Production management

Summary

Production management deals with producing goods sustainably at the right time, quantity, and quality with the minimum cost. This course equips students with practical skills and tools for effectively managing demand, supply, and implementing advanced analytics in manufacturing companies.

Content

Keywords

Demand management, Supply management, Forecasting, Inventory management, Production planning, Simulation, Supply Chain Analytics.

Learning Prerequisites

Required courses

• Probability and Statistics

Recommended courses

• Continuous Improvement of Manufacturing Systems
• Supply Chain Management
• Data Science for Business

Important concepts to start the course

• Data analysis using Excel
• Active engagement and teamwork
• Advanced level of probability and statistics

Learning Outcomes

By the end of the course, the student must be able to:

• Choose production tools and methods based on performance and cost requirements and needs, taking into consideration applicability limits and associated hypotheses, CP8
• Model , analyse and optimize the internal logistics of a production and distribution system and the dynamic behaviour of a network of companies, CP9
• Design a system based on engineering specifications utilizing suitable numerical and analytical tools for optimizing the design parameters, CP10
• a system based on engineering specifications utilizing suitable numerical and analytical tools for optimizing the design parameters, CP10
• , analyse and optimize the internal logistics of a production and distribution system and the dynamic behaviour of a network of companies, CP9
• production tools and methods based on performance and cost requirements and needs, taking into consideration applicability limits and associated hypotheses, CP8

Transversal skills

• Assess progress against the plan, and adapt the plan as appropriate.
• Communicate effectively, being understood, including across different languages and cultures.
• Manage priorities.
• Negotiate effectively within the group.
• Evaluate one's own performance in the team, receive and respond appropriately to feedback.
• Demonstrate the capacity for critical thinking
• Write a scientific or technical report.
• Take feedback (critique) and respond in an appropriate manner.
• Take account of the social and human dimensions of the engineering profession.
• Take responsibility for environmental impacts of her/ his actions and decisions.
• Resolve conflicts in ways that are productive for the task and the people concerned.
• Use both general and domain specific IT resources and tools

Teaching methods

• Formal lectures
• Group activities
• Class discussions
• Hands-on exercises
• Project-based learning
• Games and simulations
• Guest lectures by leading academic and industry figuers

Expected student activities

• Individual: Self-study, Active class discussions, case evaluations, Q&A
• In-group: Teamwork (respect, brainstorming, involvement and constructive feedback)
• Presentation: Share your findings weekly in class/group coaching sessions

Assessment methods

Continuous evaluation of case reports, projects, individual and group presentations, class discussions, during the semester. More precisely:

• 25% Participation, and class engagement,
• 45% Class assignments, presentations, projects, and case reports,
• 30% Final (Final report and presentation and understanding of the case)

Supervision

Resources

Virtual desktop infrastructure (VDI)

Yes

Bibliography

Series of book chapters, hand-outs, and notes will be shared in the class. The following books are recommended for further reading (and not mandatory);

1. Yoo, M. J., & Glardon, R. (2018). Manufacturing Operations Management.
2. Jacobs, F. R., Berry, W. L., Whybark, D. C., & Vollmann, T. E. (2011). Manufacturing planning and control for supply chain management: APICS/CPIM Certification Edition. McGraw-Hill Education.
3. Stevenson, W. J. (2020). Operations management. McGraw Hill.
4. Slack, N., Chambers, S., & Johnston, R. (2016). Operations management. Pearson education.
5. Chase, C. W. (2013). Demand-driven forecasting: a structured approach to forecasting. John Wiley & Sons.
6. Chase, C. W. (2016). Next generation demand management: People, process, analytics, and technology. John Wiley & Sons.
7. Sterman, J. (2010). Business dynamics. Irwin/McGraw-Hill c2000.
8. Provost, F., & Fawcett, T. (2013). Data Science for Business: What you need to know about data mining and data-analytic thinking. " O'Reilly Media, Inc.".
9. Kahneman, D. (2011). Thinking, fast and slow. Macmillan.
10. Kahneman, D., Sibony, O., & Sunstein, C. R. (2021). Noise: A flaw in human judgment. Little, Brown.
11. Taleb, N. N. (2007). The black swan: The impact of the highly improbable (Vol. 2). Random house.
    
12. Silver, N. (2012). The signal and the noise: Why so many predictions fail-but some don't. Penguin.
13. Porter, M. E., & Heppelmann, J. E. (2014). How smart, connected products are transforming competition. Harvard business review, 92(11), 64-88.
14. Porter, M. E., & Heppelmann, J. E. (2015). How smart, connected products are transforming companies. Harvard business review, 93(10), 96-114.
15. Agrawal, A., Gans, J., & Goldfarb, A. (2018). Prediction machines: the simple economics of artificial intelligence. Harvard Business Press.
16. Gupta, S. (2018). Driving digital strategy: A guide to reimagining your business. Harvard Business Press.Chicago
17. Iansiti, M., & Lakhani, K. R. (2020). Competing in the age of AI: strategy and leadership when algorithms and networks run the world. Harvard Business Press.

Ressources en bibliothèque

• Manufacturing operations management / Yoo
• Manufacturing Planning and Control for Supply Chain Management / Vollman
• Operations Management / Stevenson
• Operations Management / Slack
• Demand-Driven Forecasting / Chase
• Next generation demand management / Chase
• Business dynamics / Sterman
• Data science for business / Provost
• Thinking Fast and Slow / Kahneman
• Noise / Kahneman
• The Black Swan / Taleb
• Driving Digital Strategy / Gupta
• How smart, connected products are transforming companies / Porter
• How smart, connected products are transforming competition / Porter
• Prediction machines / Agrawal
• Competing in the Age of AI / Iansiti
• The signal and the noise / Silver

Notes/Handbook

• Course slides (main material)
• Videos
• Hand-outs during the semester

Moodle Link

• https://go.epfl.ch/ME-419