KUM664 - EXPERIMENT and LABORATORY KNOWLEDGE
Course Name | Code | Semester | Theory (hours/week) |
Application (hours/week) |
Credit | ECTS |
---|---|---|---|---|---|---|
EXPERIMENT and LABORATORY KNOWLEDGE | KUM664 | Any Semester/Year | 1 | 4 | 3 | 7 |
Prequisites | ||||||
Course language | Turkish | |||||
Course type | Elective | |||||
Mode of Delivery | Face-to-Face | |||||
Learning and teaching strategies | Lecture Discussion Question and Answer Observation Field Trip Team/Group Work Role Play Preparing and/or Presenting Reports Demonstration Experiment Drill and Practice Case Study Problem Solving Brain Storming Project Design/Management Other: individual study | |||||
Instructor (s) | To be determined by TSE and the department | |||||
Course objective | The objective of this course is to develop students? skills to make comparison tests as a part of the quality assurance for the laboratory activities and to interpret the results and to solve the common and general problems in the laboratories | |||||
Learning outcomes |
| |||||
Course Content | ? General information about TS EN ISO/IEC 17025 and accreditation ? Security and privacy rules of laboratories ? Definition of measurement uncertainty and sources of uncertainty ? Preparing the samples and performing the tests and evaluation of the results ? Availability of the quality of test results ? Proficiency tests organized by TSE and its labs and statistical methods ? Common and general problems in the laboratory and solutions | |||||
References | ? TS EN ISO/IEC 17025 Standards ? Training notes of TSE |
Course outline weekly
Weeks | Topics |
---|---|
Week 1 | Introduction and general information about TSE and its labs - security and privacy rules |
Week 2 | TS EN ISO/IEC 17025 ? general introduction |
Week 3 | TS EN ISO / IEC 17025 standard 5.Technical Requirements |
Week 4 | TS EN ISO / IEC 17025 standard 5.4 Test and calibration methods and validation of methods |
Week 5 | Definition of measurement uncertainty and sources of uncertainty for a measurement method |
Week 6 | Case study about measurement uncertainty |
Week 7 | Proficiency tests organized by TSE and its labs and statistical methods |
Week 8 | Midterm Exam |
Week 9 | Preparing the samples and performing the tests and evaluation of the results ? case study |
Week 10 | Quality assurance of the test results |
Week 11 | Practical study about the quality assurance of the test results |
Week 12 | Preparing the samples and performing the tests and evaluation of the results ? report the results |
Week 13 | Common and general problems and solutions for the laboratory |
Week 14 | Case study about common and general problems and solutions for the laboratory |
Week 15 | Study for the final exam |
Week 16 | Final exam |
Assesment methods
Course activities | Number | Percentage |
---|---|---|
Attendance | 14 | 8 |
Laboratory | 0 | 0 |
Application | 2 | 2 |
Field activities | 0 | 0 |
Specific practical training | 0 | 0 |
Assignments | 1 | 4 |
Presentation | 0 | 0 |
Project | 1 | 6 |
Seminar | 0 | 0 |
Midterms | 1 | 25 |
Final exam | 1 | 55 |
Total | 100 | |
Percentage of semester activities contributing grade succes | 1 | 45 |
Percentage of final exam contributing grade succes | 1 | 55 |
Total | 100 |
WORKLOAD AND ECTS CALCULATION
Activities | Number | Duration (hour) | Total Work Load |
---|---|---|---|
Course Duration (x14) | 14 | 1 | 14 |
Laboratory | 0 | 0 | 0 |
Application | 14 | 4 | 56 |
Specific practical training | 0 | 0 | 0 |
Field activities | 0 | 0 | 0 |
Study Hours Out of Class (Preliminary work, reinforcement, ect) | 13 | 4 | 52 |
Presentation / Seminar Preparation | 0 | 0 | 0 |
Project | 1 | 16 | 16 |
Homework assignment | 1 | 12 | 12 |
Midterms (Study duration) | 1 | 20 | 20 |
Final Exam (Study duration) | 1 | 40 | 40 |
Total Workload | 45 | 97 | 210 |
Matrix Of The Course Learning Outcomes Versus Program Outcomes
D.9. Key Learning Outcomes | Contrubition level* | ||||
---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | |
1. Reach the necessary knowledge and methods within the scope of Quality and Conformity Assessment Engineering through scientific research; evaluate knowledge and methods; utilize and implement them during quality monitoring, conformity assessment and quality improvement processes with a system point of view. | X | ||||
2. Implement engineering tools and modeling techniques for the innovative design, development, analysis and improvement of quality that integrates man, machine, material and knowledge. | X | ||||
3. Determine the national and international standards of products, processes and systems and prepare the necessary documentation. | X | ||||
4. Develop measurement systems to assess the conformity of products and systems and implement them. | X | ||||
5. Develop and plan projects for quality improvement, conformity assessment and standard determination; monitor, control and evaluate projects in progress. | X | ||||
6. Evaluate the data obtained from systems through the analysis with advanced methods; complete limited and missing data within the scope of quality and conformity engineering through scientific methods. | X | ||||
7. Report and present studies, projects, outcomes/results and evaluations on the design, development, analysis, planning, monitoring and improvement of quality systems. | X | ||||
8. Effectively utilize computer software, information systems, information and communication technology related with quality and conformity engineering. | X | ||||
9. Are aware of the professional responsibility, describe the technological, economic and environmental effects of the quality and conformity assessment engineering applications, work as an individual independently and as a team member having an understanding of the scientific and institutional ethical values, take responsibility and lead the team. | X | ||||
10. Are aware of the up-to-date quality and conformity assessment engineering applications, follow the necessary literature within the scope of quality and conformity assessment engineering; have the competency to reach knowledge in a foreign language, to quote and implement them | X |
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest