Course 4: Quality Management for Extended Enterprise
Syllabus: Course 4_ Quality Management for Extended Enterprise
Last Update: February 1, 2020
Course Objective: The extended enterprise concept has been adopted to collaborate in the entire supply chain. Quality and efficiency issues, therefore, extend well beyond the traditional enterprise. This course constructs student competencies of management skills, particularly on how to define, develop, implement and manage the strategy to improve and build the quality system to align with the digital domains. Students will be trained on the modern quality management methods used in product design, product development ,and production planning, as well as, the quality management methods focused on statistical quality control methods and data analytics, under the context of the extended enterprise. This course will also develop a technical skill for students to implement quality control and monitoring system that covers both process operation and supply chain operations
Learning Outcomes: The students on the completion of this course would be able to:
- Understand the impact of digitalization on quality management system, particularly on processes and people.
- Identify the strategy to assess the need and define the suitable technologies in order to transform the production system and organization, quality culture and processes to maximize value
- Analyze operational quality-related data for sustaining the process and Enterprise as well as identify the improvement by using quality monitoring tools such as SPC and modern data analytic technique and be able to embed quality management principles and tools in the value chain of operations and integrate with business operation strategy.
- Design a data visualization platform and Create its system components based on operational data such as quality and productivity output characteristics as well as Enterprise data (Enterprise Quality Metrics visualization).
- Design the proper quality management system for smart factories that can integrate the production and quality operations under the digital quality management concept
Prerequisite: None
Course Outline:
| Week | Topic | Workshop | Learning Materials | Teaching Materials | Note |
| 1 | Quality Management Concept under the Digital Era | MSIE-04-L-M1S1-TH | |||
| 2 | Organization Performances and Quality System Strategy for I4.0 | MSIE-04-L-M1S2-TH | |||
| 3 | Quality Strategy for Digital Quality Management System | MSIE-04-L-M1S3-TH | |||
| 4 | Quality System Structures for I4.0 | MSIE-04-L-M1S4-TH | |||
| 5 | Quality Control Concept under Digital Data Collection | MSIE-04-L-M2S1-01_TH | |||
| 6 | Automated SPC Strategy | MSIE-04-L-M2S2-TH | |||
| 7 | Multivariate SPC Strategy | MSIE-04-L-M2S3_TH | |||
| 8 | Data Analytic for Quality Monitoring | MSIE-04-L-M2S4_TH | |||
| 9 | Automated Quality Report Concept | MSIE-04-L-M3S1-TH | |||
| 10 | Strategic Quality Improvement under I4.0 | MSIE-04-L-M3S2-TH | |||
| 11 | Real-Time Quality Control | MSIE-04-L-M3S3-TH | |||
| 12 | Quality System Transformation | MSIE-04-L-M3S4-TH |
Laboratory Sessions: None
Learning Resources:
Textbooks: No designated textbook, but class notes and handouts will be provided.
Reference Books:
- Juran’s Quality Handbook: The Complete Guide to Performance Excellence
- Montgomery, Douglas C. Introduction to statistical quality control. John Wiley & Sons, 2012.
- Luis Rocha-Lona, Jose A. Garza-Reyes, and Vikas Kumar. Building Quality Management Systems. CRC Press, 2013
- J.D.T. Tannock. Automating Quality Systems. Chapman & Hall, 1992.
Journals and Magazines:
- Germany Trade & Invest, “Smart manufacturing for the future,” http://www.gtai.de/GTAI/Content/EN/Invest/_SharedDocs/Downloads/GTAI/Brochures/Industries/industrie4.0-smart-manufacturing-for-the-future-en.pdf; National Academy of Science and Engineering, “Securing the future of German manufacturing industry: Recommendations for implementing the strategic initiative of Industry 4.0
- Forces of change: Industry 4.0
- A Deloitte series on Industry 4.0
- Case study: FANUC, the Japanese robotics company, https://www.cbinsights.com/research/future-factory-manufacturing-tech-trends/#quality
- 8 different steps of the manufacturing process to Future Factory, https://www.cbinsights.com/research/future-factory-manufacturing-tech-trends/#quality
- Nikon Strategic Focus on Quality 4.0, https://metrology.news/nikon-strategic-focus-on-quality-4-0/
- A strategist’s guide to Industry 4.0, https://www.strategy-business.com/article/A-Strategists-Guide-to-Industry-4.0?gko=a2260
- Suggested Indicators to Measure the Impact of Industry 4.0 on Total Quality Management, International Scientific Conference on Industry 4.0, At 3-16. DECEMBER 2017, BOROVETS, BULGARIA
- Developing a Kano-Based Evaluation Model for Innovation Design, Mathematical Problems in Engineering 2015(2):1-8 · October 2015
- The Complete Guide to the Kano Model: Prioritizing Customer Satisfaction and Delight https://foldingburritos.com/kano-model/
- Perdikis, Theodoros, and Stelios Psarakis. “A survey on multivariate adaptive control charts: Recent developments and extensions.” Quality and Reliability Engineering International 35.5 (2019): 1342-1362.
- Mason, Robert L., and John C. Young. Multivariate statistical process control with industrial applications. Vol. 9. Siam, 2002.
Teaching and Learning Methods:
This is an activity-based course. During lecture sessions, class discussion will be conducted. During workshop sessions, the students, to be active learners, will practice several skills including, but not limited to, decision making, problem-solving, critical thinking, written communication, oral communication, presentation, debate, and teamwork.
Time Distribution and Study Load:
Lectures: 45 hours
Workshop: 60 hours
Self-study: 45 hours
Evaluation Scheme:
The final grade will be computed according to the following weight distribution:
Assessment (CLO1): (20%)
- LogBook/Journal + Cases Study (5%)
- Oral Presentation (Individual Work Presentation & Report) (5%)
- Open Exam (10%)
Assessment (CLO2): 20%
- Role Play + Cases Study (5%)
- Extended Response Question (5%)
- Report of Strategy Plan and Analysis (10%)
Assessment (CLO3): (30%)
- Professional Discussion (5%)
- Cases Study +Simulation (10%)
- Assignment (15%)
Assessment (CLOs 4&5): (30%)
- Project (20%)
- Oral Presentation (5%)
- Oral Question (5%)
An “A” would be awarded if a student can design the proper quality management system for smart factories.
A “B” would be awarded if a student can evaluate the proper quality management system for smart factories.
A “C” would be given if a student can analyze the proper quality management system for smart factories.
A “D” would be given if a student can only remember some criteria for designing the proper quality management system for smart factories.
Developer: Wichai Chattinnawat (CMU), Suriya Jirasatitsin (PSU), Anintaya Khamkanya (TU)