Intelligent production lines and intelligent laboratories are changing the production model of traditional enterprises, freeing people from repetitive operations, harsh environments and heavy flow operations. For steel plants, the intelligence of the main production line and the intelligence of the machine-side laboratory near the unit exit are extremely important for comprehensively improving labour productivity, reducing equipment accidents, quality accidents and safety accidents, and comprehensively improving product quality and company brand.
Made in China 2025 has effectively promoted the intelligent development of steel plants. At present, robots have widely played an important role in various steel plants, especially in medium-to-high temperature, high-risk, and difficult areas, which further demonstrate the power of robots.
Intelligentization of steel plate strip production lines in steel plants
The partial intelligence of the steel plant has laid a good foundation for the intelligence of the main production line, but the intelligence of the main production line is the goal and direction.
1. Intelligent architecture of the main production line
The production line is an intelligent platform, digitalization is the foundation of intelligence, the industrial internet is the support of intelligence, and the intelligent centre is the core of intelligence. The current overall automation level of the steel plant production line is relatively high, and there is not much manual participation in adjustment and control. This means that the digitization of the online collection system for product quality and the digitization of the online collection system for equipment status are particularly important. Once the production line is digitized, intelligence will not be far behind.
2. Digitization of steel plate strips quality online collection system
Listed below are the online acquisition systems for the quality of steel plate strip products, which are also the actual product quality parameters that users are currently concerned about and need to be focused on digitizing.
- Solution online detection system
- Ingredient content online detection system
- Coating film thickness online detection system
- Colour difference online detection system
- Mechanical properties online testing system
- Roughness online detection system
- Plate width and thickness online detection system
- Surface defect online detection system
Here are 2 examples to illustrate
1) Coating film thickness online detection system
Used for online real-time detection of coating film thickness such as fingerprint-resistant film, a passivation film, insulating coating, colour-coated plate coating, and oil coating amount on the surface of coated products. This system provides a basis for online real-time and accurate control of coating film thickness.
2) Mechanical properties online testing system
Used for mechanical properties of strip steel (hardness, yield strength, tensile strength, elongation after fracture, hardened layer depth, C layer penetration depth, N layer penetration depth, residual stress, N, R, retained austenite, delamination hardness, Uniform elongation) online real-time detection provides a basis for real-time and accurate control of the mechanical properties of the strip.
3. Digitization of equipment status online collection system
The following lists some of the equipment that may affect the normal operation of the main production line of the steel plant. The status of this equipment is collected and digitized online, which plays a key role in the status control and normal operation of the production line.
Online collection system for rotating equipment status
Rotating equipment mainly collects two parameters: temperature and vibration. Accurate collection of these two parameters, as well as status analysis and control, can effectively monitor the effective operation of rotating equipment.
4. Intelligent Center
The intelligent centre is the intelligent core of the production line. Its function is just like the human brain and the CPU of a computer. It is powerful, and only intelligent systems can be powerful.
Intelligent Center Functions
The expert system collects “production process parameters” and “equipment status parameters”, compares them with the “knowledge base”, and establishes new optimization plans and optimization models for production line control. At the same time, relevant parameters and data are stored in the “knowledge base”, and the “knowledge base” data is continuously accumulated, the model is continuously optimized, and the solutions are continuously enriched. At the same time, the relevant status of the production line can be transmitted and displayed in time.
The current automation level of steel plant production lines is relatively high. In terms of intelligence, efforts should be focused on the digitization of production processes and equipment status. Once digitization is solved, intelligence is not far away.
Intelligentization of machine-side laboratories in plate and strip steel plants
1. Current status of machine-side laboratories in plate and strip steel plants
At present, most steel plants need to quickly detect the specifications, dimensions and quality characteristics of steel coils at and near the exit of the finished unit. Rapid testing is generally done by setting up a laboratory next to the machine in this area, and the operators operate according to the requirements of process control and provide timely feedback on quality results for the adjustment of the process parameters of the unit.
The conventional on-machine laboratory testing process in plate and strip steel plants is as follows:
The operator manually takes the large sample, manually detects the length, width and thickness of the large sample, manually carries the large sample to the sample preparation area as a sample preparation and retains the sample, manually carries the large sample to the processing equipment, and manually processes the large sample as a test sample. Mark the sample code, manually test the sample, manually judge the test results, manually enter the test results into the computer or record them in the test result record book, manually process the waste samples after testing, and complete the entire process of sample testing in the on-machine laboratory.
Conventional on-machine laboratories have at least the following problems:
(1) Low labour productivity.
All work requires manual operations, resulting in a large amount of operator input.
(2) The quality of testing cannot be guaranteed.
The quality of inspection is directly related to the operator’s sense of responsibility, technical level, mood and physical condition, and it is difficult to control the quality of inspection.
(3) Safety cannot be guaranteed.
There are risks such as the sample scratching the body and the processing equipment breaking fingers.
(4) The detection speed is slow.
Each process requires operators to complete it in sequence. It cannot be like an unmanned laboratory where all equipment can run at the same time.
(5) High cost.
The salary cost of operators is rising, product quality problems cause product downgrades and even quality objections cause economic losses, etc. The direct and indirect costs are relatively high.
