Academic year 2022 - 2023

•   Quality Management MS00BX00-3002 30.01.2023-31.05.2023  5 credits  (YIQMS22V) +-
  Competence objectives of study unit

  After completing the course, the student can
  -define the principles and value of Quality Management Systems
  -apply the main standards in her/his own business area
  -establish the main principles of quality management in practical
  -understand the value of quality management to improve processes and cost-effectiveness of a company
  -apply quality management to facilitate a positive company culture and teamwork

  Content of study unit

  -Quality Management and ISO standards
  -Lean, Lean (six) Sigma, Agile
  -Customer-centric approach, Lean leadership, Lean culture, Continuous improvement

  ---

  Teacher(s) in charge

  Sari Airenne

  Heidi Salokangas

  Teachers and responsibilities

  Heidi Salokangas ja Sari Airenne

  Mode of delivery

  Face-to-face

  Learning material

  Material is provided in ItsLearning platform.
  
  e-book:
  Sarah E. Burke and Rachel T. Silvestrini. The Certified Quality Engineer Handbook. ASQ Quality Press
  Milwaukee, Wisconsin 2017
  
  ISO standards (SFS online)

  Learning methods

  -On-line videos and lectures
  -Independent exercises, quizzes
  -Group assignments
  -Individual assignments

  Objects, timing and methods of assessment

  The grade will be consist of three assignments (Individual and group assignments)
  
  Assessment of teacher, peer review and self- assessment are included.
  
  Grading is F-5 (average of three assignments)

  Teaching language

  English

  Timing

  30.01.2023 - 31.05.2023

  Enrollment date range

  01.12.2022 - 17.02.2023

  • 5 credits

  Group(s)

  • YIQMS22V

  Responsible unit

  Engineering and Business

  Degree Programme(s)

  Master of Engineering, Industrial Quality Management

  Assessment scale

  H-5

  Alternative methods of attainment for implementation

  -

  Exam dates and retake possibilities

  Grading is based on assignments.

  Pedagogic approaches

  -Team-based learning in student groups and presentations (substance and communication skills)
  -Individual assignments
  -Independent working and information retrieval from reference material
  -Visitors´lectures (real cases and examples from industry)

  Student's schedule and workload

  Contact days and lectures: 16 hours = 4 x 4 hours (Online working)
  There are four contact days:
  3.2 8:00 – 12:00 Online
  3.3. 8:00 – 12:00 Online
  31.3. 8:00 – 12:00 Online
  21.4 8:00 – 12:00 Online
  
  
  Independent working (individually and in groups): approx. 119 h

  Content scheduling

  -the principles and value of quality management systems
  -the main quality management standards (ISO 9001:2015)
  -the main principles of quality management in practical
  -principles of Lean
  -implementation of Lean management
  
  After completing the course, the student can
  -Define the principles and value of Quality Management Systems
  -Apply the main quality management standard in her/his own business area
  -Establish the main principles of quality management in practical
  -Understand the value of quality management to improve processes and cost effectiveness of a company
  -Apply quality management to facilitate a positive company culture and teamwork
  
  There are four contact days:
  3.2 8:00 – 12:00 Online
  3.3. 8:00 – 12:00 Online
  31.3. 8:00 – 12:00 Online
  21.4 8:00 – 12:00 Online

  Assessment criteria

  Learning assignments have not been returned.

  Assessment criteria – satisfactory (1-2)

  The learning assignments have been completed according the instructions, but the content is limited in scope.

  Assessment criteria – good (3-4)

  The assignments have been completed in accordance with the instructions and the returned documents are good in content and scope. The source material has been utilized in the preparation of learning tasks.

  Assessment criteria – excellent (5)

  The learning assignments are excellent in quality and scope. They show a deep familiarity with the source materials as well as the ability to apply the learning things in an appropriate way.
  The student has been actively looking for information, new solutions and perspectives.

