Chemistry Digitalization for Industry 4.0
A.Y. 2025/2026
Learning objectives
The course aims to train students in the use of the main methods of digitalization of the basic concepts of Chemical Sciences and Technologies covered in the other teaching modules of the Course of Studies. The notions and transversal skills useful for selecting and using in the most appropriate and convenient way the different types of software and technological tools available on the market, applying them to the industrial chemical sector, will therefore be transmitted.
Expected learning outcomes
At the end of the course, the student is expected to be able to: 1) Describe the characteristics and functions of the main digitalization techniques in the chemical field; 2) Use data processing software to obtain graphical representations and to carry out numerical regression procedures; 3) Describe the correlations between properties and molecular structure as learned during the use of the molecular digital twin; 4) Describe the basic notions of machine learning and artificial intelligence; 5) Assemble and program electronic boards for specific objectives (value control, alarm, recording); 6) Analyze bibliometric data with graphic and conceptual maps; 7) Use Process Simulation software for the design and optimization of chemical unit operations.
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Second semester
Course syllabus
The teaching program includes the presentation and discussion of the following topics:
· Types of software and their characteristics for data processing and statistical analysis (as Design of Experiments) in the scientific sector, for the construction of diagrams, for programming in order to solve complex problems or manage control instruments: basic theory and exercises (both individually and in group settings).
· Introduction to the Science of simulation of unit operations and process plants. Characteristics, advantages, limitations, types of commercial software: basic theory and examples.
· Use of simulation science for creation of digital twins of i) plants or parts of plants (basic theory), and ii) molecular structures/reaction mechanisms. Practical examples will be provided.
· Exercises with digital twin software in a virtual room for learning new notions complementary to the basic theory already acquired: visit to the plant, work procedures, maintenance procedures, in-depth analysis on real field (individual and group work).
· Artificial intelligence and machine learning at the service of industrial chemistry: basic theory, specific applications, analysis of available software and their use, advantages and limitations. This unit will also go over the basic theory about supervised vs. unsupervised learning, predictive modelling, regression analysis, chemometrics together with the discussion of specific case studies and exercises on selected software (both individually and in group settings).
· Advanced analysis of digital resources for scientific and patent literature. Use of VOSviewer software for the creation of graphic maps and for data processing (both individually and in group settings).
· Case studies illustrating the application of digitalization in the industrial chemistry sector and showcasing the integrated and complementary use of various approaches will be discussed (both individually and in group settings).
· Types of software and their characteristics for data processing and statistical analysis (as Design of Experiments) in the scientific sector, for the construction of diagrams, for programming in order to solve complex problems or manage control instruments: basic theory and exercises (both individually and in group settings).
· Introduction to the Science of simulation of unit operations and process plants. Characteristics, advantages, limitations, types of commercial software: basic theory and examples.
· Use of simulation science for creation of digital twins of i) plants or parts of plants (basic theory), and ii) molecular structures/reaction mechanisms. Practical examples will be provided.
· Exercises with digital twin software in a virtual room for learning new notions complementary to the basic theory already acquired: visit to the plant, work procedures, maintenance procedures, in-depth analysis on real field (individual and group work).
· Artificial intelligence and machine learning at the service of industrial chemistry: basic theory, specific applications, analysis of available software and their use, advantages and limitations. This unit will also go over the basic theory about supervised vs. unsupervised learning, predictive modelling, regression analysis, chemometrics together with the discussion of specific case studies and exercises on selected software (both individually and in group settings).
· Advanced analysis of digital resources for scientific and patent literature. Use of VOSviewer software for the creation of graphic maps and for data processing (both individually and in group settings).
· Case studies illustrating the application of digitalization in the industrial chemistry sector and showcasing the integrated and complementary use of various approaches will be discussed (both individually and in group settings).
Prerequisites for admission
The basic prerequisites are a good knowledge of stoichiometry, physical chemistry and a basic knowledge of mass and energy balances, transport phenomena, chemical reactors, distillation and absorption columns, fluid phase equilibria. Students coming from different Bachelor's degrees from Industrial Chemistry can contact the teacher for on-demand learning of prerequisites. The most important concepts for unit operations and processes will be provided during the course, so no entry level knowledge of chemical plants is required.
Teaching methods
The lectures will alternate with classroom exercises for the use of the various digital resources on which the course is based. For these latter activities, work methods are planned in groups of 2-3 students. All the necessary material for both the lectures and the exercises will be available throughout the course on myAriel website. During the activities, the Wooclap application will be also used to propose questions or surveys in order to increase teacher-student interaction. Exercises in the computer room will also be planned to acquire basic knowledge in the use of some process simulation software. Attendance at lectures and exercises is strongly recommended.
Teaching Resources
The reference material will be available on the "teaching content" page of the Moodle myAriel website of the course.
In particular, lecturers will provide:
- slides presented in class;
- literature articles, manuals of the adopted software;
- the following books (availables in "Biblioteca di chimica"):
· A. C. Dimian, C. S. Bildea, A. A. Kiss: Integrated Design and Simulation of Chemical Processes", 2nd Edition, Elsevier;
· Mohammadali Ahmadi, Artificial Intelligence for a More Sustainable Oil and Gas Industry and the Energy Transition, Elsevier (2024).
In particular, lecturers will provide:
- slides presented in class;
- literature articles, manuals of the adopted software;
- the following books (availables in "Biblioteca di chimica"):
· A. C. Dimian, C. S. Bildea, A. A. Kiss: Integrated Design and Simulation of Chemical Processes", 2nd Edition, Elsevier;
· Mohammadali Ahmadi, Artificial Intelligence for a More Sustainable Oil and Gas Industry and the Energy Transition, Elsevier (2024).
Assessment methods and Criteria
A project will be assigned to each student, or to small groups of students, on one of the topics of the course that involves the use of one or more digital applications, which will also be made available outside of class hours. The final exam will consist of an oral exam of the individual student with discussion and verification of both the report concerning the assigned project and the other topics covered in the course. Students who will carry out the assigned project in work groups will still have to take the final oral exam individually. The evaluation parameters of the exam will be:
· Ability to describe the project work carried out with appropriate terms
· Ability to critically reason about the project work carried out
· Ability to describe the digital technologies covered in the course
· Ability to critically reason about the digital technologies covered in the course
· Quality of the presentation
· Competence in the use of specialized vocabulary
The final grade will be given on a scale of 30. There are no intermediate assessments throughout the course.
· Ability to describe the project work carried out with appropriate terms
· Ability to critically reason about the project work carried out
· Ability to describe the digital technologies covered in the course
· Ability to critically reason about the digital technologies covered in the course
· Quality of the presentation
· Competence in the use of specialized vocabulary
The final grade will be given on a scale of 30. There are no intermediate assessments throughout the course.
ING-IND/25 - CHEMICAL PLANTS - University credits: 6
Laboratories: 16 hours
Lessons: 40 hours
Lessons: 40 hours
Professors:
Pargoletti Eleonora, Pirola Carlo
Professor(s)
Reception:
By email appointment
Department of Chemistry, Building 5A-O, 3rd floor
Reception:
Monday: 9:30-13:30 am
Pilot Plants Laboratory (Build # 7 of the Chemistry Departement)