Czech

6

Not applicable.

Knowledes related to process control and optimisation, presentation skills and temwork problems solving. - Describe the importance of statistical estimates and assess the impact of random effects, including a definable process stability, SPC and regulatory processes;
- Categorize the sources of variability and use the graphical analysis of data sources, including stratification variability;
- Represent the position and variability using the histogram, box-plot and practice normal probability plots for assessing normality;
- Apply the stratification of the data and explain the sources of variability;
- Estimate the sample mean and sampling variance, estimate the values ​​of quality parameters using a model of a normal distribution;
- Describe the difference between the base and a sample, to distinguish between population parameters and selection characteristics;
- Describe the characteristics of a representative selection and appreciate the role of sampling error;
- Describe the quality of the measured data in relation to the application of metrology and measurement processes, suggesting Measurement System Analysis, appreciation of operational definitions;
- Describe the sources of variability data, whether actual variability of the measured parameters and the variability of the measurement system;
- Explain the concept of Six Sigma as a toolkit for improving processes and products, respectively, as an approach for process improvement (the role and selection of six sigma projects, create a project charter);
- Distinguish costs nejakost distinguish the cost of poor quality (COPQ) describe the role of quality management systems;
- Distinguish five stages of DMAIC methodology, describe the importance of phase definition, measurement, analysis, implementation and management measures; represent the difference between the PDCA cycle and the DMAIC methodology;
- Discuss identification of critical parameters of the output (CTQ), apply draw a tree decay requirements and utilize incorporate into Kano analysis;
- Describe the determination voice of the customer (LSL, USL) and the assessment of voice process (LCL, UCL), to assess analyzed graphical and numerical expression, analyze the results of analysis of the process;
- Name life cycle stages of the development project, list the contents of these phases and describe the properties of the project, apply foundation, the project charter,
- Apply the use of the logical framework and the use of structure-life (WBS), practice using the network diagram and determine the priority dependency, activity duration estimating method PERT, Gantt chart plotting;
- Understand practicing effective communication and collaboration of the project team to demonstrate the idea of ​​transactional analysis, practice presentation skills, apply for brainwriting brainstorming and team problem-solving;
- Describe the development of approaches to quality management, express the difference between repressive and preventive approach, define the problem, solve the problem in a structured way, through the fishbone diagram to describe the causal factors;
- Use the seven basic tools to interpret Pareto chart, identify identifiable sources of variability in the control chart, applied checklists, describe the process map process, use the correlation diagram;
- Understand the nine steps of the methods used G8D solve problems with poor quality, fill in the table G8D report, discuss the difference between the partial steps to understand the link between defining the problem, identifying and demonstrating the root causes and the adoption of measures;
- Apply statistical evaluation of failures, discuss the importance of FMEA analysis for the prevention, implementation of FMEA analysis - from function to types of defects, criticality, causes, expected výstkytu, methods of detection, detectability, to RPN and propose preventive measures.

The subject knowledge on the Bachelor´s degree level is requested. In the field of applied statistics, students should be able to:
- Explain the basic concepts of probability and statistics (arithmetic mean, the distribution of random variables,
probability of the event)
- Knows how to determine an estimate of basic statistical charakteritic (arithmetic mean, median, mode, variance,
the standard deviation, work with the histogram).
- Can work with random variable and its numerical characteristics (mean, variance, standard
deviation, percentiles, mode, median)
- Able to perform statistical tests (t-test, F-test, paired test)

Not applicable.

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.

Student’s appraisal-examination: excellent (90-100 points), very good (80-89 points), good (70-79 points), favourable (60-69 points), satisfactory (50-59 points), unsatisfactory (0-49 points). Points allocation according the written notification at the course beginning.

Process control introduction
Process approach
Metrology and quality of measured data
Operational process control
Process control procedures and methods
Statistical methods and tools for decision making and process control.
Process variability, sources of process variability and statistical process control.
Proces stability evaluation and assurance
Process capability evaluation
Quality planning
Design of experiment techniques (DOE)
Six sigma
Economical aspects of process management and lean thinking

Not applicable.

Development of students qualification related to the study area

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.

Not applicable.

Not applicable.

Novotný, R. Řízení technologických procesů. FEKT VUT v Brně, 2015.
Novotný, R. Řízení technologických procesů - prezentace. FEKT VUT v Brně, 2015.

Not applicable.

39 hours, optionally

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).