Business Process Improvement
- Credits: 10
- Ending: Examination
- Range: 16sP
- Semester: winter
- Year: 1
- Faculty of Business Economics with seat in Košice
Teachers
Included in study programs
Teaching results
The main educational goal of the course is to focus on improving processes based on exactly determined criteria, in the most general sense and reducing the variability of their parameters, in the conditions of the fourth industrial revolution, combining methods of statistical quality improvement and design of experiment procedures.
Students will acquire the following knowledge:
• in the field of identification of basic parameters of processes and their improvement;
• about the most important techniques and methods used in statistical process control and planning of experiments;
• in the field of different approaches to planning of experiments, process capabilities and their improvement.
Students will acquire the following competencies in case of successful completion of the course:
• ability to choose an appropriate method, tool, or a technique applicable to solving a specific problem;
• verify all the necessary conditions for using the specific method and select the most suitable one on the basis of the improvement criteria;
• ability to interpret and verify mentioned methods in practice.
Students will acquire the following skills in case of successful completion of the course:
• the ability to implement individual methods of business process improvement in practice;
• computational literacy at the user level in the field of SPC and DOE;
• to present achieved results accurately, concisely and in an understandable form.
Indicative content
• Process of improvement, cycles of improvement
• Process regulation, Statistical process control
• Process capability
• Introduction to Design of Experiments (DOE)
• Full and fractional factorial designs
• Screening designs
• Experimental Design and Optimization
• Response surface designs
Support literature
1. OAKLAND, John – OAKLAND, Robert. Statistical Process Control, 7th Edition. London: Routledge Taylor and Francis Group. 2019. 446 s. ISBN 978‐1‐138‐06426‐3.
2. DOTY, A. Leonard.Statistical Process Control, 2nd Edition. New York: Industrial Press Inc. 200 Madison Avenue. 1996. 400 s. ISBN – 10:0831130695.
3. BERGER, W. Roger – HART, H. Thomas. Statistical Process Control: A Guide for Implementation (Quality and Reliability Book 8) 1st Edition, Kindle Edition. 2020. ASQC – The American Society for Quality Control. Edward G. Schilling, Center for Quality and Applied Statistics, Rochester Institute of Technology, Rochester, New York. First Published 1986.80 s. ISBN 0-8247-7625-9.
4. MONTGOMERY, C. Douglas. Design and Analysis of Experiments (8thEdition). John Wiley & Sons, Inc. 111 River Street, Hoboken, New Jersey, United States. 2017. 725 s. ISBN978-1-118-14692-7.
5. ANTONY, Jiju. Design of Experiments for Engineers and Scientists, 2nd Edition. London: Elsevier Health Sciences, 2014. 221 s. ISBN 978-0-08-099417-8.
6. KRISHNAIAH, Kamatam – SHAHABUDEEN, Peer Mohamed. Applied Design of Experiments and Taguchi Methods. Kindle Edition. New Delhi: Asoke K. Ghosh, PHI Learning Private Limited, 2012. Eastern Economy Edition. 362 s. ISBN 978-81-203-4527-0.
7. ANDERSEN, Bjørn. Business Process Improvement Toolbox, 2nd Edition. Milwaukee, Wisconsin: American Society for Quality, Quality Press, 2007. 296 s. ISBN 978-0-87389-719-8.
Syllabus
• PDCA cycle, DMAIC process, DMADV methodology, IDOV methodology. Criteria and models for process improvement. • Statistical process control charts. Shewhart charts, CUSUM, EMWMA, a Hotelling control charts, Performance of control charts. • Process capability index, Taguchi capability Index. • Stages of DOE: o Planning; o Screening; o Optimization; o Robustness Testing; o Verification • Full and fractional factorial designs at 2-levels and 3-levels • Screening of designed procedures, Plackett Burman designs. • Optimization of designs using mathematical models and computation. • Box – Behnken design, Central composite design, Gradient – enhanced kriging. • Recommended software: R Studio, IBM SPSS Modeler.
Requirements to complete the course
30% - active participation in colloquia, presentation of a selected topic
30% - research study
40% - final exam
Student workload
Student’s workload (in hours): 260 hours (10 ECTS x 26 hours)
Participation in colloquia: 16 hours
Preparation for colloquia: 44 hours
Elaboration of a research study: 100 hours
Preparation for the final exam: 100 hours
Language whose command is required to complete the course
Slovak language / English language
Date of approval: 06.09.2024
Date of the latest change: 20.01.2022