CTU FEE Moodle
Quality and Reliability
B232 - Summer 23/24
This is a grouped Moodle course. It consists of several separate courses that share learning materials, assignments, tests etc. Below you can see information about the individual courses that make up this Moodle course.
Quality and Reliability - BD1M13JAS1
Main course
Credits | 6 |
Semesters | Winter |
Completion | Assessment + Examination |
Language of teaching | Czech |
Extent of teaching | 14KP+6KC |
Annotation
Terminology and definitions from the area of quality and reliability and their control, philosophy of quality, systems of quality control in the world. Reliability as a part of quality. Basic definitions from the area of reliability, basic distributions used in reliability and their basic characteristics. Back-up using a warm and cold standby, types of warm and cold standbys. Reliability of components and systems, calculation of reliability using composition and decomposition. and using a method of a list. Basic statistical methods and tools joined with quality control, managerial tools for quality control. Techniques FMEA and QFFD, house of quality. Capability of a process. Taguchi loss function. Audits. Statistical inspection.
Study targets
Student will acquaint with basic systems for quality and reliability control and with characteristis of these parameters. He will meet with basic processes for calculation of quality and reliability parameters and with the basic tools for control these parameters.
Course outlines
1. Terminology and definitions from the area of quality control and reliability. Systems of TQM, Kaizen, ISO 9000:2000, Poka-Yoke, Six Sigma.
2. Reliability as a part of quality. Basic reliability concepts. Basic reliability standards.
3. Types of reliability data. Theory of tolerances. Mathematical smoothing. Distributions used in reliability for a discrete variable.
4. Distributions used in reliability for a continuous variable.
5. Reliability of components and systems, method of composition and decomposition, method of a list.
6. Testing of data normality, data transformation.
7. Techniques of exploratory analysis, verification assumptions about data.
8. Accelerated reliability tests, Arrhenius and Eyring formula.
9. Derivation of reliability of and equipment, failure rate, repair rate.
10. Readiness, interval usability, coefficient of usability, coefficient of repairs. Systems with buffer containers.
11. Cold and warm standby, change of basic characteristics of a system by a back-up. Tree of failures, its construction and the use.
12. FMEA, QFD and house of quality.
13. Statistical inspection based on attributes, types of inspections.
14. Statistical inspection based on variables. Audits. Course of certification according to the ISO 9000:2000.
2. Reliability as a part of quality. Basic reliability concepts. Basic reliability standards.
3. Types of reliability data. Theory of tolerances. Mathematical smoothing. Distributions used in reliability for a discrete variable.
4. Distributions used in reliability for a continuous variable.
5. Reliability of components and systems, method of composition and decomposition, method of a list.
6. Testing of data normality, data transformation.
7. Techniques of exploratory analysis, verification assumptions about data.
8. Accelerated reliability tests, Arrhenius and Eyring formula.
9. Derivation of reliability of and equipment, failure rate, repair rate.
10. Readiness, interval usability, coefficient of usability, coefficient of repairs. Systems with buffer containers.
11. Cold and warm standby, change of basic characteristics of a system by a back-up. Tree of failures, its construction and the use.
12. FMEA, QFD and house of quality.
13. Statistical inspection based on attributes, types of inspections.
14. Statistical inspection based on variables. Audits. Course of certification according to the ISO 9000:2000.
Exercises outlines
1. Examples of systems of quality control. Costs joined with low quality, costs for quality control. Structure of a book of quality.
2. Topisc of team projects. Structure of a case study.
3. Processing of a case study.
4. The practical use of a theory of tolerances. The practical use of a mathematical smoothing.
5. Examples for the use of distributions for a discrete variable.
6. Examples for the use of distributions for a continuous variable.
7. Examples of a composition and decomposition of a system. Method of a list.
8. Normality testing by the use of a QC Expert program, skewness-kurtosis test. The use of an exploratore analysis.
9. Accelerated reliability testing.
10. Processing of a case study.
11. Processing of a case study.
12. Processing of a case study.
13. Defense of the projects.
14. Defense of the projects. Assessment.
2. Topisc of team projects. Structure of a case study.
3. Processing of a case study.
4. The practical use of a theory of tolerances. The practical use of a mathematical smoothing.
5. Examples for the use of distributions for a discrete variable.
6. Examples for the use of distributions for a continuous variable.
7. Examples of a composition and decomposition of a system. Method of a list.
8. Normality testing by the use of a QC Expert program, skewness-kurtosis test. The use of an exploratore analysis.
9. Accelerated reliability testing.
10. Processing of a case study.
11. Processing of a case study.
12. Processing of a case study.
13. Defense of the projects.
14. Defense of the projects. Assessment.
Literature
1. Montgomery, D. C.: Introduction to Statistical Quality Control. J. Wiley and Sons, 2005
2. Goetsch, D. L., Davis, B. D.: Quality Management: Introduction to Total Quality Management for Production, Processing, and Services, Prentice Hall, 2003
3. Goetsch, D. L., Davis, S.: Quality management for organizational excellence. Introduction to total quality (7th Edition), Prentice Hall, 2012
4. Dodson, B., Nolan, D.: Reliability Engineering Handbook, QA Publishing, LCA, 2002
5. Chandrupatla, T. R.: Quality and reliability in Engineering. Cambridge University Press, 2009
2. Goetsch, D. L., Davis, B. D.: Quality Management: Introduction to Total Quality Management for Production, Processing, and Services, Prentice Hall, 2003
3. Goetsch, D. L., Davis, S.: Quality management for organizational excellence. Introduction to total quality (7th Edition), Prentice Hall, 2012
4. Dodson, B., Nolan, D.: Reliability Engineering Handbook, QA Publishing, LCA, 2002
5. Chandrupatla, T. R.: Quality and reliability in Engineering. Cambridge University Press, 2009
Requirements
A student must attend at training courses and must obtain an assessment before examination. A knowledge of lectured matter and laboratory tasks will be required at examination.
