Course detail

Quality management

FEKT-MPA-QMAAcad. year: 2021/2022

Each student of the Technical University is expanding his / her competence by studying quality management. Process quality is a question that concerns not only managers and engineers, but also entrepreneurs who want to succeed with their products and services. Understanding that quality is free, that the cost of poor quality affects the financial health of a company, and the methods and tools used in quality management are irreplaceable is not only important in the area of production.

Language of instruction

English

Number of ECTS credits

6

Mode of study

Not applicable.

Learning outcomes of the course unit

Knowledge and skills for work in various professions.
Recognize the principles, practices, and types of quality management tools.
Connecting the tools with engineering goals.
Understand the contributors to the cost of quality.
Understanding the background and meaning of the DMAIC process improvement cycle.

Prerequisites

There are no prerequisites.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Techning methods include lectures, computer laboratories and practical laboratories. Course is taking advantage of e-learning (Moodle) system. Students have to write a single project/assignment during the course.

Assesment methods and criteria linked to learning outcomes

Maximum 70 points for completed tasks during the semester, 30 points final test.

Course curriculum

1. Quality as a competitive advantage, impact of quality on productivity and profit. Japanese strategies, zero defects, quality control circles, kaizen and PDCA.
2. Process approach and process management. Process management as the foundation of organizational management. Process focus and continuous Improvement; end-to-end view of the process, SIPOC.
3. Hidden costs of poor quality, quality is free concept. PAF model,cost of poor quality (COPQ). Proactive process and focus on prevention of defects versus reactive process and focus on the identification of defects
4. Waste and defects elimination by applying lean methodology, quality at the source, mistake proofing and poka-yoke. Incoming, in-process, final inspection.
5. History of quality assurance: Taylor, Ford, Shewhart, Ishikawa. Seven quality management principles. Deming’s 14 Points and deadly diseases. The Juran trilogy: quality planning, quality control and quality improvement.
6. Dimensions of quality: Performance, reliability, durability, seviceability, aesthetics, pereived quality, conformance to standards. Quality characteristics and standards or specifications, nominal or target value, upper specification limit and lower specification limit.
7. Tools and methods for process quality improvement. Qualitative tools such as 5 why, concentration diagrams, cause and effect diagrams. Quantitative tools introduction.
8. Teamwork problem solving techniques. Scrap and rework, repair and troubleshooting. Identification of causes, random and assignable causes. DMAIC methodology.
9. Supplier quality management, global eight disciplines (G8D). From quality problem recognition, problem description, short-term measures, cause analysis, to a preventive action.
10. Factual approach to decision making, decision based on fact. Collection and summarizing data that enables process improvements. Mean, standard deviation, normal distribution. Statistical traps.
11. Product inspection vs. process control. Inspection, testing and measurement, metrology. Quality testing, Shewhart control charts. Process capability concept.
12. Six sigma principles and methodologies. Quality management systems and standards (ISO 9001).
13. Key concepts and case studies.

Work placements

Not applicable.

Aims

Quality management is an important aspect of today's life. It's not just about making a product, providing a service. It relies on prevention instead of repression. It uses methods and tools to meet customer requirements as well as regulatory requirements. The aim is to acquaint students with the concepts and approaches that are applied today in companies and improve their position on the labor market. To show how quality management is reflected in the work of engineers, designers, process engineers, quality engineers, technologists, metrologists in a view in which practice prevails over theory.

Specification of controlled education, way of implementation and compensation for absences

The content and forms of instruction in the evaluated course are specified by a regulation issued by the lecturer responsible for the course and updated for every academic year.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Jones, E., C.: Quality management for organization using lean Six Sigma techniques. Boca Raton: CRC Press, 2014, ISBN: 978-1-4398-9782-9 (EN)
Mauch, P., D.: Quality management: theory and application. Boca Raton: CRC Press, Taylor & Francis Group, 2017, ISBN: 978-1-138-11620-7 (EN)
Sartor, M., Orzes, G.: Quality management: tools, methods, and standards. Bingley: Emerald Publishing, 2019, ISBN: 978-1-78769-804-8 (EN)
Su, Ch., T.: Quality engineering: off-line methods and applications. Boca Raton: CRC Press, 2013, ISBN: 978-1-4665-6947-8 (EN)

Recommended reading

Not applicable.

Classification of course in study plans

  • Programme MPA-MEL Master's 2 year of study, summer semester, compulsory-optional
  • Programme MPAD-MEL Master's 2 year of study, summer semester, compulsory-optional

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

Syllabus

1. Management introduction, planning, organization, coordination, inspection, organisational structure, authority and responsibility, job description, standardisation in repeated processes, organizational culture impact.
2. Process management in the organisation, IPO diagram, SIPOC a process approach. Critical parameters identification related to product and process, QFD concept.
3. Metrology, quality of measured data, measurement system attributes, traceability chain, repeatability and reproduceability analysis, analysis of attributive measurement system.
4. Operational process control, repressive and preventive approach, non-conformance product control, traceability, G8D process, management of one-shot and repeated processes.
5. Process management methods and tools, seven basic tools, product and process FMEA analysis.
6. Statistical methods and tools for decision making and process control.
7. Process variability and sources of process variability, statistical process control, control charts, process control charts types.
8. Process stability evaluation and assurance.
9. Process capability, tolerance setting and requirements specification and capability and performance indexes.
10. Quality planning, critical parameters determination, tolerance limits specification, measurement systems evaluation, Process stability and process capability evaluation.
11. Critical technological factor determination by using design of experiment techniques (DOE).
12. Industrial and transactional process improvement approaches, lean thinking, six sigma and lean six sigma, DMAIC methodology and belt roles.
13. Economical aspects of process management cost of poor quality - COPQ, lean thinking, material and information flow analysis (value stream map), waste identification and value added analysis.

Exercise in computer lab

39 hod., optionally

Teacher / Lecturer

Syllabus

1. SIPOC diagram, critical to quality parameters determination (CTQ), tolerance setting, process mapping, team results presentation. Situational study solved by teamwork.
2. Quality problem causes evaluation and analysis, cause and effect diagram, interrelationship diagram, nominal group technique and team results presentation. Situational study solved by teamwork.
3. Technological process FMEA analysis – case study with output in the form of FMEA table. Team results presentation and comparison.
4. Seminar works presentation, colloquium and feedback – part I.
5. Applied descriptive statistics methods for technological treatment evaluation. Data stratification, graphical and numerical analysis. Computer exercise.
6. Applied inductive statistics methods for quality assurance – t-test, ANOVA, chi-square – Situational study, computer exercise.
7. Seminar works presentation, colloquium and feedback – part II.
8. Repeatability and reproduceability study by using mean-range method. Measurement system establishing, experiment execution and evaluation.
9. Control charts, control limits setting and logical subgroups definition. Technological process simulation study, computer exercise.
10. Technology capability evaluation. Analytical examples solved by using statistical software.
11. Technological process optimisation by using design of experiments techniques. Case study by using virtual laboratory.
12. Seminar works presentation, colloquium and feedback – part III.
13. Quality problem solving in the frame of an industrial company – situational study by using action learning (labyrinth case study).