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2021 Annual Training / Smart Manufacturing Courses
for Colleges and Technical Schools

More Than 100 Cases of On-site Smart Manufacturing Projects PPT Courseware List
 

I.  Courseware Description


This batch of courseware is mainly used for classroom teaching of Smart Manufacturing Specialty in Colleges and technical schools. The courseware is displayed in the order of technical basic courses, professional basic courses and professional courses. Smart Manufacturing first needs to design and develop intelligent system, and its main technology lies in:

  • Engineering modeling, familiar with various engineering fields and establish engineering models for the problems to be solved;

  • Machine learning is to predict the future with historical data, and fully bind the model with the production line through machine learning, that is, to realize the high accuracy of the model;

  • Intelligent system architecture development to achieve comprehensive optimization; The scene use cases are arranged in a complete way, integrated into the intelligent system, invoked the engineering model, and all kinds of scenario use cases are processed in detail by programming, providing solutions for each scenario use case.

The industrial 4.0 Smart Manufacturing system integrated with basic automation system, MES, ERP and other systems can realize the optimal machine generation: operators run the system (to operate production), engineers optimize the system behind the scenes (models, scenarios, use cases, etc.), and managers inspect the system (whether there are problems in the production line? How about the quality and output?).
 

Each set of PPT in the following tables contains about 40 slides, which can be used for 1.5-2.0 hours. Each set of PPT documents is divided into five chapters to facilitate orderly teaching.

  

II.  Basic Course of Technology

Machinery, process, material, automation, data acquisition, information technology, etc

There are only a few basic technical courses listed here, which are necessary courses for understanding Smart Manufacturing, no matter what major this Smart Manufacturing major is transformed from. All schools should increase basic technical courses according to their own priorities and advantages. For example, students should have ten fields of basic knowledge, such as material, process, intelligent data acquisition, and so on. In order to achieve high-quality Smart Manufacturing, the main designer should have practical work experience in relevant fields, which means a long growth cycle, at least ten to twenty years! If there are weaknesses in any of the above fields, the designed intelligent system may have problems in the weaknesses, and such problems are very difficult to find because they are the synthesis of multiple fields!
 

num

PPT Courseware name

1

Example of information system construction - Dam

3

Mechanical hardware, electrical hardware and model of zero level system

6

Technical status, application and development of artificial intelligence

7

Basic automation system - sensor

8

Application principle of laser and microwave sensors

9

PLC Programmable controller

10

Basic automation system and its information optimization

28

Characteristics, development and application of big data technology

29

Introduction of cloud computing technology based on AWS

30

Introduction of cloud computing based on Microsoft azure a Google Technology

96

Transnational multidisciplinary learning methods

 

III.  Professional Basic Courses

Industry 4.0/self energy, MES, ERP, robot, etc

Intelligent systems must be integrated with various data systems and automation systems. Data systems include MES and ERP. Although they have certain intelligence, such as MES can formulate production plans and automatically label products, their intelligence is difficult to exceed industrial 3.5. The limbs of the robot are similar to mechanical parts, but the brain of the robot may reach industry 4.0! This paper focuses on Smart Manufacturing, which requires the integration of intelligent system and robot, so robot is included in the professional basic course.
 

Num

PPT Courseware name

2

Background and key fields of Smart Manufacturing

4

Description of Smart Manufacturing by Engineering Institute

5

Background, history and technical achievements of artificial intelligence

11

MES(1): Background, function and technology

12

MES(2): Application, implementation and integration

25

Functions of industrial Internet platform

26

Development of industrial Internet platform

27

Industrial Internet platform application

31

Robot structure, technology and function, etc

32

Overview of domestic digital manufacturing technology

33

Digital / intelligent case analysis of domestic companies

34

Introduction to Smart Manufacturing technology

35

Focus accumulation of digital intelligence abroad

36

Comparative analysis of Smart Manufacturing between weak and strong countries

37

Examples of Smart Manufacturing Technology--1

38

Examples of Smart Manufacturing Technology--2

39

Examples of Smart Manufacturing Technology--3

41

Multilevel system data list

42

Industry4.0

43

Intelligent system technology and Application--1

44

Intelligent system technology and Application--2

79

Benefits and optimization of automobile digital manufacturing

80

Production operation of automobile digital manufacturing

90

Hot strip setting - slab and finish rolling

91

Hot strip setting - rolling schedule

92

Industry 4.0 details

93

Countries' efforts

94

Automobile manufacturing process

  

