SMT (surface mounted technology) refers to the abbreviation of a series of process flows for processing on the basis of printed circuit board (PCB). It is the most popular technology and process in the electronic assembly industry. SMT has developed for more than 40 years and has been widely used in communication, computer, home appliance and other industries. And in the direction of high density, high performance, high reliability and low cost.
With the development of industry 4.0 and the Internet of things, a large number of SMT factories have started the intelligent transformation of “Internet + manufacturing” relying on new technologies such as digital twins. Among them, data visualization enables the traditional information manufacturing industry to achieve unified data management and operation and maintenance by building a multi-dimensional presentation of data, enabling the industry to develop towards intelligence and green.
At present, Tupu software visualization has joined hands with Huawei cloud IOT, Wuhan Lenovo and other enterprises to build SMT smart factories. Through visual enabling digital twin applications, Tupu software visualization has helped more manufacturing factories open the bridge between the physical world and the virtual world, and realize the digital transformation and upgrading of enterprises.
Tupu & Huawei cloud IOT join hands to build SMT smart factory
On August 10, Tupu software and Huawei cloud IOT shared a live broadcast on the theme of “digital twin of Huawei cloud IOT & Tupu visualization to realize industrial digital transformation” on the devrun platform. Around the scene of industrial digital transformation, the live broadcast introduced the application case practice of Huawei cloud iota service digital twin technology combined with Tupo software visualization products in building digital chemical plants, and further explored how digital twin and visualization technology can better help industrial enterprises realize digital transformation and upgrading.
Tupu software provides a solution for building advanced 2D and 3D data visualization. Based on the self-developed HT graphics engine, it can quickly build real-time data-driven plant equipment and production line models, providing rich visual display forms and effects for digital twins; Huawei cloud IOT provides data analysis services based on the IOT asset model, which can integrate IOT data integration, cleaning, storage and analysis, and provide one-stop services for IOT data developers.
Based on the rapid construction of equipment asset model, model attributes and analysis tasks on Huawei cloud IOT platform, the interface dynamic configuration production line model is realized through graph visualization. At present, the SMT digital factory platform has realized intelligent, code free and configurable factory digital management. It can not only parameterize modeling and perform analysis tasks, but also greatly reduce the development threshold and shorten the development cycle.
At present, many manufacturing plants, including Huawei mate 40 manufacturing plant, have an increasingly urgent demand for the digitalization of production lines. By building the SMT digital factory platform and building the digital twin of the mobile phone patch production line, the production process can be improved, the management of manufacturing engineering manufacturers and quality control management can be optimized, and the efficiency of the production line can be greatly improved. At the same time, the rapid realization of IOT data value also helps enterprises reduce operating costs and make the digital transformation and upgrading of factories “within reach”.
Difficulties and solutions of factory digital transformation
At present, more and more factories are actively exploring the digital transformation path of “industry 4.0”, mining data value through data collection, analysis, visualization and other technologies, so as to optimize production. However, in this practice process, it is inevitable to face some common problems, such as:
1. Isolated islands of data and information, with numerous chimneys
A factory may find different suppliers to undertake at different stages because of different projects. Segmented project suppliers lead to different system applications. To put it vividly, multiple systems are not interconnected, that is, they are like independent “chimneys”. Each “chimney” has “smoke”, but they are not interconnected. In the industrial 4.0 stage, non interoperability means an information island, which means that the digital assets of enterprises are scattered, with high maintenance costs and low use efficiency.
2. Slow application launch, time-consuming and labor-intensive
The emergence of information islands stems from the lack of interoperability between different systems. As a result, new applications will be launched “repeatedly to build wheels”: each application will have a lot of repetitive work, waste human and material resources, and take a long time. More importantly, data processing problems caused by new applications: due to the lack of unified modeling, each application needs to process the original data repeatedly. The two “repetitions” make the already high cost even worse.
3. High data analysis threshold
Factories, or enterprises, have a desire to reduce costs and increase efficiency. For example, they want to find rules through analyzing existing data to optimize processes, but they are discouraged because of the high threshold of data analysis. The key reason is that the business scenario is not clear and a good data platform is not found.
The above pain points and difficulties are encountered by most manufacturers in the industrial field during the exploration of “industry 4.0”, and the “application” runs through them. In other words, one of the important reasons for the above problems is that the software developers do not do enough layered decoupling. Based on “application”, the factory has also experienced the evolution of several development modes:
The early mode experienced the evolution from the “chimney” Application of mode 1 to the unified data acquisition platform of mode 2. The reason is the lack of overall planning and low efficiency caused by the independent collection and use of business data, which promoted the derivation of the unified platform. Although the “platform” between the production line and the application is centralized, unified and open, which improves the overall efficiency, the use of data is still independent, and there is no real integration.
