754110 Quality management II
This page is available under these URLs:
- Semester hours
- Lecturer (assistant)
- Domig, Konrad , Dürrschmid, Klaus , Zitz, Ulrike , Bender, Denisse
- Offered in
- Sommersemester 2023
- Languages of instruction
- Quality management systems according to ISO 9001 - quality requirements, sustainable implementation in practice
- Quality policy and objectives
- Quality planning – quality indicators, tools like QFD
- Errors and error culture, error avoidance and risk minimization, FMEA and HACCP
- Systematic error correction, techniques
- Visualize and analyze operational processes, process organization and control, productivity-oriented maintenance
- Problem solving or analysis, elementary quality tools, types of control charts
- Process control, statistical process control, capability studies, acceptance sampling
- computerized procedures, data integrity and security
- Classification of test equipment, requirements, test equipment management
- Measuring and testing, quality features of measuring methods
- Adjust, calibrate and calibrate, standards
- Test instructions and test reports
- Method validation, method suitability, method assessment
- Measurement uncertainty, assessing results at the limit, aspects of sampling
- Method comparisons, ring trials and reference materials
- Previous knowledge expected
Quality Management I
- Objective (expected results of study and acquired competences)
After successfully completing the course, the students can describe the basic procedure for the realization and promotion of a living QM system and know what is important. Using ISO 9001 as an example, they can characterize the relevant requirements for a management system and know how to put them into practice. You know the importance of internal audits and can describe the implementation of audits as well as options for operational implementation of the continuous improvement process.
Graduates know the importance of quality planning and have an overview of their tools. You can use the Quality Function Deployment method to analyze and evaluate the data obtained. The classic quality tools and quality management tools are known, can be used and interpreted.
You know terms such as Computer Integrated Manufacturing, Computer Aided Quality Management, the tasks and functionality of process control systems and laboratory information systems. You know about the requirements regarding data integrity and data security when using computers.
The graduates of this course understand the concept of quality improvement and what it is used for. You know the essential methods of error management and key figure groups. They are familiar with the basic structure of problem-solving processes and know the Plan Do Check Act cycle. Methods and tools for quality improvement such as benchmarking, balanced scorecards and the Six Sigma concept are known in their basic structure.
Graduates can present and analyze processes. They know which methods can be used to record and analyze errors. They know the basic types of sampling and know how sampling and analysis errors can be determined. You know the meaning of the term traceability. They know what test equipment is and how to use it. They have the theoretical basics to create work instructions and test reports. They are familiar with quality control methods and know how process capability can be assessed. They understand the importance of quality control charts and have the basic knowledge to create and interpret them.
They can describe the concept of validation of an analytical method and know about the validation process. They know different types of calibration of analytical methods and have the theoretical basics to determine process characteristics such as sensitivity, selectivity and accuracy as well as detection and determination limits. You will understand the importance of defining the working range and will be able to differentiate between types of bias and apply statistical tests to verify a basic calibration.
The graduates know different statistical methods for comparing methods based on their performance parameters, understand the importance and implementation of interlaboratory trials. You can differentiate the term measurement uncertainty from measurement deviation and describe the basic process steps for determining the measurement uncertainty according to GUM.
You can find more details like the schedule or information about exams on the course-page in BOKUonline.