traceability of the components and their use in each final product. The solution is based on the DATA-TRACK platform.

The created production accounting system provided:

• Real-time production data collection.
• Control of metal movement and production processes at production units.
• Filling product passports with technological parameters and events. Provision of product passports with related process information in the form of schedules. Formation of product passports and related process information.
• Transfer of information on production tasks to APCS, identification of performance of production tasks.

Project implementation date: 2013 - 2016

2015: MES (DCA, PTG). Construction and deployment of a metal tracking system (production accounting) at the units of Sheet Rolling Shop No. 1.

The project includes the following MES technologies (according to MES-11): the DCA (Data Collection/Acquisition) function - data collection and storage, PTG (English Product Tracking and Genealogy) - product tracking and genealogy.

Provides the ability to obtain information about the status and location of an order at any time. Status information includes who is performing the task, components, materials, and their suppliers, lot number, serial number, current manufacturing conditions, process disturbance warnings, reprocessing data, and other product-related events. Real-time tracking creates historical data about the progress of production processes. This data ensures the traceability of the components and their use in each final product. The solution is based on the DATA-TRACK platform.

The created production accounting system provided:

• Real-time production data collection
• Control of metal movement and production processes at production units.
• Filling product passports with technological parameters and events. Provision of product passports with related process information in the form of schedules. Formation of product passports and related process information.
• Transfer of information on production tasks to APCS, identification of performance of production tasks.

Technical vision was used for production metering and product tracking.

The following are examples of tracking at various locations.

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Фото: Data center Automation

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Фото: Data center Automation

Project implementation date: 2014 - 2015

2014: MES (DCA, PTG). Construction and deployment of the metal tracking system (production accounting) at the rolling mill

The project includes the following MES technologies (according to MES-11): the DCA (Data Collection/Acquisition) function - data collection and storage, PTG (English Product Tracking and Genealogy) - product tracking and genealogy.

Provides the ability to obtain information about the status and location of an order at any time. Status information includes who is performing the task, components, materials, and their suppliers, lot number, serial number, current manufacturing conditions, process disturbance warnings, reprocessing data, and other product-related events. Real-time tracking creates historical data about the progress of production processes. This data ensures the traceability of the components and their use in each final product. The solution is based on the DATA-TRACK platform.

The created production accounting system provided:

• Real-time production data collection
• Control of metal movement and production processes at production units.
• Provision of filling of certificates of operation of rolling mills 150, 250, 350 with process parameters and events. Provision of product passports with related process information in the form of schedules. Formation of product passports and related process information.
• Transfer of information on production tasks to APCS, identification of performance of production tasks.

Project implementation date: 2013 - 2014

2013: MES (DCA, PTG). Construction and Deployment of Metal Tracking System (Production Accounting) in Electric Steel Smelting Plant

The project includes the following MES technologies (according to MES-11): the DCA (Data Collection/Acquisition) function - data collection and storage, PTG (English Product Tracking and Genealogy) - product tracking and genealogy.

Provides the ability to obtain information about the status and location of an order at any time. Status information includes who is performing the task, components, materials, and their suppliers, lot number, serial number, current manufacturing conditions, process disturbance warnings, reprocessing data, and other product-related events. Real-time tracking creates historical data about the progress of production processes. This data ensures the traceability of the components and their use in each final product. The solution is based on the DATA-TRACK platform.

The created production accounting system provided:

• Real-time production data collection.
• Control of metal movement and production processes at production units.
• Provision of heat data sheets filling with process parameters and events. Provision of heat data sheets with related process information in the form of schedules. Formation of heat data sheets and related process information.
• Transfer of information on production tasks to APCS, identification of performance of production tasks.

Project Implementation Date: 2013

2010: MES (DCA, PTG, QM) и BI. Automated system for monitoring and statistical control of production processes "AC UPC Technologiya"

In the project Automated System of Statistical Control of Processes (AS UPC) "Technology," the company pioneered the construction of global systems covering a large enterprise, allowing real-time analysis of enterprise data and achieving economic effect.

The project includes the following technologies MES (according to MES-11): DCA a function (Data Collection/Acquisition) collection and, data storage PTG (Product Tracking and Genealogy) product tracking and genealogy, QM (English Quality Management) quality management.

Since the project was created to support management decisions in the field of product quality management, BI technology is provided - global analysis of production data.

The company "DATA-CENTER Automatics" carried out the following works within the framework of the NP SKP "Technologiya" project:

• Manufacturing survey.
• Design.
• Supply and installation of sensors, monitoring devices, server equipment.
• Tracking systems in metal the unit were introduced or upgraded on all units.
• The results of micro, macro and mechanical tests of the metal were collected by transmitting data from the automated systems of the converter laboratory of chemical analysis.
• Data collection on metal sorting and rejection by means of data transfer from enterprise systems was implemented, comparison of defect type, culprit unit name with product unit numbers was carried out.
• Monitoring of the movement of products on a through redistribution, as well as inter-unit and inter-unit tracking of products were implemented.
• Order data is obtained from the ERP system.

At the time of commissioning of the NPP system, about 7,000 data sources were connected. Each year the Customer independently connects additional sources. Before the implementation of the NPP system, the Process Control System at the plant did not have the opportunity to combine data from different production systems into a single information field. Collection and storage of process parameters was carried out by local APCS, providing information storage in the interval of 2-30 days and access to information through screen forms and/or paper protocols. Process parameters were stored as generalized data without reference to product units or as measured parameters tied to astronomical time. Many sites did not have automated information collection and storage systems at all. The main process parameters were recorded on the recorders. Product tracking was not consolidated into a single system.

At present, PAO Severstal effectively uses the Technology AS system as part of the ongoing business process to improve production.

Technological personnel of workshops and quality control centers were trained in the use of mathematical statistics methods.

When analyzing the quality of products, reports generated by the NPP system of the Process Information System are used. Metallurgical experts conduct in-depth studies of the accumulated data to develop recommendations for changing production.

The effect of a change in production per year exceeds the cost of deploying the system. We can say that the system fully pays for itself annually (see "Development of the procedure for assigning slabs of the strip steel converter shop to orders based on statistical methods "//Journal" STEEL. " - M., 2015. – № 1. - S. 88-92).

It should be noted that in 2008 the term Big Data had just begun to be introduced in the academic environment and spread in the business press, and the term Continuous Intelligence had not yet appeared. "DATA CENTER Automation" was again ahead of global trends.

In the AC UPC Technology project, the first versions of the DATA-TRACK and EXPERTBASE platforms showed their stability and performance.

Project Implementation Date: 2008 - 2010