How should applied universities carry out intelligent manufacturing training and teaching?

In 2015, my country proposed “Made in China 2025”, setting the ambitious goal of a manufacturing powerhouse. Vigorously promote breakthrough development in key areas, aim at strategic priorities such as next-generation information technology, high-end equipment, new materials, biomedicine, etc., guide the gathering of various resources in society, and promote the rapid improvement of advantages and strategic industries. Focus on the development of a new generation of information technology, high-end cnc machine tools and robots, aerospace equipment, marine engineering equipment and high-tech ships, advanced rail transit equipment, energy-saving and new energy vehicles, power equipment, new materials, biomedicine and high-performance medical equipment, Ten areas of agricultural machinery and equipment.
In recent years, nearly a thousand colleges and universities across the country have successively opened industrial robots and intelligent manufacturing and other related majors in order to cultivate advanced manufacturing talents. But even with relatively rapid development in recent years, compared with the increasing demand for talents year by year, the cultivation of intelligent manufacturing professionals is still relatively lagging. As an emerging professional discipline, the process from curriculum content setting to talent training is still immature, and the school is therefore faced with a series of problems.

1. The setting of professional courses is unreasonable

Before setting up the major of intelligent manufacturing, most universities lacked in-depth investigation and research on the demand for regional talents, blindly imitating, and blindly imitating the professional design of other colleges and universities, resulting in the training of talents that do not meet the job requirements.

2. Serious shortage of teaching resources

The price of intelligent manufacturing equipment ranges from hundreds of thousands to several million, so that many schools do not have enough funds to purchase intelligent manufacturing equipment in the training room, which seriously affects the development of teaching work.

3. The construction of teachers needs to be strengthened urgently

Due to the late start of the intelligent manufacturing specialty, universities lack professional leaders, teachers’ professional quality is not too hard, lack of professional theoretical system knowledge, lack of industry experience, and cannot meet the requirements of practical teaching.

4.the combination of work and learning is a formality

Under the test-oriented education system, traditional teaching is still mainly based on teacher explanations. Students are in a passive learning state and their skills cannot be exercised. In addition, in terms of school training, due to the limitations of funds and venues, the number of equipment purchases cannot satisfy a large number of students. The demand for practical training has caused students to lack practical training in the learning process.

5.the construction of the training system is not perfect

Failure to closely integrate the training objectives of professional talents in the systematic design of the training curriculum system, and the matching tutorials, instruction books, and related resources are not complete: the lack of evaluation standards, tools, and methods for student training has led to The emergence of “equipment, poor use, practical training, no system” has greatly reduced the effectiveness of student training.

The National College Automation Professional Teaching Forum held in Nanchang in the middle of this month is precisely implementing the spirit of the National Education Conference and the “Implementation Plan for Accelerating Education Modernization (2018-2022)”, and implementing the National College Undergraduate Education Work Conference in the New Era Under the guidance of the “Ministry of Education’s Opinions on Accelerating the Construction of High-Level Undergraduate Education and Comprehensively Improving the Ability of Talent Training”, in order to solve the above teaching problems, the professional curriculum construction and talent training experience exchange forum dedicated to the national university automation professional organization, promote excellent teaching The results promote the connotative development of undergraduate education in automation majors, and the following solutions are proposed.

01 Solve the problem of learning-the basic teaching system of intelligent manufacturing

It is well known that the concept of intelligent manufacturing is too large. It is difficult to cover all the knowledge points and teach the learned in a short period of professional teaching in a few years. The solution of Huiyang Technology is to choose a typical practical case. Design backbone, all knowledge selection and content design are carried out around actual cases. The advantage of this is that the content selection is compatible with the current situation of the industry, and the main knowledge points are consistent with the production content. This solves the problem that the teaching content is out of reality and the curriculum setting is unreasonable. problem.

The learning method is also very different from traditional books. The learner is placed in the virtual factory environment to learn from the perspective of a visitor. The system is responsible for helping and guiding the learner. This solution focuses on what you see and I feel that Huiyang Technology calls this model the “museum learning model”, which is characterized by a complete and clear learning route, wide coverage of knowledge content, and rich media types. It is positioned to popularize knowledge and is especially suitable for teaching by novice and old teachers. It is a good supplement to the construction of intelligent manufacturing faculty.

02 Solve practical problems-intelligent manufacturing virtual training system

In my country’s higher education, there has always been such a problem, “graduation = unemployment”. How to obtain high-quality training opportunities before leaving school has always been a topic that the education industry is striving to improve. We virtualize the actual production environment, management methods, and processing technology into the software through examples, allowing learners to play different roles in the production work, and complete the challenges of each task through collaboration, and each interactive process It’s up to the learners to make their own choices, which can develop a wide range of stories. It is characterized by the ability to record changes in every detail and show these effects on the final result, and learners can experience it in the process The process of changing the identities of different positions is similar to the management of production, so it is called the “operator learning model”.

03 Solve the problem of innovative design-intelligent manufacturing simulation system

Design is at the top of the production chain, which determines the efficiency of the entire production system. Due to the high cost of smart equipment, it is difficult for colleges and universities to provide sufficient conditions to carry out production line design experiments, resulting in the status quo that the quality of experiments in colleges is generally low. Huiyang Technology uses virtual technology to connect part of the hardware, such as PLC as the control part, to the software, design, build and teach industrial robots in the software, write the PLC program in the external hardware, and use the hardware to drive the equipment in the software. Complete the verification of the design. It is characterized by freedom and efficiency. It uses virtual twin technology to solve practical problems. The highly simulated operations and scenarios allow colleges and universities to completely get rid of their dependence on expensive equipment.

The above three systems constitute a complete closed loop of the intelligent manufacturing teaching experiment. It solves the five major problems mentioned above. The difficulty gradually increases from easy to difficult. It has both comprehensive basic knowledge coverage and key issues. In-depth and focused. We have also cooperated with many colleges and universities to actively prepare and explore. The goal is to continuously enrich the content and functions of this system and work hard to solve the practical difficulties in the teaching of intelligent manufacturing.