Quality and Reliability - B1M13JAS1
Credits | 6 |
Semesters | Winter |
Completion | Assessment + Examination |
Language of teaching | Czech |
Extent of teaching | 2P+2C |
Annotation
Terminology and definitions from the area of quality and reliability and their control, philosophy of quality, systems of quality control in the world. Reliability as a part of quality. Basic definitions from the area of reliability, basic distributions used in reliability and their basic characteristics. Back-up using a warm and cold standby, types of warm and cold standbys. Reliability of components and systems, calculation of reliability using composition and decomposition. and using a method of a list. Basic statistical methods and tools joined with quality control, managerial tools for quality control. Techniques FMEA and QFFD, house of quality. Capability of a process. Taguchi loss function. Audits. Statistical inspection.
Study targets
Student will acquaint with basic systems for quality and reliability control and with characteristis of these parameters. He will meet with basic processes for calculation of quality and reliability parameters and with the basic tools for control these parameters.
Course outlines
1. Terminology and definitions from the area of quality control and reliability. Systems of TQM, Kaizen, ISO 9000:2000, Poka-Yoke, Six Sigma.
2. Reliability as a part of quality. Basic reliability concepts. Basic reliability standards.
3. Types of reliability data. Theory of tolerances. Mathematical smoothing. Distributions used in reliability for a discrete variable.
4. Distributions used in reliability for a continuous variable.
5. Reliability of components and systems, method of composition and decomposition, method of a list.
6. Testing of data normality, data transformation.
7. Techniques of exploratory analysis, verification assumptions about data.
8. Accelerated reliability tests, Arrhenius and Eyring formula.
9. Derivation of reliability of and equipment, failure rate, repair rate.
10. Readiness, interval usability, coefficient of usability, coefficient of repairs. Systems with buffer containers.
11. Cold and warm standby, change of basic characteristics of a system by a back-up. Tree of failures, its construction and the use.
12. FMEA, QFD and house of quality.
13. Statistical inspection based on attributes, types of inspections.
14. Statistical inspection based on variables. Audits. Course of certification according to the ISO 9000:2000.
2. Reliability as a part of quality. Basic reliability concepts. Basic reliability standards.
3. Types of reliability data. Theory of tolerances. Mathematical smoothing. Distributions used in reliability for a discrete variable.
4. Distributions used in reliability for a continuous variable.
5. Reliability of components and systems, method of composition and decomposition, method of a list.
6. Testing of data normality, data transformation.
7. Techniques of exploratory analysis, verification assumptions about data.
8. Accelerated reliability tests, Arrhenius and Eyring formula.
9. Derivation of reliability of and equipment, failure rate, repair rate.
10. Readiness, interval usability, coefficient of usability, coefficient of repairs. Systems with buffer containers.
11. Cold and warm standby, change of basic characteristics of a system by a back-up. Tree of failures, its construction and the use.
12. FMEA, QFD and house of quality.
13. Statistical inspection based on attributes, types of inspections.
14. Statistical inspection based on variables. Audits. Course of certification according to the ISO 9000:2000.
Exercises outlines
1. Examples of systems of quality control. Costs joined with low quality, costs for quality control. Structure of a book of quality.
2. Topisc of team projects. Structure of a case study.
3. Processing of a case study.
4. The practical use of a theory of tolerances. The practical use of a mathematical smoothing.
5. Examples for the use of distributions for a discrete variable.
6. Examples for the use of distributions for a continuous variable.
7. Examples of a composition and decomposition of a system. Method of a list.
8. Normality testing by the use of a QC Expert program, skewness-kurtosis test. The use of an exploratore analysis.
9. Accelerated reliability testing.
10. Processing of a case study.
11. Processing of a case study.
12. Processing of a case study.
13. Defense of the projects.
14. Defense of the projects. Assessment.
2. Topisc of team projects. Structure of a case study.
3. Processing of a case study.
4. The practical use of a theory of tolerances. The practical use of a mathematical smoothing.
5. Examples for the use of distributions for a discrete variable.
6. Examples for the use of distributions for a continuous variable.
7. Examples of a composition and decomposition of a system. Method of a list.
8. Normality testing by the use of a QC Expert program, skewness-kurtosis test. The use of an exploratore analysis.
9. Accelerated reliability testing.
10. Processing of a case study.
11. Processing of a case study.
12. Processing of a case study.
13. Defense of the projects.
14. Defense of the projects. Assessment.
Literature
1.David L. Goetsch, Stanley Davis. Quality Management for Organizational Excellence: Introduction to Total Quality. Pearson Education, 2012
2. Montgomery. D. C. Introduction to Statistical Quality Control. John Wiley & Sons. 2012, 17th edition
3. D. C. Summeras. Quality mangements. Prentice Hall. 2008
4. Pyzdek, T., Keller, P.: The Six Sigma Handbook, McGraw-Hill, 2014
5. Breyfogle III, F. W. Implementing Six Sigma. New York: John Wiley & Sons. 1999
2. Montgomery. D. C. Introduction to Statistical Quality Control. John Wiley & Sons. 2012, 17th edition
3. D. C. Summeras. Quality mangements. Prentice Hall. 2008
4. Pyzdek, T., Keller, P.: The Six Sigma Handbook, McGraw-Hill, 2014
5. Breyfogle III, F. W. Implementing Six Sigma. New York: John Wiley & Sons. 1999
Requirements
A student must attend at training courses and must obtain an assessment before examination. A knowledge of lectured matter and laboratory tasks will be required at examination.