At present, “data processing unified twin model”, as a new model, is simultaneously solving the problems of “application decoupling” and “data unified processing”. For example, Huawei cloud IOT uses the “unified twin model” method to abstract the devices in the physical world into the models in the digital world, and transform the interaction between applications and physical devices into the interaction between applications and digital twins, realizing the unified digital processing.
On the basis of Huawei cloud IOT platform, the 3D visualization application layer built by Tupu software has opened the bridge from abstract model to data presentation through SMT virtual factory, giving the effect of simulation visualization of “device model / device instance” expressed in the form of “class / object”. At the same time, the panel data is connected to the Huawei cloud IOT basic platform in real time, mapping the abstract digital twin production line model, and realizing the data-driven and interactive effect of the digital model.
Digital twin practice based on SMT digital factory
The following is the effect and development process of SMT digital chemical plant project based on the visualization of Huawei cloud IOT digital twin & Tupu.
Before the specific explanation, some index concepts involved in the construction of SMT plant data modeling and analysis application are introduced.
1. Introduction to OEE concept
That is, overall equipment effectiveness (OEE). Generally speaking, each production equipment has its own theoretical capacity. To achieve this theoretical capacity, it must be ensured that there is no interference and quality loss. OEE is the ratio of the production capacity of the equipment to the theoretical capacity.
The calculation of OEE involves three dimensions:
Time utilization= Σ Actual running time/ Σ Planned startup time *100%. It is used to evaluate the loss caused by shutdown, including any event that causes planned production shutdown, such as equipment failure, shortage of raw materials, change of production methods, etc;
Performance utilization= Σ [output quantityCycle time for processing a product under the proper state of the equipment]/ Σ Actual running time100%。 Used to evaluate the loss of production speed. Including any factors that make the production unable to run at the maximum speed, such as equipment wear, unqualified materials and operator errors;
Qualification rate = [qualified output quantity] / [output quantity] *100%. It is used to evaluate the quality loss. It is used to reflect the products that do not meet the quality requirements (including reworked products);
Then the final calculation formula is oee=[time utilization][performance utilization][pass rate] *100%, which is a key indicator to measure the comprehensive operation efficiency of equipment, and also a key indicator in many electronic manufacturing plants and other similar plants. Generally speaking, the OEE values of domestic manufacturers are not too high, generally only 70%, or 80%, or even about 40%.
2. Effect drawing of plant twin production line and equipment modeling and analysis
The plant twin production line and equipment modeling analysis can be viewed through some visual management background. The following are the renderings of three different functions.
Figure 1: there is one production line shown, which can be dragged and dropped appropriately. The OEE value of each device can be seen in the figure. Through the asset modeling and analysis capabilities, the OEE of production lines and equipment can be calculated in real time, the key indicators of each equipment can be monitored in real time, and the historical data can be viewed at the same time.
Figure 2: equipment modeling diagram. Through the combination of equipment failure message and equipment model, real-time monitoring of equipment operation status can be realized.
Figure 3: asset analysis chart. Through the asset model analysis capability, you can analyze and monitor whether the reported equipment data is abnormal in real time. For example, the humidity is 45%~63% under normal conditions. If the reported data is not within this range, it is abnormal data. A yellow dot will be displayed on the interface, indicating that the data reported by the equipment here is abnormal. It can be seen that data analysis can be calculated and monitored in real time. If there are serious exceptions, it can even be pushed to the operation and maintenance personnel.
3. Asset modeling practice
Equipment modeling: SMT production line printing machine equipment
When building a digital asset model for things in the physical world, you must first define the asset model, and then create the asset. Generally speaking, there are 7 kinds of equipment in a production line. Let’s take the printing press as an example to see the attributes and presentation methods involved in equipment modeling.
First, the configuration of attributes. For the printing press, three attributes are defined:
Static configuration attribute: ideal printing time and equipment model
Measurement data attributes: printing speed, demoulding speed and printing height
Analysis task attributes: time utilization, performance utilization, qualification rate, OEE
The three attribute data are presented in real time through the equipment information panel of “OEE data” and “business data” of the printer.
The analysis task attribute also has the following calculation configurations:
Conversion calculation: calculate time utilization, performance utilization, OEE and temperature status
Aggregate calculation: calculate actual working hours, actual working hours, and qualified rate
Flow calculation: not used in SMT scenario
The figure above shows the complete example after all parameters are equipped. There are about 70 attributes that simulate the real industry.
