Course detail

Technological process control

FEKT-NRTPAcad. year: 2015/2016

Technical aspects of technological processes management related to process control, optimisation and improvement. Systematic procedures, methods and tools related to industrial and transaction process control.

Language of instruction

English

Number of ECTS credits

6

Mode of study

Not applicable.

Guarantor

doc. Ing. Radovan Novotný, Ph.D.

Department

Department of Microelectronics (UMEL)

Learning outcomes of the course unit

Knowledes related to process control and optimisation, presentation skills and temwork problems solving.

Prerequisites

The subject knowledge on the Bachelor´s degree level is requested.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.

Assesment methods and criteria linked to learning outcomes

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.

Course curriculum

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

Work placements

Not applicable.

Aims

Development of students qualification related to the study area

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

Pyzdek,T. The Six Sigma Handbook. The McGraw-Hill Companies 2001. ISBN 0-07-141015-5

Recommended reading

Not applicable.

Classification of course in study plans

  • Programme EECC-MN Master's

    branch MN-MEL , 1 year of study, summer semester, elective specialised

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

doc. Ing. Radovan Novotný, Ph.D.

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

doc. Ing. Radovan Novotný, Ph.D.

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).