|
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!
|
number |
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 and 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.
|
Number |
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 China and
Germany |
|
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 |
Made-in-China
2025 |
|
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).
|
Number |
PPT
Courseware name |
|
13 |
Metal Pass
defect warning system based on installation of MES |
|
14 |
Level 2
system model and software |
|
15 |
Metal Pass
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 Pass
online information resources--1 |
|
50 |
Metal Pass
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 intelligent manufacturing
training PPT courseware, and recent popular training fields,
such as manufacturing Metaverse.
|
Number |
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.
|
number |
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 Pass
network more than 100 app architecture development（1） |
|
145 |
Metal Pass
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 consult of Zhengwei
international 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 intelligent
manufacturing case courseware
Training
General,
Paper,
Courses,
Course overview,
Resources,
Trainer,
Experience,
Study method,
project,
Case-based
=========
Contact us: Please scan the figure below to add
Wechat (e.g. myQQfriend); Tel: 13400064848 or 13430699003; E-mail
BLi68@QQ.com. See
Profile
of the key consultant.
|