At the interaction level, Huawei cloud IOT provides logical judgment and configuration of business functions. Take the “conversion calculation” of the printer analysis task as an example. You only need to read the reported temperature value and make an expression judgment. For example, if the temperature is greater than 25 and less than 35, it is considered to be a normal temperature. Once an alarm occurs, the Huawei cloud IOT platform will automatically push the alarm signal and corresponding key data to the visualization application interface of the map. The visual interface will feed back the alarm signal in real time through dynamic effects. Through interactive clicking, the user can further view the details of the alarm.
Production line modeling: SMT production line
In fact, the concept of production line modeling is the same as that of equipment modeling, and the model is similar. The production line is relatively simple. It mainly calculates the OEE value, that is, the analysis task attribute, including the four indicators related to OEE, as well as conversion calculation, aggregation calculation and flow calculation.
The following figure shows an example of the equipment asset configuration diagram of the printing press and one of the automatically generated 3D production line models:
Next, let’s look at how production line assets are built. As shown in the following figure, the production line assets are divided into three layers:
The first level is factory (parent asset)
The second layer is the production line (sub asset)
The third layer is equipment (sub assets)
The above three figures:
Figure 1 is the logic structure diagram of production line and equipment. Production lines and equipment also have models. The three-tier model constitutes the number of assets in a “parent-child relationship”. Assets come from models and are instantiated from models. At the same time, when models are instantiated as assets, hierarchical relationships can be specified according to business scenarios, and assets are independent of each other.
Figure 2 shows the constructed asset tree. Compared with the logic diagram in the previous figure, this is an example diagram. The figure shows that an electronic factory has three SMT production lines, and each production line has seven SMT equipment.
Figure 3 is the final auto generated 3D model of the factory scene electronic factory. Through the mapping of data model, three SMT production lines are generated, and each production line has 7 SMT devices. Among them, the equipment model, quantity and panel information are automatically generated and associated with real-time data.
Asset operation monitoring
After all product creation and attribute configuration are completed, you can click publish to publish and run the model. When a model is defined, it is a static process. Once it is published, it will be activated. According to the task analysis logic defined in the previous sequence, the system will automatically calculate and obtain real-time results for reporting. All the data can be seen in the following figure.
With the adjustment of the actual production line, the published model may need to be adjusted. On this basis, the visual interface has been automatically linked with the background configuration interface. The following is a comparison of the production line creating / deleting the post furnace AOI instance object. The post furnace AOI equipment of the visual production line model has automatically created / deleted according to the production line data model object configured in the background.
The released production line data can also be displayed in different graphic display modes such as line chart, thermal chart and curve chart according to the needs of the business, so that it is easier to understand and analyze the data for assisting management decision-making:
Above, based on the SMT digital chemical plant built by Tupu visual chemical plant, the IOT digital twin of Huawei cloud, the orderly and controllable production can be realized by making the production line production process transparent. The intelligent, code free and configurable one-stop solution can quickly build the production line, reduce the development threshold and shorten the development cycle to a certain extent. The normal online time of the application is reduced from 6-9 months to 3 months or less. At the same time, the twin modeling analysis + data visualization scheme realizes the connection of all elements of SMT digital factory, drives intelligent production with data, and greatly improves the data utilization efficiency. Relying on the generalization of the above digital base, the same technical scheme can also be applied to more industries and enterprises undergoing industrial digital transformation.
Tupu & Lenovo, Wuhan SMT intelligent production line helps to return to work and production efficiently
In 2019, Tupu software helped Wuhan Lenovo build a new 3D visual simulation operation and maintenance system for SMT Mounter production line. SMT operation and maintenance system is based on graphic visualization technology, which can quickly file various basic information of the production line, digitize and monitor in real time, and realize the full life cycle and fine management of the patch production line. Through 3D production line modeling and business linkage, it can remotely monitor the operation status of each production line, realize “unmanned and automated” operation, and help enterprises increase production and efficiency. In the maintenance of some equipment and the treatment of downtime, the efficiency should be improved by at least 20% than before.
During the epidemic period, the production uncertainty of the affected people put forward higher requirements for the automation level, quality improvement and efficiency increase of the manufacturing plant. As Lenovo’s most advanced industrial factory in the world, the Lenovo Wuhan industrial base, from seriously affected by the epidemic to short-term recovery of 10000 people to full production, has cooperated with the upstream and downstream of the supply chain to resume work and production at the same frequency, benefiting from its own digital transformation vigorously promoted. Including Wuhan Lenovo industrial base, Tupu software SMT visualization scheme has been implemented in multiple intelligent factories, which will also help more enterprises solve the challenges faced in intelligent manufacturing and digital transformation.
