Independent innovation and localization technology: SMT production line monitoring and management visualization of intelligent manufacturing

SMT (Surface Mounted Technology, surface mount technology) refers to the abbreviation of a series of process processes based on printed circuit boards (Printed Circuit Board, PCB), and is the most popular technology and process in the electronics assembly industry. SMT has been developed for more than 40 years and has been widely used in communications, computers, home appliances 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 relying on new technologies such as digital twins have begun the road of intelligent transformation of "Internet + manufacturing". Among them, data visualization allows the traditional information manufacturing industry to achieve unified data management, operation and maintenance by constructing data in multiple dimensions, and empowering the industry to develop toward intelligence and green.

At present, Tupu Software Visualization has joined hands with Huawei Cloud IoT, Wuhan Lenovo and other companies to build SMT smart factories, empowering digital twin applications through visualization, helping more manufacturing plants to bridge the bridge between the physical world and the virtual world, and realize the digital transformation of enterprises upgrade.

& Huawei Cloud IoT work together to build an SMT smart factory

On August 10th, Tupu Software and Huawei Cloud IoT jointly shared a live broadcast on the topic of "Huawei Cloud IoT Digital Twin & Tupu Visualization to Realize Industrial Digital Transformation" on the DevRun platform. Focusing on industrial digital transformation scenarios, the live broadcast introduced the application case practice of Huawei Cloud IoTA service digital twin technology combined with Tupu software visualization products in building a digital factory, and further explored how digital twins and visualization technologies can better help industrial enterprises achieve digital transformation and upgrading .

Tupu Software provides solutions for building advanced 2D and 3D data visualization. Based on the self-developed HT graphics engine, it can quickly build real-time data-driven factory equipment and production line models, and provide 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 models and model attributes and analysis tasks on the HUAWEI CLOUD IoT platform, an interface-based dynamic configuration production line model was realized through Tupu visualization. At present, the SMT digital factory platform has realized intelligent, code-free, and configurable digital factory 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 the Huawei South Plant (Huawei Mate 40 production plant), have an increasingly urgent demand for the digitization of production lines. By building the SMT digital factory platform solution to build a digital twin of the mobile phone patch production line, it can improve the production process, optimize the management of manufacturing engineering manufacturers and the management of quality control, and greatly improve the efficiency of the production line. At the same time, the rapid realization of the value of IoT data will also help companies reduce operating costs and make the digital transformation and upgrading of factories "at your fingertips."

Pain and Difficulties of Factory Digital Transformation and Solutions

At present, more and more factories are actively exploring on the road of "Industry 4.0" digital transformation, mining data value through data collection, analysis, visualization and other technologies to optimize production. However, in this practice process, it is inevitable to face some common problems, such as:

1. Data and information islands, with many chimneys

A factory, at different stages, because of different projects, it is possible to find different suppliers to undertake. Segmented project suppliers lead to different system applications. To put it in perspective, if multiple systems are not interoperable, they are like independent "chimneys". Each "chimney" has "smoke", but they are not interoperable. In the industry 4.0 stage, non-interworking means information islands, which means that the company's digital assets are scattered, maintenance costs are high, and use efficiency is low.

2. The application launch is slow, time-consuming and labor-intensive

The emergence of information islands stems from the non-interoperability between different systems, which leads to the "repetitive wheels" when new applications go online: each application goes online, there is a lot of repetitive work, waste of manpower and material resources, and time-consuming. More importantly, the data processing problems brought about by new applications: Due to the lack of unified modeling, each application needs to process the original data repeatedly. The two "duplications" have made the already high cost even more "worse."

3. High threshold for data analysis

Factories, or companies, have a desire to reduce costs and increase efficiency. For example, they want to find patterns by analyzing existing data to optimize processes, but they are discouraged because of the high threshold of data analysis. The most critical reason for this is that the business scenario is not clear, and a good data platform has not been found.

The above pain points and difficulties are encountered by most manufacturers in the industrial field in the process of exploring "Industry 4.0", and "applications" run through them. In other words, the failure of software developers to achieve sufficient layered decoupling is one of the important reasons for the above-mentioned problems. Based on "applications", the factory has also experienced the evolution of several development models:

The early model experienced the evolution from the "chimney" application of model one to the unified data acquisition platform of model two. The reason was the lack of overall planning and inefficiency caused by the separate collection and use of business data, which promoted the derivation of the unified platform. Although the overall efficiency has been improved through the centralized and unified opening of the "platform" between the production line and the application, the use of data is still independent and no real integration has been achieved.

At present, the "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 models in the digital world, and transforms the interaction between the application and the physical device into the interaction between the application and the digital twin. Digital unified processing.

Based on the HUAWEI CLOUD IoT platform, the 3D visualization application layer built by Tupu Software, through the SMT virtual factory, opens up the bridge between the abstract model and the data presentation, and gives the "device model" expressed in the form of "class/object" /Equipment instance" simulation visualization effect. 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 effects of the digital model.

Digital twin practice based on SMT digital factory

The following is the effect and development process of the SMT digital factory project based on HUAWEI CLOUD IoT digital twin & Tupu visualization.

Before the specific explanation, first introduce some index concepts involved in the construction of SMT factory data modeling and analysis applications.

1. Introduction to OEE concept

That is, Overall Equipment Effectiveness (OEE). Generally speaking, every production equipment has its own theoretical capacity. To realize this theoretical capacity, it must be guaranteed that there is no interference and quality loss. OEE is used to express the ratio of the production capacity of the equipment to the theoretical capacity.

When calculating OEE, three dimensions are involved:

Time utilization

Time utilization = Σ actual running time / Σ planned start-up time * 100%. Used to evaluate the loss caused by the shutdown, including any event that caused the planned production shutdown, such as equipment failure, shortage of raw materials, and changes in production methods;

Performance utilization

Performance utilization = Σ[output quantity cycle time for a product to be processed in the state of the equipment]/Σ actual running time 100%. Used to evaluate the loss in production speed. Including any factors that cause production to fail to run at maximum speed, such as equipment wear, unqualified materials, and operator errors;

Pass rate

Qualification rate=[quantity of qualified output]/[quantity of output]*100%. Used to evaluate the loss of quality, 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] [Qualification Rate]*100%. This is a key indicator to measure the overall operating efficiency of equipment, and it is also a key indicator for many electronic manufacturing plants and other similar plants. A key indicator in the Generally speaking, the value of OEE of domestic manufacturers is not too high, generally only 70%, or 80%, even less than 40%.

2. Factory twin production line and equipment modeling analysis effect diagram

The factory twin production line and equipment modeling analysis can be viewed through some visual management backends. The following are the renderings of three different functions.

Figure 1: There is a total of 1 production line displayed, which can be dragged and dropped appropriately. You can see the OEE value of each device in the graph. Through asset modeling and analysis capabilities, the OEE of production lines and equipment can be calculated in real time, key indicators of each equipment can be monitored in real time, and historical data can be viewed at the same time.

Figure 2: Modeling diagram for the equipment. Through the combination of equipment reporting fault messages and equipment models, real-time monitoring of equipment operating status.

Figure 3: Asset analysis diagram. Through the asset model analysis capabilities, real-time analysis and monitoring of reported device data are possible for abnormalities. For example, the humidity is 45%~63% under normal conditions. If the reported data is not within this range, it is considered abnormal data. The interface will display a yellow dot, indicating that the data reported by the device is abnormal. It can be seen that data analysis can be calculated and monitored in real time, and if there are some serious abnormalities, it can even be pushed to 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, a production line has 7 types of equipment. Let's take the printing press as an example to look at the attributes and presentation methods involved in equipment modeling.

First, it is the configuration of attributes. For printing machines, the three attributes defined are:

Static configuration attributes: product ideal printing time, equipment model

Measurement data attributes: printing speed, demolding speed, printing height

Analyze task attributes: time utilization, performance utilization, pass rate, OEE

The three kinds of attribute data are presented in real time through the equipment information panel of the printing machine "OEE data" and "business data".

The analysis task properties also have the following calculation configurations:

Conversion calculation: calculating time utilization, calculating performance utilization, calculating OEE, and judging temperature status

Aggregate calculation: calculate the actual working time, calculate the actual working time, calculate the pass rate

Stream computing: SMT scenario is not used yet

The above picture is a complete sample after all parameters are equipped. There are about 70 attributes that can be seen in it, all of which simulate some attributes of the real industry.

