Completed Enterprise Field Projects
 

This paper sorts out the enterprise projects completed by the team and the main trainer.

The main trainer Dr. Li's biggest technical advantage is that he has completed a large number of projects on the enterprise site for 30 years! The main trainer has completed more than 100 on-site Smart Manufacturing projects in Germany, the United States, China and South Korea; As the head of American Metal Pass, the main trainer also led / guided the team to complete a large number of projects.

Generally, the on-site technicians have low educational background, so their understanding is weak, and their complex on-site problems are mostly limited to experience; However, the main trainer has double doctorates in German engineering and American software, has practical work experience in nearly 10 business fields, and has a thorough understanding of on-site problems. John Newman, an American expert, once claimed that there were a large number of problems that could not be explained by theory and could only be explained by experience at each site, but the expert was completely convinced after being explained by the team leader!
 

1.  The Main Trainer Dr. Li Has Completed More Than 100 Projects

 Table 1: Items completed by the main trainer

2.  More Than 100 Projects Completed by American Metal Pass Team

Most of the projects are completed under the leadership / guidance of the head of the team as the leader of Metal Pass. For example, an expert discussed with Dr. Li by telephone every night during an Indian project. The list of items is as follows. Each item is described in detail on this website.

Table 2: projects completed by American Metal Pass (including projects guided or participated by the main trainer)

3.  Introduction to Smart Manufacturing Training Benchmarking Project

The thermal and mechanical finite element artificial intelligence model completed by the main trainer in Germany in the early years created a precedent for the application of this model technology in the final shape prediction and production process optimization of large and complex sections at the factory level. In the model development of Morgan construction company (now Siemens), three groups of more than 100 models have been completed, including material deformation model series, material force energy and power demand model series, and material microstructure and mechanical property prediction model series. After that, he took the model to the front line of the plant to develop intelligent system, and led the development of three Level 2s (Intelligent System) for metal smelting electric furnace, refining furnace and continuous casting for kescat company. See Table 3.

Table 3: benchmarking items

After that, based on the technical foundation and solid model background of German engineering and American software doctors, the main trainer served as a technical consultant for intelligent system development in various countries all over the world, and successively completed large-scale international benchmarking projects such as EOS of the United States, POSCO of Korea, NISCO and BYD of China, as well as Tesla of the United States.

Oregon company's traditional high-end material project: in the production process of hard and thin products, there were defective products every day. During the return visit half a year after completion, I was told that there had been no similar defective products in the past half a year.

Burr length is predicted and measured by model (there are more than ten influencing factors, including tool quality and use, process parameters and incoming material quality, etc.)

BYD lithium battery Smart Manufacturing related projects: burr defect is the main factor causing lithium battery fire (Samsung mobile phone lithium battery explosion, BYD lithium battery incident). At the beginning of the cooperation, the factory used the pole piece slitting burr prediction model which is very difficult to model to strictly investigate the model level of the team. It is required that the hit rate of the model is 85%, and the team has reached 98%; At present, the second phase of the project (burr early warning) and the third phase of the project (knife notch measurement) have been completed. In view of the weak data acquisition ability in some countries' manufacturing industry, the soft sensing technology with high difficulty in the industry has been successfully applied. Soft sensing is to predict the parameters to be measured by using high-precision model when it is difficult to measure directly; This defect early warning system is based on BYD MES and quality inspection data. At present, there is only one company that combines the process of this project with that of Metal Pass automation system in the market. Figure 1 shows the predicted burr length based on the operating parameters of lithium battery electrode. Compared with the measured burr length, the hit rate is more than 98%!

Electronic manufacturing related projects: more than ten enterprises such as Skyworth, TCL and Guangye. In addition, there are still a large number of online information for the projects.

Training

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  Trainer, Experience, Study method, project, Case-based

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