FSI-9EXTAcad. year: 2023/2024
The aim of this course is to provide students with a general and useful introduction to the experimental methods for measurement and analysis of friction, lubrication and wear. The course covers fundamentals of design of experiment, determination of precision, accuracy and errors of measurement and statistical analysis of data.
Language of instruction
Number of ECTS credits
Mode of study
Knowledge from general courses on mechanics, physics, math, machine elements, materials technology and surface engineering.
Rules for evaluation and completion of the course
Conditions for gaining the exam:- submission and defense of individual work on measurement or experimental analysis of selected tribological problem. The work would include theoretical description, error and measurement quality analysis and design of results evaluation.
Absence from lessons may be compensated for according to instructions of the teacher.
The main aim is to provide basic knowledge of the experimental methods, theory of measurement and experiments in the field of tribology with respect to the topic of PhD thesis.
- The ability to identify the key problems for experimental validation of tribological problems.- The ability to select proper experimental methods with respect to the specific problems in the field of tribology.- The ability to design experiments and assess quality of measurements.- The ability to statistically evaluate results.
Prerequisites and corequisites
Bhushan, B. Principles and Applications of Tribology. New York: John Wiley, 1999. ISBN 04-715-9407-5.
Classification of course in study plans
Teacher / Lecturer
- Samples and Characterization of Test Specimens. Lubricant and Process Fluid and Solids Analysis. - Sample Preparation. Control of the Test Environment.- Surface Topography Measurement.- Tribometers. Controlling of Load, Measurement of Friction and Wear.- Optical Methods for Analysis of Tribological Processes.- Wear Analysis, Surface and Subsurface Micrography, Chemical Analysis.- Design of Experiment.- Statistical Analysis of Data.- Measurement Errors, Noise, Precision and Accuracy.