•   Quality Tools MS00BW99-3002 13.09.2022-16.12.2022  5 credits  (YIQMS22V) +-
  Competence objectives of study unit

  After completing the course, the student is able to
  - define the main quality tools
  - choose a suitable software or programming environment for statistical analysis and use it.
  - do variance analysis, ANOVA
  - represent 2D and 3D data graphically
  - make non-linear fits and surface fits and use these to analyze data
  - do statistical Design of Experiments (DoE)

  Content of study unit

  -Cause-and-effect diagram
  -Check sheet
  -Control chart
  -Pareto chart
  -Stratification
  -Nonlinear curve fitting and surface fitting
  -Measurement errors
  -Analysis of variance, ANOVA
  -Design of Experiment, One factor at a time, Factorial Design, Response surface method
  -Evaluation of measurement processes

  ---

  Teacher(s) in charge

  Patric Granholm

  Sari Airenne

  Teachers and responsibilities

  Sari Airenne, Patric Granholm

  Mode of delivery

  Face-to-face

  Learning material

  Sarah E. Burke and Rachel T. Silvestrini. The Certified Quality Engineer Handbook. ASQ Quality Press Milwaukee, Wisconsin 2017
  Data Analysis and Design of Experiment:
  Michael H. Herzog, Gregory Francis, Aaron Clarke. Understanding Statistics and Experimental Design - How to Not Lie with Statistics. Springer Open. 2019 ISBN 978-3-030-03498-6 ISBN 978-3-030-03499-3 (eBook) https://doi.org/10.1007/978-3-030-03499-3
  Franz Kronthaler, Silke Zöllner. Data Analysis with RStudio - An Easy going Introduction. Springer Spectrum and R Studio. 2021 ISBN 978-3-662-62517-0 ISBN 978-3-662-62518-7 (eBook) https://doi.org/10.1007/978-3-662-62518-7.
  Amitava Mitra, Fundamentals of quality control and improvement, 4th ed. John Wiley & Sons, Inc., Hoboken, New Jersey. 2016. ISBN 978-1-118-70514-8 (cloth)

  Learning methods

  - On-line videos and lectures
  - Independent exercises, quizzes
  - Group assignments
  - Individual assignments

  Objects, timing and methods of assessment

  Assessment will be based on the individual and group assignments submitted in the itslearning course platform.

  Teaching language

  English

  Timing

  13.09.2022 - 16.12.2022

  Enrollment date range

  01.06.2022 - 14.10.2022

  • 5 credits

  Group(s)

  • YIQMS22V

  Responsible unit

  Engineering and Business

  Degree Programme(s)

  Master of Engineering, Industrial Quality Management

  Assessment scale

  H-5

  Pedagogic approaches

  - Team-based learning in student groups and presentations (substance and communication skills)
  - Individual assignments
  - Independent working and information retrieval from reference material

  Student's schedule and workload

  Contact days and lectures: 16 hours (Online working)
  
  -Group work and assignments
  -Individual work and assignments

  Content scheduling

  - Define the main quality tools
  - Establish the quality tools for continuous improvement and problem-solving
  - Evaluate critically the applying of quality tools in practice
  - Nonlinear curve fitting and surface fitting
  - Measurement errors
  - Analysis of variance, ANOVA
  - Design of Experiment, One factor at a time, Factorial Design, Response surface method
  - Evaluation of measurement processes
  
  Online days: 30.9.2022 , 28.10.2022, 3.11.2022, 10.11.2022, 24.11.2022 and 2.12.2022
  Online lectures: 16 hours together (2 or 4 hours / day)

  Assessment criteria

  Basic learning outcomes are not met.
  Assignments are not returned or the quality is poor or incorrect.

  Assessment criteria – satisfactory (1-2)

  Assignments partly returned and the quality is weak.

  Assessment criteria – good (3-4)

  Assignments are returned and the quality is good.

  Assessment criteria – excellent (5)

  All assignments are returned and correctly solved. Solution are correctness are verified and critically evaluated.

•   Research and Development Methods MS00BW98-3002 01.09.2022-31.12.2022  5 credits  (YIQMS22V) +-
  Competence objectives of study unit

  After passing the course the student is able to:
  · search and utilize scientific literature
  · identify and describe the main research and development approaches and analysis methods
  · choose and apply an appropriate methodology for his/her work
  - choose a suitable software or programming environment for statistical analysis.
  - use the basic functionality of the chosen environment.
  - be aware of differences in data file formats and is able to open files for reading and writing.
  - perform basic data cleansing e.g. to treat outliers and missing data.
  - know the difference between data types.
  - do basic sampling descriptive statistics
  - graphically represent data.
  - make linear fits and linear regression analysis.
  - do statistical tests, Z-test, F-test and Student’s t-test

  Content of study unit

  Basics of research
  Qualitative and quantitative research methods
  Start of the Master´s Thesis project

