SylabUZ
| Course name | Production Data Analysis |
| Course ID | 06.9-WM-MaPE-P-PDA- 23 |
| Faculty | Faculty of Mechanical Engineering |
| Field of study | Management and Production Engineering |
| Education profile | academic |
| Level of studies | First-cycle studies leading to Engineer's degree |
| Beginning semester | winter term 2023/2024 |
| Semester | 7 |
| ECTS credits to win | 3 |
| Course type | obligatory |
| Teaching language | english |
| Author of syllabus |
|
| The class form | Hours per semester (full-time) | Hours per week (full-time) | Hours per semester (part-time) | Hours per week (part-time) | Form of assignment |
| Lecture | 15 | 1 | - | - | Exam |
| Project | 30 | 2 | - | - | Credit with grade |
The main effect of the course will be learning about the essence of production data analysis in the enterprise as well as methods and models of data analysis.
Knowledge of mathematics and the area of production and service management.
Lecture (S - full-time studies)
SW1: Industry 4.0 Technologies - big data analysis.
SW2: Data - Information - knowledge. Synthesis of knowledge. Formalization of knowledge.
SW3-SW5: Business analytics in the SAP IT system.
SW6-SW7: Application of Business Intelligence (BI) tools to manage business processes
SW8: Analytical reports in the SAP system.
Project:
SP1: Preparation of the database for analysis in the SAP system.
SP2-SP3: Data analysis of the project management area in the SAP system.
SP4-SP5: Data analysis of the area of customer relationship management in the SAP system.
SP6-SP7: Analysis of sales area data in the SAP system.
SP8-SP10: Data analysis of the warehouse management area in the SAP system.
SP11-SP13: BI in the SAP system.
SP11-SP12: BI in the SAP system.
SP13-SP14: Analytical reports in the SAP system.
SP15: Design of data analysis areas in the SAP system.
Conventional lecture. Project.
| Outcome description | Outcome symbols | Methods of verification | The class form |
Lecture: Written exam preceded by obtaining a pass from project.
Project: mark for the project
Passing the course: The condition for passing the course is to pass all its forms. The final grade for passing the course is the arithmetic mean of the grades for individual forms of classes.
1. Patalas-Maliszewska J.,Managing Manufacturing Knowledge in Europe in the Era of Industry 4.0, Routledge, 2022
2. Atluri DT., Bardhan D., Ghosh S., Ghosh S., Saha A., SAP Data Intelligence - The Comprehensive Guide, Rheinwerk Publishing, 2022
3. Patalas-Maliszewska J., Managing Knowledge Workers - Value Assessment, Methods, and Application tools, Springer Verlag, 2013
Modified by prof. dr hab. inż. Justyna Patalas-Maliszewska (last modification: 12-05-2023 13:09)
