IIoT Workshops in Lyon (France)

Start your IIoT project with the help of our workshop series and learn how to implement your project efficiently and purposefully!

In today's rapidly evolving industrial landscape, the merging of IT and OT is increasingly changing production processes and the demands placed on companies and their employees. Topics such as industrial IoT, data analysis, big data and the use and management of edge gateways are becoming increasingly important for you as a plant operator, machine manufacturer and developer. The aim is to minimize downtime and increase efficiency.

The workshops offered here are designed to make it easier for you to get started with your IIoT project and familiarize you with the basic technologies in Industrial IoT.

The workshop is primarily aimed at consultants, project managers, IIoT system integrators, automation engineers and IT specialists who want to discover and put into practice the main technologies commonly used in industrial IIoT projects.

Date: Tuesday, 04. Jun. 2024 from 09:00 to 17:00

Location: NH LYON AIRPORT – 915, rue d’Espagne – 69125 Lyon Saint-Exupéry

Find your way via Google Maps

Lecturer: Jan Luginbühl (Technical Product Consulting Hilscher Switzerland, Solothurn)

Price: 150,00 EUR plus VAT

Language: English

Participants: max. 14 participants

Banner of the IIoT Workshop OT meets IT on colorful background in French.

Target groups:

  • Automation engineers
  • Software developers
  • Computer scientists
  • Product managers

Objective:

  • Operating, linking and managing IoT apps securely in an industrial environment
  • Creating and commissioning Docker applications
  • Simple connection to the cloud

Prerequisites: General technical knowledge, laptop with internet access and browser

Methodology

  • Theory with practical exercises on your own laptop
  • Teams of two each work on their own real training system
  • Working with an IIoT edge gateway and sensorEDGE with Docker environment and device management
Contents
Part 1

OT-to-IT access method

  • Automation network to cloud
    • Active via edge device " Passive via TAP
    • PLC to cloud (acyclic)
    • Sensor to cloud
  • From sensor to the cloud with sensorEDGE

Security in OT

  • Hardened operating system
  • Secure boot
  • OT/IT network segmentation
  • Secure cloud connection

IIoT protocols

  • OPC UA
  • MQTT
Part 2

Develop, commission and manage IIoT applications

  • Introduction to software virtualization with Docker
  • Developing secure IIoT applications using Docker
  • Linking IIoT applications
Part 3

Hands on

  • Acquire sensor data using PROFINET and IO-Link
  • Publish sensor data to MQTT broker
  • Setting up a Docker container for further processing of the data
  • Upload sensor data to the cloud and retrieve data from the cloud

Date: Wednesday, 05. Jun. 2024 from 09:00 to 17:00

Location: NH LYON AIRPORT, 915, rue d’Espagne, 69125 Lyon Saint-Exupéry

Find your way via Google Maps

Lecturers: Jan Luginbühl (Technical Product Consulting Hilscher Switzerland, Solothurn), Dr. Stefan Pauli (Senior Data Scientist Swiss Smart Factory, Biel)

Price: 520,00 EUR plus VAT

Language: English

Participants: max. 14 participants

Banner of the IIoT Analytics, Big Data, Machine Learning on colorful background in English.

Target groups:

  • Developers
  • Product managers

Objective:

  • Basic understanding of the operation of data analyses
  • Simplest data analyses using the Dataiku framework

Prerequisites: General technical knowledge, laptop with internet access and browser

Methodology:

  • Theory with practical exercises on your own laptop
  • Teams of two each work on their own real-life training system
  • Working with an IIoT edge gateway as a data aggregator and the Data Science Studio from Dataiku
Content
  • Exercise to create data connections SQL server with machine data
  • Visualizing the data in Dataiku
  • Creating predictions using machine learning
  • Discussion of use cases in industry and applications in your day-to-day work
Procedure
  • In the practical part, participants can put what they have learned into practice
  • In the theoretical part, various machine learning algorithms are explained in an understandable way

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