  ---

  Teacher(s) in charge

  Ulla Seppälä-Kaven

  Patric Granholm

  Sari Airenne

  Teachers and responsibilities

  Patric Granholm
  Ulla Seppälä-Kavén

  Mode of delivery

  Distance learning

  Learning material

  Qualitative research methods:
  Eriksson, P. & Kovalainen, A. 2008.Qualitative Methods in Business Research. London: SAGE Publications Ltd.
  Klenke, K., Martin, S. and Wallace, J.R. 2016. Qualitative Research in the Study of Leadership: Second Edition. Bingley: Emerald.
  Auerbach, C. & Silverstein, L.B. 2003. Qualitative Data : An Introduction to Coding and Analysis. New York: New York Univesity Press. ProQuest Ebook Central.
  Dey, I. 2005. Qualitative Data Analysis: a user-friendly guide for social scientists. London: Taylor & Francis.
  Ouantitative methods:
  Michael H. Herzog, Gregory Francis, Aaron Clarke. Understanding Statistics and Experimental Design - How to Not Lie with Statistics. Springer Open. 2019 ISBN 978-3-030-03498-6 ISBN 978-3-030-03499-3 (eBook) https://doi.org/10.1007/978-3-030-03499-3
  Sarah E. Burke and Rachel T. Silvestrini. The Certified Quality Engineer Handbook. ASQ Quality Press
  Milwaukee, Wisconsin 2017
  Franz Kronthaler, Silke Zöllner. Data Analysis with RStudio - An Easy going Introduction. Springer Spectrum and R Studio. 2021 ISBN 978-3-662-62517-0 ISBN 978-3-662-62518-7 (eBook) https://doi.org/10.1007/978-3-662-62518-7.

  Learning methods

  Qualitative research methods:
  - individual and team work
  - self- and peer-assessments
  - discussions
  - presentations
  Quantitative methods:
  - Individual and team work
  - Exercises
  - Presentations

  Objects, timing and methods of assessment

  Quantitative methods:
  - Individual and group assignments
  - Online exams and quick tests
  Qualitative methods:
  - Individual and group assignments

  Teaching language

  English

  Timing

  01.09.2022 - 31.12.2022

  Enrollment date range

  01.08.2022 - 02.09.2022

  • 5 credits

  Group(s)

  • YIQMS22V

  Seats

  5 - 35

  Responsible unit

  Engineering and Business

  Degree Programme(s)

  Master of Engineering, Industrial Quality Management

  RDI share

  3 credits

  Share of online studies

  5 credits

  Assessment scale

  H-5

  Pedagogic approaches

  Qualitative research methods:
  - individual and team assignments
  Quantitative methods:
  - individual and team assignments

  Student's schedule and workload

  Qualitative research methods:
  4 x 2 h online meetings + independent work individually and in groups
  research and analysis methods and tools - exercises
  Quantitative methods:
  4 x 2 h online meetings + independent work and exercises
  
  + Thesis seminars: presentations of thesis plans and acting as opponents

  Content scheduling

  Qualitative Research:
  Content:
  - different types of approaches and research principles
  - qualitative research and analysis methods: interviews, benchmarking, questionnaires with open questions, workshops / brainstorming, content analysis with coding
  - quality issues and ethics in the research, data management, IPR and GDPR
  - literature search, evaluation and use of the appropriate research methods for projects and master's thesis
  Ouantitative methods:
  -Basics of Probability Theory
  -Basics of Experiment Design
  -Data file formats and file reading.
  -Data cleansing, outliers and missing data
  -Graphical representation of data.
  -Curve fitting and linear regression
  -Sampling and descriptive statistics
  -Statistical tests, Z-test, F-test and Student’s t-test
  
  Master's Thesis plan and opposing - presentations 8.12.2022 8.00-16.00

  Assessment criteria

  - Quantity: Assignments are not completed to an acceptable level and or not returned assignments - instructions have not been followed
  - Quality: The minimum learning objectives are not met

  Assessment criteria – satisfactory (1-2)

  Communication and reflection are acceptable - assignments partly done according to the instructions

  Assessment criteria – good (3-4)

  Communication and reflection are good - assignments done according to the instructions

  Assessment criteria – excellent (5)

  Outstanding communication, reflection and application - assignments done according to the instructions and returned on time -by the deadline

Academic year 2023 - 2024

There is no implementations attached to this degree programme.