Suzhou SILU Production Engineering Services Co., Ltd.

Inter-university Cooperation Courses

We successfully collaborate in inter-university cooperation projects with multiple renowned universities in China, such as Tongji University, XJTLU, Nanjing University, Xi'an Jiaotong University, Soochow University, National University of Singapore Suzhou Research Institute. The audience mainly consists of undergraduate and master's students in the field of German Industry 4.0 and intelligent manufacturing related courses. As an extracurricular supplement to the school's theoretical knowledge, the inter-university cooperation course helps college students broaden their horizons, let students understand the most cutting-edge production technology and intelligent manufacturing. Students find help in determining their career goals and plans in advance. Inter-university cooperation projects generally follow a summer school model.

Highlights of past inter-university cooperation:

Overview of inter-university cooperation courses：Smart Manufacturing and Industry 4.0

Objectives and Content

The concept of Industry 4.0 is based on the integration of information and communication technology in Cyber-Physical Systems. The Production/Value Chain is analyzed with Big Data and in real-time to achieve a shifting of the industry towards intelligence. In the Industry 4.0 Demonstration and Innovation Center, the most frontier technology of Industry 4.0 is demonstrated to show the ultimate benefits of the concept.

Why do you need to use smart manufacturing
Industry 4.0 demonstration
a)Development of Industry 4.0
b)Industry 4.0 Use cases
c)Technology scope
Benefits of Industry 4.0
a)Personalized, localized and batch customized
b)Interconnected production and cluster dynamics enable higher capacities
Visit & experiences of Sino-German Industry 4.0 Demonstration and Innovation Center
Visit & experiences of Sino-German Artificial Intelligence Innovation Factory

Outline

Scalable Automation by Human-Robot Collaboration

Objectives and Content

The increasing demand for customization, shortened product lift-cycles and increasing labor cost raise new challenges for production systems. Flexible systems are needed, that can adapt to these changing requirements and achieve similar cost efficiency as traditional lean production systems. Scalable Automation allows a quick adaption of the automation level of an assembly system. Enablers for scalable automation are introduced in this course. Special attention is paid to proper task allocation between human operators and Collaborative Robots (Cobots).

Motivation of changeability and scalable automation
Challenges and change drivers enabled by Industry 4.0
Assessment of automation levels
Overview of assessment tool and functionalities
Case study: Changeability analysis
Introduction of human-robot collaboration
a) Industrial robots and Cobots
b) Show case of Cobots
c) Case study: Scenario development

Outline

Data Analytics and Machine Learning

Objectives and Content

The ubiquitous use of sensors and connected devices leads to a tremendous increase in collected data. Data analytics in production is the use of big data analytics and machine learning methods to ensure quality, to increase performance, and to reduce cost. This training combines theoretical knowledge and hands-on practices to show the potential of data analytics in production.

Introduction of Data Analytics & Machine Learning
a) General Introduction
b) Standard CRISP-DM process model
c) Examples for analysis & implementation
Machine Learning Algorithms
a) Supervised learning (e.g. Artificial Neural Networks)
b) Unsupervised learning (e.g. Support Vector Machines)
c) Reinforcement learning (e.g. Q-Learning)
Data analysis platform & tools
Introduction of Industry implementation examples
Guided practice on chosen use cases

Outline

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