Industries 4.0 in 12 Lessons
Practice course how to transform an organization into an Industries 4.0 business
A practice course that demonstrates with use cases and own experiments how to implement Industries 4.0 for your business. You will see how a steady evolutionary transformation and retro-fitting of an organization can be done in the spirit of industries 4.0 in a shared platform economy without breaking your existing structures.
12 lessons @ 3 days (8 * 45min)
This course is for you if you want inspirations and tips:
- How to plan or implement transformation to Industries 4.0
- Disruptive business models with Industries 4.0
- Benefits and Risks of Industries 4.0
- Use of Industries 4.0 in various industry sectors
- Disruption caused by Industries 4.0 for agriculture and health care
- Details on technology required to implement Industries 4.0
- Build some sample implementation for Industries 4.0 retro-fit
- How to work with Big Data and machine assisted analytics
- How machines can easily interact with humans
- Security, safety, privacy
- How block-chain and alternatives can enhance your security
- On the basics of Artificial Intelligence
The course targets any kind of engineers and decision or policy makers who are concerned with assisting and/or driving the change in the light of Digital Transformation including engineers or post-graduates of computer sciences and engineering and any decision maker.
Knowledge in engineering or computer sciences concerned with decision making and business strategy building or policy making for their organization are pre-requisite.
Participants will receive the Blue Elefant Certificate of Excellence. Duration 12 weeks: 12 units of 3 days (8 x 45minutes)
Introduction and Defining the Scope
Introduction to Industries 4.0 as bridge between internet and physical world.
Use cases for industries 4.0
Uses of Industries 4.0 for Manufacturing 4.0, Agriculture 4.0, Health Care 4.0, Logistics 4.0 etc.
IoT: Connecting everything to the internet
Data Acquisition from physical Sources, public and private clouds and coping with data deluge
ESB: Controlling data flows
Strategies to make data transfer reliable, handle contention, guaranty sequencing and aging
Data Lakes, data cleansing and verification, pooling, public domain data sources, archiving
Data Analytics makes use of fast algorithmic and the availability of big data to get new insights.
Industries 4.0 is the seamless cooperation between human workers and their machines.
Security, Safety, Reliability
Internet Infrastructure, Security, Safety and how to guarantee the availability of authentic data
Workflows, EDI, Woven production, Autonomous vehicles, Human machine interaction
Machine (Automated) Learning, Learning Machines, Machine games, Darwin Machines
Putting it all together
Putting a practical demo solution together to demonstrate the needs for Industries 4.0
Leadership for Industries 4.0
Concepts and methodology to orchestrate industries 4.0 related businesses and projects