Visualization of SMT production line monitoring and management for Tupu software intelligent manufacturing
The visualization of Tupu software adopts lightweight modeling and powerful visualization engine technology to build a brand-new SMT process monitoring and management visualization system case, creating an intelligent and green digital smart factory. It provides new ideas for enterprises that want to make digital transformation, such as intelligent workshops, intelligent assembly plants, engineering machinery and equipment plants, automobile manufacturing industry, logistics warehouse management and other industries.
SMT data visualization
According to the needs of industry operation, government and enterprise decision-making, the main data of the whole production line can be displayed through the multi-dimensional data panel. Based on the construction and operation results of user data, the boring and scattered data can be graphically and scenariously displayed to show the OEE (comprehensive efficiency of equipment), time utilization, performance utilization, output completion, through rate, equipment utilization, defect rate, IOT connection rate, etc. of each line.
Relying on the graphic components and interface design, the UI part realizes the data dynamic loading effect on the data panel, and more intuitively compares the chart data. The visual effect felt by the user is a higher level compared with the static chart data!
Equipment information visualization
Through the docking data interface, the business data of key equipment in the three-dimensional scene can be visualized, the status of key equipment can be displayed in the page, and the equipment values and icons of different colors can represent different equipment status. In addition, the intelligent early warning analysis function is added. Once the equipment data exceeds the established threshold and the historical data is analyzed and judged, the equipment will be flashing red in the three-dimensional scene, and the conventional manual patrol inspection will be converted to intelligent patrol inspection, so as to timely understand the health status of the equipment.
Learn from Xianghua to build a localization independent engine
Since its inception, Tupu software has always insisted on independent research and development of visualization products to create its own localization independent engine. As a partner of Huawei, it not only has a close cooperative relationship, but also has the same corporate philosophy.
Relying on their respective technology accumulation and industry practice, deepen cooperation, further promote the optimization and upgrading of their respective product systems, promote full cooperation in key industries such as industry, city, communication and transportation, and build perfect scenario solutions for customers.
Ren Zhengfei said, “what does Huawei have? We don’t even have limited resources, but our employees work very hard to create resources. As the international song says, don’t say we have nothing. We are the masters of tomorrow.” there has never been a savior, nor an Immortal Emperor, but all by ourselves. “.
Earlier, in the face of U.S. sanctions, the U.S. Department of Commerce issued an export ban on its website, requiring foreign enterprises using U.S. chip manufacturing equipment to obtain an export license before supplying goods. Huawei’s ban and upgrade once again challenged the bottom line of the international supply chain and industrial chain. Huawei issued a document in its heart community, “there are no scars, there is no rough skin and thick flesh, and heroes have suffered many hardships since ancient times”. The article only has two sentences: “looking back, there are bumps” and “looking forward, never give up”.
As well as the latest news, the United States has banned any enterprise from providing 5g chips for Huawei, and is not allowed to use machines to produce 5g chips for Huawei. In order to suppress the development of Chinese science and technology enterprises, they even made various shady moves, detained Meng Wanzhou, Ren Zhengfei’s daughter, and suppressed Huawei enterprises in a disguised form. As well as cracking down on one Chinese high-tech enterprise after another.
However, as an enterprise with a “wolf” culture, Ren Zhengfei chose to be more courageous and more frustrated. He wholly built his own chip company in China, and all the industrial chains and production technologies were personally developed by Huawei.
The external pressure on the United States tells us that we must become stronger and independent if we want to become stronger. China’s development is inseparable from the independent scientific and technological innovation of enterprises. We should strive for self-improvement. The important theory that “science and technology are the primary productive forces” also tells us that only through independent research and development of our own technological products can we face all challenges on the road of future science and technology.
Localization replaces the general trend, and Tupu software adheres to independent control
At the 36th collective study of the Political Bureau of the CPC Central Committee, the general secretary stressed that “we should firmly hold the ‘bull nose’ of independent innovation of core technologies, grasp the frontier technologies of network development and key core technologies with international competitiveness, accelerate the promotion of domestic independent and controllable substitution plans, and build a safe and controllable information technology system.”, The ZTE incident, Huawei incident and other incidents tell us that if we want to be uncontrolled by people, we must spare no effort to build our own “controllable” technology.
Tupu software has long been committed to the construction of system visualization in diversified industries. Based on the accumulated experience of the technical industries involved, Tupu software has created representative visual control systems in many industries through independent innovation and R & D of technical products. At the forefront of future scientific and technological progress, Tupu software will continue to follow the pace of progress and innovate more solutions for industrial Internet visualization systems. Comply with the development of industry 4.0 and the construction of new infrastructure such as 5g network and data center, constantly improve products and innovate to meet the opportunities and challenges given by future science and technology!