2. Necessity and feasibility of machine-side laboratory intelligence:
Blacklight factories and blacklight laboratories are currently popular and vigorously developed innovative projects that are in line with national guidelines and policies. Intelligentization of machine-side laboratories is necessary to improve labour productivity, ensure testing quality, ensure personal safety, and improve product quality and corporate brand. This is an important component of smart factories.
The intelligent machine-side laboratory is a branch of the smart workshop or smart factory. On-machine laboratories do not involve direct product production. The configuration of on-machine laboratory processing and testing equipment is also relatively simple. It can be said that the machine-side laboratory is relatively independent and relatively simple, and it is completely feasible to make the machine-side laboratory intelligent. Develop fully automatic processing and inspection equipment, configure relevant robots and vision systems, establish an industrial Internet network, and develop virtual and real digital twin functions and mobile APP functions. If you have the ability or need, add self-learning, self-diagnosis and self-diagnosis with “intelligent” capabilities. Neuron network technology to solve problems and realize laboratory intelligence
3. Case study of intelligent on-machine laboratory:
Examples of smart project projects for labs next to hot-dip galvanizing production units are as follows:
On-machine laboratory functions:
Quickly process the large samples cut from the unit as test samples, quickly detect the hot-dip galvanized product sample width, sample thickness, U-bend performance, V-bend adhesion performance, roughness performance, and defect stamping performance to quickly provide the first-class solution for the unit Hand-made product quality performance.
1) The entire on-machine laboratory is unmanned for testing.
The entire on-machine laboratory is divided into three processes from sample testing.
(1) Sample sampling process
The AGV is equipped with a robot. The AGV robot grabs 2 large samples from the sample delivery platform of the unit and places 1 large sample on the large sample placement platform for testing by the machine-side laboratory. Another large sample is placed on the AGV car and sent to the sample preparation storage area for storage as a retained sample.
(2) Sample processing process
The ground-rail robot grabs the large sample from the large sample placement platform and places it on the fully automatic laser-cutting machine. The fully automatic laser cutting machine first determines the type of test sample and the processing position of the sample based on the sample code from the production unit; then the laser engraving machine performs laser marking on the sample. The laser cutting machine then laser cuts the sample. The ground-orbiting robot grabs all samples into the sample box, and at the same time grabs the waste samples into the waste sample box, completing the entire sample processing process.
(3) Sample testing process
The ground rail robot transports the samples in the sample box to the corresponding fully automatic testing equipment, such as a fully automatic U-bend detector, a fully automatic roughness detector, etc. All fully automatic testing equipment detects, processes and transmits test samples in their own way.
2) The entire machine-side laboratory has four major functions.
(1) Unmanned detection function
From sample sampling, to sample processing, to sample testing, and finally testing data processing and transmission, everything is unmanned, realizing unmanned laboratory functions.
(2) System reliability function
The relevant fully automatic processing and testing equipment all have a manual operation and fully automatic operation functions. Key equipment has backup machines. For example, ground rail robots can replace AGV robots. The ground rail robots can be used on one standby, and the system computers can be used on one standby to ensure that the machines are nearby. The entire laboratory system can operate normally and effectively.
(3) Safety and environmental protection functions
The dust removal device of the laser cutting machine adopts noise reduction measures, and the noise is controlled below 70 decibels. All robot operating areas are separated by guardrails. The entire machine-side laboratory is monitored by probes inside and outside. The AGV car is a human-machine hybrid. It stops when people approach it. The speed is controllable. The outer shell is made of plastic, so it will not cause personal injury even if it hits a person.
(4) Remote monitoring function
The system configuration combines virtual reality with digital twin software and mobile phone APP software, enabling remote monitoring and mobile monitoring.
The current machine-side laboratories are mainly manual operations. In terms of intelligence, the focus is on the full automation of a single set of equipment. Once full automation is solved, intelligence is not far away. The intelligence of the machine-side laboratory can be considered simultaneously with the intelligence of the main production line.
Case Study of Intelligent Laboratory in Plate and Strip Steel Plant
At present, most steel plant laboratory samples are processed and tested manually. This results in low labour productivity, slow inspection speed, high safety risks, and high inspection quality risks.
Laboratory intelligence case
Use laser cutting machines and high-speed circular saws to replace traditional sawing machines to complete rough processing; use drawing processing centres, impact processing centres and CNC lathes to replace traditional manual processing equipment to complete finishing processing; add a three-dimensional sample preparation warehouse to realize cutting backup samples Automatic classification and storage. A new information management system (system management and control and communication functions, digital twin function and mobile APP function) and sample handling system (including inkjet coding, scanning code, robots, etc.) have been added, and the original sample incoming roller table and The new processing equipment is connected in series and combined with the information management system to realize automated functions such as sample information identification, sample rough cutting, sample edge thinning, sample finishing, sample preparation, classification and storage.
After the system is put into operation, laboratory sample processing will be unmanned, solving the problem of relying on a large number of processing equipment and operators to complete heavy processing tasks, comprehensively improving labour productivity, speeding up sample processing, and reducing personnel safety risks, thus Comprehensively improve the level of laboratory automation.