IV.  Professional Courses

Smart Manufacturing in various industries, including engineering modeling, machine learning and intelligent system architecture development

Each project listed in the following table starts with engineering modeling and solves engineering problems through intelligent systems. For example, the defect early warning system first models the influencing factors of defects, and can predict whether the product will be genuine or defective in the future before the production is completed; If it is a defective product, it will give an alarm in varying degrees to prompt the on-site personnel to change the parameter combination or even change the worn parts, so as to turn the production parts that would otherwise be defective products into genuine products! In this process, the defect early warning system provides the recommended value of the best parameters. While many of the cases used in this batch are in cases in Germany, United States, and South Korea, the team has also done a certain number of Smart Manufacturing projects in China (including engineering modeling, machine learning and intelligent system architecture development), which are also included in the project cases.

A basic rule, do not assume that the operator is an Smart Manufacturing expert! When operators face data board (typical industrial 3.0 data system rather than intelligent system), they may not be able to see the problem, and it is more difficult to find a solution! I hope MES and ERP can be integrated with intelligent systems to solve this problem!

It is impossible for students to learn Smart Manufacturing without cases. This batch of case-based Smart Manufacturing solutions is very valuable! If a school wants to set up an Smart Manufacturing major, it is not enough to download some articles from Search Engine that show the importance of Smart Manufacturing; There are no cases, and even the lecturers themselves do not know how to engage in Smart Manufacturing (how to establish engineering models, how to carry out machine learning, how to collect complete scene use cases to build intelligent systems, etc.), they can not teach students / students to engage in Smart Manufacturing! Or it is not enough to just tell the students what to do but not how to do it (as is the case in most Smart Manufacturing articles in certain countries).

  

Num

PPT Courseware name

13

Metal Data QA system on defect warning, based on installation of MES

14

Level 2 system model and software

15

Metal Data Level 2 model and software

16

Engineering modeling in Level 2 rolling

17

Level 2 system engineering modeling

18

Shape control model

19

Force and energy demand model for lithium battery manufacturing

20

Rolling model of lithium battery electrode

21

Manufacturing defect model of lithium battery electrode

22

Material processing metallography, deformation range and product shape

23

Modeling of field problems

24

Current situation, application, function and case of machine learning

40

New generation Level 2

45

Information physics system

46

Germany DFG Project

47

Morgan manufacturing intelligent system

48

Cascade Steel Rolling Mills three sets of Level 2 system

49

Metal Data online information resources--1

50

Metal Data online information resources--2

51

Oregon company: development and application of new generation Level 2--1

52

Oregon company: development and application of new generation Level 2--2

53

Development of Level 2 engineering model

54

Level 2 architecture - model software--1

55

Level 2 architecture - model software--2

56

Level 2 architecture - model software--3

58

Guided Two-Parameter Learning

59

NISCO Guided Two-Parameter Learning Model Design

60

POSCO project

61

Tiannuo project

62

Lithium battery material

63

BYD phase I model

64

BYD online model and soft sensing

65

BYD model software development technology

66

BYD model software development process

67

BYD software interface phase I and phase II Plan

68

BYD software interface phase II Implementation

69

BYD Geometry and force analysis in knife notch

70

BYD tool detection device

71

BYD tool management

72

Development of Geesun winding optimization system

73

SKYWORTH Smart Manufacturing and TCL's SMT project

74

Development of intelligent retail decision optimization system

75

Smart Manufacturing in garment industry

76

Electronic manufacturing project development

77

Development of Smart Manufacturing system for 5g materials / high-end materials

78

Smart Manufacturing Development of AMER Group 5G new material

81

Bougward: production guidance and appraisal of electric vehicles

82

Business data modeling / intelligent modeling platform

83

Diagnosis and optimization of lithium battery production based on MES data

84

On line inspection system of defective products based on machine vision

85

Foxconn project introduction

86

Technical introduction of practical training of Smart Manufacturing

87

Technology and resources of AMER Group 5G material production

88

Hot continuous rolling

89

Analysis of microstructure and properties of steel

95

Desulfurization of iron and steel by sintering

97

Application of artificial intelligence in Smart Manufacturing

98

Model self-study + Smart Manufacturing case

99

Smart Manufacturing case + practical training

 