At the interactive level, HUAWEI CLOUD IoT provides the logical judgment configuration of business functions. Take the "conversion calculation" of the printing press 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, then it is considered to be a normal temperature. Once an alarm occurs, Huawei The cloud IoT platform will automatically push alarm signals and corresponding key data to Tupu's visual application interface. The visual interface will feedback the alarm signal in real time through dynamic effects, and through interactive clicks, the user can further view the detailed information of the alarm.

production line: SMT production line

Production line modeling is actually the same concept as equipment modeling, and the model is similar. The production line is relatively simple, mainly to find the value of OEE, that is, to analyze task attributes, including 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 a printing press and one of the automatically generated 3D production line models:

Next, let's take a look at how production line assets are constructed. As shown in the figure below, the production line assets are divided into three layers:

The first layer is the factory (parent asset)

The second layer is the production line (sub-assets)

The third layer is equipment (sub-assets)

The above 3 pictures:

Figure 1 is a logical structure diagram of the production line and equipment. Production lines and equipment also have models, and the three-tier model constitutes a "parent-child relationship" of assets. Assets come from the model and are instantiated from the model. At the same time, when the model is instantiated as an asset, the hierarchical relationship can be specified according to the business scenario, and the assets are independent of each other.

Figure 2 is the constructed asset tree. Compared with the logic diagram in the previous picture, this is an example diagram. The figure shows that an electronics factory has three SMT production lines, and each production line has 7 SMT equipment.

Figure 3 is the final 3D model of the factory automatically generated electronic factory. Through the mapping of the data model, a total of three SMT production lines are generated, and each production line has 7 SMT devices. Among them, the model, quantity, and panel information of the equipment are automatically generated and real-time data association is carried out.

Asset operation monitoring

After all the product creation and attribute configuration are completed, you can click "Publish" to publish and run the model. When the model is defined, it is a static process, and once it is released, it will be activated. According to the task analysis logic defined in the preamble, the system will automatically calculate and obtain real-time results for reporting. All the data can be observed in the figure below.

As the actual production line is adjusted, the released model may need to be adjusted. On this basis, the visualization interface has been automatically linked with the background configuration interface. The following is a comparison of the AOI instance objects after the production line creation/deleting after the furnace, and the production line data model objects of the after the furnace AOI equipment of the visual production line model according to the background configuration Create/delete is realized automatically.

The released production line data can also be displayed in different graphical display methods such as line graphs, heat graphs, and curve graphs according to the needs of the business, making it easier to understand and analyze the data and use it to assist management decisions:

Above, the SMT digital factory built based on the HUAWEI CLOUD IoT Digital Twin & Tupu Visualization Factory realizes orderly and controllable production by making the production process transparent on the production line. The intelligent, code-free, and configurable one-stop solution can quickly build production lines, lower the development threshold to a certain extent, and shorten the development cycle. The regular application launch time has been reduced from 6-9 months to 3 months or less. At the same time, the twin modeling analysis + data visualization solution realizes the all-element connection of the SMT digital factory, uses data to drive intelligent production, and greatly improves the efficiency of data utilization. Relying on the generalization of the aforementioned digital bases, the same technical solutions can also be applied to more industries and enterprises that are undergoing industrial digital transformation.

& Lenovo, Wuhan SMT intelligent production line

In 2019, Tupu Software helped Wuhan Lenovo build a new 3D visual simulation operation and maintenance system for the SMT placement machine production line. The SMT operation and maintenance system is based on the Tupu visualization technology, which can quickly build various basic information of the production line, digitally monitor in real time, and realize the full life cycle and refined management of the patch production line. Through 3D production line modeling and business linkage, the operating status of each production line can be monitored remotely, realizing "unmanned and automated" operations, helping companies increase production and efficiency. In the maintenance of some equipment and the processing of downtime waiting time, the efficiency is at least 20% higher than before.

During the epidemic, the production uncertainty of the affected people puts forward higher requirements for the automation level, quality and efficiency of manufacturing plants. As Lenovo’s most advanced industrial plant in the world, Lenovo’s Wuhan Industrial Base has been severely affected by the epidemic to resume 10,000-person full-production operations in a short period of time, and coordinated the resumption of work and production at the same frequency in the upstream and downstream of the supply chain, thanks to the vigorous promotion Digital transformation of itself. Including the Wuhan Lenovo Industrial Base, Tupu Software's SMT visualization solution has been implemented in multiple smart factories, and it will also help more companies to solve the challenges faced by smart manufacturing and digital transformation.

