PRODUCTION SCHEDULING

Course Description

Students in this course will learn fundamental problem areas of production planning and control and, the relation between planning and control activities. To Discuss practical uses and consequences of the methods under study. Two sequel courses are designed together to provide the basics of production planning and control with the need of modern manufacturing organizations in mind. The topics covered in the first course are production and operations strategy, subjective and objective forecasting (i.e. Delphi method, trend-based methods, and methods for seasonal series), deterministic inventory planning and control (i.e. Economic Order Quantity model and its extensions to several environments), stochastic inventory planning and control, aggregate production planning, and master production scheduling.

PRODUCTION SCHEDULING

Evaluation Tools (Active Term)

No evaluation items have been defined.

Course outcomes

1. 01 Identify the methods and techniques that are available for building scheduling systems
2. 02 Recognize several scheduling algorithms and tell when each algorithm is appropriate
3. 03 Analyze and ilustrate how several scheduling algorithms work to solve problems
4. 04 Model network problems and solve them using specialized algorithms

Course Syllabus

Reference Books & Course Materials

1. 01 D.R. Sule, Industrial Scheduling, PWS Publishing Company, 1997.
2. 02 M. Pinedo, Scheduling Theory, Algorithms and Systems, Prentice Hall, 1995.
3. 03 Sipper, D., and Bulfin R.L., Production: Planning, Control, and Integration, McGram-Hill,1997, ISBN: 0-07-057682-3.
4. 04 Winston, W.L., Operations Research Application and Algorithms, 3rd edition, Duxbury,1994.

Learning Outcomes

1. L01 Identify the methods and techniques that are available for building scheduling systems
2. L02 Recognize several scheduling algorithms and tell when each algorithm is appropriate
3. L03 Analyze and ilustrate how several scheduling algorithms work to solve problems
4. L04 Model network problems and solve them using specialized algorithms

Program Outcomes

1. P01 Knowledge of mathematics, natural sciences, basic engineering, computer-based computation, and topics specific to the relevant engineering discipline.
2. P02 Ability to apply knowledge of mathematics, natural sciences, basic engineering, computer-based computation, and topics specific to the relevant engineering discipline to the solution of complex engineering problems.
3. P03 Ability to define complex engineering problems by using knowledge of basic sciences, mathematics, and engineering, while considering the relevant United Nations Sustainable Development Goals (SDGs) related to the problem addressed.
4. P04 Ability to formulate complex engineering problems using knowledge of basic sciences, mathematics, and engineering, while considering the relevant United Nations Sustainable Development Goals (SDGs) associated with the problem addressed.
5. P05 Ability to analyse and solve complex engineering problems using knowledge of basic sciences, mathematics, and engineering, while considering the relevant United Nations Sustainable Development Goals (SDGs) associated with the problem addressed.
6. P06 Ability to design creative solutions to complex engineering problems.
7. P07 Ability to design complex systems, processes, devices, or products in a way that meets present and future needs while considering realistic constraints and conditions.
8. P08 Ability to select and use appropriate techniques and resources—including estimation and modelling—for the analysis and solution of complex engineering problems, while being aware of their limitations.
9. P09 Ability to select and use modern engineering and computational tools—including estimation and modelling—for the analysis and solution of complex engineering problems, while being aware of their limitations.
10. P10 Ability to conduct literature research and use appropriate research methods for the investigation of complex engineering problems.
11. P11 Ability to design experiments for the investigation of complex engineering problems.
12. P12 Ability to conduct experiments, collect data, analyse results, and interpret findings for the investigation of complex engineering problems.
13. P13 Knowledge of the impacts of engineering practices on society, health and safety, the economy, sustainability, and the environment within the framework of the United Nations Sustainable Development Goals (SDGs).
14. P14 Awareness of the legal implications of engineering solutions within the framework of the United Nations Sustainable Development Goals (SDGs).
15. P15 Knowledge of ethical responsibility and adherence to the principles of professional engineering conduct.
16. P16 Awareness of acting impartially without discrimination in any matter and of being inclusive of diversity.
17. P17 Ability to work effectively as an individual.
18. P18 Ability to work effectively as a team member or leader in intra-disciplinary teams (face-to-face, remote, or hybrid).
19. P19 Ability to work effectively as a team member or leader in multidisciplinary teams (face-to-face, remote, or hybrid).
20. P20 Ability to communicate effectively in spoken form on technical matters, taking into account the diverse characteristics of the target audience (such as education, language, and profession).
21. P21 Ability to communicate effectively in written form on technical matters, taking into account the diverse characteristics of the target audience (such as education, language, and profession).
22. P22 Knowledge of professional practices such as project management and economic feasibility analysis.
23. P23 Awareness of entrepreneurship and innovation.
24. P24 Ability for independent and lifelong learning.
25. P25 Ability to adapt to new and emerging technologies.
26. P26 Lifelong learning ability that includes the capacity to think critically about technological changes.

Po-Lo Matrix