Digitalisation in the chemical industry
A tantárgyleírás hatályossága
| Subject name (Hungarian, English) |
Digitalizáció a vegyiparban
Digitalisation in the chemical industry
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| Subject code | BMEVEKFM217 | ||||||||||||
| Subject type | — | ||||||||||||
| Training Level | — | ||||||||||||
| Course types and hours (weekly/semester) |
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| Assessment type | vizsga | ||||||||||||
| Credits | 5 | ||||||||||||
| Subject coordinator |
DR. Havasi Dávid
position: adjunktus
contact:
havasi.david@vbk.bme.hu
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| Responsible department |
Kémiai és Környezeti Folyamatmérnöki Tanszék
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| Faculty | Vegyészmérnöki és Biomérnöki Kar | ||||||||||||
| Subject website | — | ||||||||||||
| Primary curriculum type | — | ||||||||||||
| Direct prerequisites – Strong prerequisite | none | ||||||||||||
| Direct prerequisites – Weak prerequisite | none | ||||||||||||
| Direct prerequisites – Parallel prerequisite | none | ||||||||||||
| Direct prerequisites – Milestone prerequisite | none | ||||||||||||
| Direct prerequisites – Exclusion | none |
Objectives
Overview of the industrial revolutions, meaning and elements of Industry 4.0. Basics of Lean philosophy, its relation to Industry 4.0. The 5S method and the Kaizen principle (loss reduction). The Lean startup method. Basics of chemical informatics, representation of molecules and modelling their behaviour. Opportunities to extend and explore the available chemical space, its role in the pharmaceutical, pesticides, cosmetics and semiconductor industries, virtual screening. Retrosynthetic methods and processing of literature data, natural language processing (NLP). Management and exploitation of large amounts of data. Artificial intelligence, machine learning, deep learning and their applications in chemistry and chemistry. Data standardisation, database extension through automation. Potential and limitations of laboratory automation. Machine vision and image processing. Digital identification, tracking and data transmission technologies. Application of augmented and virtual reality in chemical and chemical systems and research. Industrial Internet of Things (IIoT) and cyber security. Function, design and operation of Programmable Logic Controllers (PLCs). PLC programming languages: instruction list, ladder diagram, function block diagram, structured text, sequential flow chart.
Learning outcomes
Ez a tantárgy a KKK rendeletben meghatározott, következő kompetenciák fejlesztését szolgálja:
Knowledge
Skills
Attitudes
Autonomy and responsibility
Oktatási módszertan
Not provided.
Tanulástámogató anyagok
Not provided.
Recommended preliminary knowledge for completing the subject
General rules
Assessment methods
In-term assessments
No detailed assessments provided.
Weight of in-term assessments
No weights provided.
Exam-period assessments
No detailed assessments provided.
Weight of exam elements
No weights provided.
Grade calculation
No grade thresholds provided.
Attendance requirements
No attendance requirements provided.
Rules for retake and resubmission
Not provided.
Short description
Not provided.
Detailed description
Not provided.
Recommended courses
Not provided.
Workload to complete the subject
No workload breakdown provided.
Validity of subject requirements
Curriculum placement
| Faculty | Program | Curriculum | Curriculum type | Primary |
|---|---|---|---|---|
| Default Faculty | vegyészmérnöki | Vegyészmérnöki mesterképzési szak tanterve | kötelező | nem |