SMT production line monitoring and management visualization of

The visualization of Tupu software uses lightweight modeling and powerful visualization engine technology to build a new SMT process monitoring and management visualization system case, creating an intelligent and green digital smart factory. Provide new ideas for transformation for companies that want digital transformation, such as smart workshops, smart assembly plants, engineering machinery and equipment plants, automobile manufacturing, logistics warehouse management and other industries.

SMT data visualization

According to the needs of industry operation and government and enterprise decision-making, the main data of the entire 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 is graphically and scene-based, and the OEE (equipment) of each line is displayed. Comprehensive efficiency), time utilization, performance utilization, output completion, through rate, equipment utilization rate, defective rate, IoT connection rate, etc.

Relying on the graphic components and interface design, the UI part realizes the data dynamic loading effect on the data panel, and compares each chart data more intuitively. The visual effect felt by the user is compared to the static chart data, which can be described as a higher level. !

Device information visualization

Realize the visualization of key equipment business data in the 3D scene through the docking data interface, display the key equipment status on the page, and use different color device values and icons to represent different equipment status. And add the intelligent early warning analysis function. Once the device data exceeds the established threshold and the historical data is analyzed and judged, the device will be marked with red flashing in the three-dimensional scene, and the routine manual inspection will be converted to the intelligent inspection, so as to understand the health of the equipment in time. state.

from Huawei's concept to build a localized autonomous engine

Since its establishment, Tupu Software has always insisted on independent research and development of visualization products, and has built its own domestically-made independent engine. As a partner of Huawei, not only has a close cooperative relationship, but also a coincident corporate philosophy.

Relying on their respective technological accumulation and industry practices to deepen cooperation, further promote the optimization and upgrading of their respective product systems, promote cooperation in key industries such as industry, cities, communications, and transportation, and build perfect scenario-based solutions for customers.

Ren Zhengfei said: "What does Huawei have? We don't even have limited resources, but our employees work hard and create resources desperately. Really as the international song sings, don't say we have nothing, we are the masters of tomorrow." There is no savior, nor is it dependent on the emperor, it is all on ourselves'.

Earlier, in the face of U.S. sanctions, the U.S. Department of Commerce website issued an export ban, requiring foreign companies that use American chip manufacturing equipment to obtain an export license before supplying them. The ban and upgrade of Huawei once again challenged the international supply chain and industry. The bottom line of the chain. Huawei published an article "No scars, no scars, thick skins, and heroes who have suffered since ancient times". The article contained only two sentences: "Looking back, it is rugged and bumpy" and "Look forward and never give up."

As well as the latest news, the United States has a ban on paper that does not allow any company to provide Huawei with 5G chips, nor is it allowed to use machines to produce 5G chips for Huawei. In order to suppress the development of Chinese technology companies, they even made various tricks to detain Meng Wanzhou, the daughter of Ren Zhengfei, and suppress Huawei in disguise. And one after another Chinese high-tech companies have been suppressed and blacked out one after another.

However, as a company with a "wolf-like" culture, Ren Zhengfei chose to become more courageous as he frustrated and build a wholly-owned chip company owned by China, and all the industrial chain and production technologies were developed by Huawei.

The external suppression of the United States is telling us that we must become stronger if we want to become independent, and we must become independent if we want to become stronger. China's development is inseparable from the independent technological innovation of enterprises, and we should be self-reliant. The important theory of "science and technology is the primary productive force" 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.

replacement is the general trend,

During the 36th collective study session of the Politburo of the CPC Central Committee, the General Secretary emphasized, “We must hold fast to the core technology independent innovation, which is the'bull nose', and break through the cutting-edge technologies of network development and key core technologies with international competitiveness, and accelerate the advancement. Domestically produced independent and controllable alternative plans to build a safe and controllable information technology system.” As well as the ZTE incident, Huawei and other incidents, all tell us that if we want to be out of control, we must make every effort to build our own “controllable” technology. .

Tupu Software has long been committed to the construction of system visualization in diversified industries. It has accumulated experience in the technology industry, and through independent innovation and research and development of technical products, it has created a representative visualization control system in many industries. In the future At the forefront of technological progress, Tupu Software will continue to follow the pace of advancement and innovate more industrial Internet visualization system solutions. Comply with the development of Industry 4.0, the construction of new infrastructure such as 5G networks and data centers, continuously improve products, innovate, and meet the opportunities and challenges given by future technology!