Adding alloy to the material can greatly improve the product performance, such as improving the material strength or corrosion resistance (stainless steel, etc.), but the alloy is very expensive! In recent years, the addition of trace alloy only increases the cost a little, but the material properties can be significantly improved by controlling the temperature and deformation! Therefore, I have developed a new generation of intelligent system, a new generation of Level 2, joined the microstructure model developed by me, and combined intelligent self-study and continuous upgrading, which can well solve the above problems. I also designed a two variable self-study under the guidance, which can use a very clever method to combine a large number of models into the Level 2 system in the processing of microalloyed materials, so as to greatly optimize the production. For example, in the project of Oregon company, more than 6000 sets of model data are combined; In the NISCO project, 20000 sets of model data are combined! The design of these data is carried out by myself through software, and the cost is not very high!

Some documents biased towards process / equipment / materials are omitted from the above table. These seemingly engineering documents are very valuable for engineering modeling, but they are not included in this article in order to enable students / students to focus on Smart Manufacturing. 

 

V.  Professional Topics

This part selects a series of key training contents from more than 30 completed series of training, such as offline Smart Manufacturing training PPT courseware, and recent popular training fields, such as manufacturing Metaverse.
 

Num

PPT Courseware name

111

Shenzhen Small-Medium Enterprise Bureau Training 1 (offline 1 day)

112

Shenzhen Small-Medium Enterprise Bureau Training 2 (offline 1 day)

113

10 lectures on basic training of Metal  Pass Smart Manufacturing (online)

114

Application of AI in Smart Manufacturing (Suzhou Guojiang offline 2 days)

115

Ten series of Lecture on "Encyclopedia of Smart Manufacturing" (Suzhou Guojiang online)

116

Transformation and development of traditional household appliances in the Internet Era (offline 2 days)

117

Management innovation of the value chain in commercial enterprises under the value co-creation theory (offline 2 days)

118

Comparison & application of Smart Manufacturing between China and Germany (offline, 0.5 day)

119

Metaverse lecture series 1: Manufacturing Metaverse infrastructure (online)

120

Metaverse lecture series 2: Manufacturing Metaverse basic characteristics (online)

121

Metaverse lecture series 3: Manufacturing Metaverse industrialization technology (online)

122

Metaverse lecture series 4: Manufacturing Metaverse case analysis (online)

 

VI.  Technical Documents for In-depth Study (Word Version)

The process of solving problems on site can be repeated

There are some more in-depth materials that can go through the previous Smart Manufacturing projects with students / students, so that students / students can have a deeper understanding of Smart Manufacturing. The information listed in the table below can achieve this goal.

num

Project report (Book) name

101

German Research Association model project - Engineering Modeling

102

Model project of German Scientific Research Association - achievements and verification

103

More than 100 sets of Morgan / Siemens engineering models - technical basis and deformation(1)

134

More than 100 sets of Morgan / Siemens engineering models - force and energy microstructure and properties(2)

135

Morgan / Siemens explosion process model development (Book)

136

Cascase Intelligent system project - functional design(1)

137

Cascase Intelligent system project - Software Development(2)

138

Cascase Intelligent system project - model and calculation(3)

139

Cascase Intelligent system project - interface, database, etc(4)

140

Engineering modeling and machine learning of Level 2 system

141

Scenario use case and software architecture development of Level 2

142

Microstructure model, intelligent self-study and continuous upgrading of the new generation of Level 2 system

143

Application of a new generation of Level 2 Guided Two-Parameter Learning under the guidance

144

Metal Data network more than 100 app architecture development(1)

145

Metal Data network more than 100 app architecture development(2)

 

VII.  Project Cost


If the production of each slide (usually through 8 steps) takes 10 minutes, each set of slides has more than 40 pages, and 100 sets of slides take more than 40000 minutes, plus the sorting of other documents, it will take more than four months in total! It's just the cost of time. The technology on which these slides are based comes from more than 200 Smart Manufacturing projects I have completed and guided the team to complete in the past 30 years! In addition, when I visited Europe as a consultant of AMER Group in 2019, I downloaded more than 200 Smart Manufacturing books from the University of Aachen, Germany! In the past few years, the information I collected from libraries around the world should be one or twenty times that of these 200 books (more than one million pages, see relevant articles)!

 

See: Technical field of more than 100 sets of PPT Smart Manufacturing case courseware

 

Training

  General, Paper, Courses, Course overview, Resources,
 
Trainer, Experience, Study method, project, Case-based

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