Course detail
Maintenance of Machinery and Equipment
FSI-9USZ Acad. year: 2022/2023 Both semester
The course is focused on the most sophisticated knowledge in the area of machine and equipment maintenance. Attention is devoted to the problems of failures and wearing of machinery. Additionally, technical diagnostics, sensors, diagnostic tools, systems and models as well as diagnostic signal analyses and processing are discussed. The emphasis is laid on individual diagnostic methods and clarifying their applications for technical condition assessment of the observed objects. In this relation, a collection of data from technical diagnostics, their evaluation and visualization of diagnostic systems are also solved. The emphasis is laid on the complex solution of preventive, autonomous, predictive and pro-active maintenance. Management and maintenance engineering, i.e., planning strategy, legislation, outsourcing, economics, maintenance productivity, spare parts, overhauls, maintenance quality management, audits, are also discussed. A special attention is devoted to some maintenance methods, for example, total productive maintenance (TPM) and its application in practical terms. The existing software for different maintenance areas including possible maintenance visualization in a particular company is also discussed. A relationship among maintenance, maintenance management and company management is analysed.
The course is also based on Maintenance 4.0 and Industry 4.0 initiatives.
Language of instruction
Czech
Supervisor
Learning outcomes of the course unit
In the sense of the below mentioned annotation and curriculum, the student will gain a comprehensive knowledge of the area of machine and equipment maintenance including other machine services, which will be useful for his engagement into solving different issues in industrial machinery and electrotechnical practice related to this area.
Prerequisites
The knowledge of mathematics and physics at the level of graduated technical studies is assumed. Basic knowledge of quality management is also welcomed.
Planned learning activities and teaching methods
The course includes lectures and tutorials in pre-arranged terms.
Assesment methods and criteria linked to learning outcomes
For the exam students will study the prescribed issues. They will also elaborate in writing a specific topic from the maintenance area whose defense will be part of the oral exam. Oral examination is held after the defense of a written topic from the area of maintenance in the form of a discussion on the problems according to the course's curriculum.
Aims
The objective of the course is to gain knowledge in the area of machine and equipment maintenance.
Specification of controlled education, way of implementation and compensation for absences
The course is checked according to the student´s participation in pre-arranged tutorials.
The study programmes with the given course
Programme D-KPI-P: Design and Process Engineering, Doctoral, recommended course
Programme D-KPI-K: Design and Process Engineering, Doctoral, recommended course
Type of course unit
Lecture
20 hours, optionally
Syllabus
1. Machine and equipment operation. Life phases. Maintenance. Failures. Causes, origin and development of failures. Failure mechanism and their external symptoms. Failure classification according to the nature of their origin. Types of machinery wearing.
2. Machine and equipment conditions. Technical diagnostics – diagnosis, prognosis, genesis. Diagnostic tools. Off-line (walking) and on-line diagnostics, monitoring, condition monitoring, diagnostic models, diagnostic systems, diagnostic signals – analyses and processing.
3. Sensors, sensor parameters, sensors of mechanical quantities . Sensors of mechanical vibration, sensors of mechanical tension (tensometers), pressure gauges, fluid flowmeters, level gauges, temperature sensors, electrical, magnetic and chemical sensors. Smart sensors.
4. Vibrodiagnostics, electrical diagnostics, thermal diagnostics, tribodiagnostics, noise diagnostics, acoustic emissions, flow and level diagnostics, pressure diagnostics. Non-destructive material testing. Multi-parametric diagnostics. Remote machine diagnostics.
5. Data acquisition from machine and equipment diagnostics, assessment methods. Control diagrams as the tools of statistical process control (SPC). Statistical data analysis, data mining. Recognition of technical diagnostics, statistical methods for classification, clustering, neural networks, diagnostic expert systems, fuzzy systems. Machinery wearing indication, diagnostic monitoring systems, vizualization of diagnostic systems. Technical diagnostics within Industry 4.0 initiative.
6. Preventive maintenance with pre-defined intervals, maintenance according to technical conditions – predictive, pro-active, and testing. Preventive maintenance optimization. System creation and management of preventive, predictive and pro-active maintenance.
7. Maintenance management and engineering – maintenance organization and management in a company (strategy, outsourcing, legislation, planning, schedule, material sources, spare parts, overhauls, and re-engineering), maintenance productivity assessment economics (finance, key indicators, benchmarking), maintenance quality management, (normalized management system, documentation and audit), environmental maintenance management.
8. Maintenance focused on failure free operation – RCM (Reliability Centred Maintenance). Other methods.
9. Total productive maintenance – TPM.
10. Software for maintenance: planning, maintenance management and agenda, management and maintenance of tangible asset and life control, stock holding. Maintenance visualization. Relationship of maintenance, maintenance management and company´s management. Maintenance 4.0 and Industry 4.