• University of Padova

4.0 Shades of Digitalisation for the Chemical and Process Industries

Make the transition to Industry 4.0 as you learn how to streamline chemical and process engineer jobs with digital technologies.

Multiple blue icons of digitalisation over a chemical refinery plant to represent data-based techniques and methods for the chemical and process industries.

4.0 Shades of Digitalisation for the Chemical and Process Industries

  • 4 weeks

  • 5 hours per week

  • Digital certificate when eligible

  • Intermediate level

Find out more about how to join this course

  • Duration

    4 weeks
  • Weekly study

    5 hours
  • 100% online

    How it works
  • Unlimited subscription

    $244.99 for one whole yearLearn more

Discover the benefits of digital technologies with the University of Padova

We are in the midst of the fourth industrial revolution (Industry 4.0). By embracing new digital technologies, industries can increase automation, streamline processes, and save on costs.

On this four-week course from the University of Padova, with the collaboration of several Italian universities, you’ll explore digitalisation in the context of chemical and process industries.

You’ll gain practical skills in implementing key data-driven techniques within an Industry 4.0 paradigm, and obtain knowledge to understand the change of paradigm occurring in the industrial sectors.

Explore machine learning for the process industry

You’ll start by exploring the importance of data digitalisation in the process industry.

Through this exploration, you’ll discover machine learning methods and multivariate statistics analysis that will help you analyse your data with efficiency and accuracy.

Unpack data reconciliation and artificial neural networks

You’ll delve further into data analysis techniques such as regression and classification. This knowledge will help you extract reliable and accurate information about your industry processes.

Taking your skills further, you’ll unpack the uses of artificial neural networks and real-time optimisation to help you exploit data for advanced modelling.

Develop an understanding of model predictive control

Finally, you’ll learn the advanced method of model predictive control. This understanding will help you solve optimisation problems and further streamline your processes.

Throughout the course, you’ll explore case studies to see these methods in action, helping you gain both practical and theoretical knowledge.

By the end, you’ll understand how to choose the most convenient routes to tackle practical problems and improve processes in data management.

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Skip to 0 minutes and 10 seconds Big data, machine learning, real time optimisation, advanced control, neural networks. These are the keywords for a chemical and process industry that is evolving and changing, and where the real process - that includes equipment, hard instrumentation, and machines - is becoming more and more symbiotic with a virtual infrastructure based on digital tools and methods. The aim is to make production systems more competitive, more efficient, and more sustainable. If you want to know more about digitalisation in the process industry, this course is for you. You’ll be introduced to the world of industrial data and techniques currently available to handle those data, interpret them, extract valuable information and patterns, and use them to predict and improved process behavior.

Skip to 1 minute and 6 seconds You’ll learn about artificial neural networks and how they can be employed to represent and model real production units. You will understand the meaning of real time optimisation and how this methodology is becoming a digital workhorse to boost productivity and reduce the environmental footprint of process operations. You’ll learn what model-based automatic control is, how it can improve safety and performance, and the tools and methods necessary to set it up. This course will give you an overview of some of the techniques that are transforming chemical production and will make you more aware and competent about the practical meaning of digitalisation in the process industry.

Syllabus

  • Week 1

    Machine learning and multivariate statistics

    • Introduction: Let’s get started

      Scope, objectives, and importance of the course.

    • Reduction of data dimensions

      Importance of data and related analysis.

    • Putting it all together

      Synthesis of the week and a bit of feedback.

  • Week 2

    Regression, classification, and data reconciliation

    • Regression and PLS

      Regression and Partial Least Squares techniques.

    • Data reconciliation

      The importance of the reconciling of data.

    • Putting it all together

      Synthesis of the week and a bit of feedback.

  • Week 3

    Artificial neural networks and real-time optimization

    • Artificial Networks

      Artificial Networks versus Neurons.

    • Real-time optimization

      Optimizing processes in real-time.

    • Practicing what we know

      Let's have a look to the application of what we've learnt.

    • Putting it all together

      Synthesis of the week and a bit of feedback.

  • Week 4

    Model predictive control

    • Introduction to Process Control

      What is Process Control?

    • System identification

      Managing systems.

    • Model Predictive Control

      Predict model behaviour to better control processes.

    • Putting it all together

      Synthesis of the course and final feedback.

When would you like to start?

Start straight away and join a global classroom of learners. If the course hasn’t started yet you’ll see the future date listed below.

  • Available now

Learning on this course

On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.

What will you achieve?

By the end of the course, you‘ll be able to...

  • Define and identify some of the most important data-driven techniques supporting digitalization in the chemical and process industries
  • Classify the fundamentals of machine learning methods for data classification, regression and clustering
  • Interpret the methodologies for exploiting data for advanced modelling (e.g. Artificial Neural Networks), optimization and control
  • Describe how digital technologies are currently employed in the chemical and process industries, and the benefits they can deliver
  • Apply basic data-driven methods for solving simple practical problems
  • Compare several Industry 4.0 methods in a critical way and choose the most convenient routes to tackle practical problems in data management

Who is the course for?

This course is for students, undergraduates, or professionals in the field of engineering who want to learn more about digitalisation in the process industries.

Who will you learn with?

Dr. Bezzo is Professor of Chemical Engineering at the University of Padova. Research interests focus on process and supply chain modeling and optimization for the chemical and pharmaceutical industry.

Dr. Facco is Associate Professor of Chemical Engineering at the University of Padova. His research interests are related to data analytics, machine/deep learning, and design of experiments.

Dr. Bacci di Capaci is a Research Fellow in Chemical Engineering at the University of Pisa. His research activity is in advanced process control, system modeling, identification, and simulation, MPC.

Dr. Gabriele Pannocchia is a Professor of Chemical Engineering at the University of Pisa. His research interests include advanced process control systems, process simulation, and optimization.

Dr. Tronci is associate professor at the University of Cagliari. Her research interests are in the field of process control, with applications to chemical and biochemical processes.

Who developed the course?

University of Padova

The University of Padova is one of Europe’s oldest and most prestigious seats of learning; it aims to provide its students with both professional training and a solid cultural background.

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Ways to learn

Choose the best way to learn for you!

Subscribe & save

$244.99 for one whole year

Automatically renews

Develop skills to further your career

  • Access to this course
  • Access to 1,000+ courses
  • Learn at your own pace
  • Discuss your learning in comments
  • Tests to boost your learning
  • Digital certificate when you're eligible

Cancel for free anytime

Buy this course

$134/one-off payment

Fulfill your current learning need

  • Access to this course
  • Learn at your own pace
  • Discuss your learning in comments
  • Tests to boost your learning
  • Printed and digital certificate when you’re eligible

Limited access

Free

Sample the course materials

  • Access expires 1 Apr 2024

Find out more about certificates, Unlimited or buying a course (Upgrades)

Sale price available until 5 March 2024 at 23:59 (UTC). T&Cs apply.

Find out more about certificates, Unlimited or buying a course (Upgrades)

Sale price available until 5 March 2024 at 23:59 (UTC). T&Cs apply.

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