Production planning and control

Academic Year 2026/2027 - Teacher: ANTONIO COSTA

Expected Learning Outcomes

The course aims to teach production programming methods, with particular reference to short- and medium-term planning.

Knowledge and understanding

Upon completion of the course, the student will acquire knowledge and understanding of short- and medium-term production planning problems, as well as advanced topics regarding solution methodologies, supported by the teaching material provided by the instructor and the recommended textbooks. Specifically, the knowledge and understanding will cover the following topics:

- International nomenclature and notation for defining scheduling problems;

- Basic elements of complexity theory;

- Industrial production system layouts;

- Heuristic methods for solving scheduling problems;

- Local search and evolutionary algorithms;

- Mathematical models of production systems;

- Assembly system balancing methods;

- Sequencing methods for mixed-model assembly lines;

Ability to apply knowledge and understanding

By the end of the course, the student will be able to apply the aforementioned knowledge and understanding in a professional manner, thanks to the numerous industrial case studies introduced by the instructor and solved during the course. The student will possess the skills necessary to understand production system layout types and identify process constraints, as well as to select, design, and develop solution methods appropriate to the nature and complexity of the problem. More specifically, the student will be able to:

- Match the ideal layout model to the actual production system under study.

- Mathematically model the dynamics of real production systems.

- Validate the mathematical simulation model of the production system.

- Develop and implement solution methods for the planning problem at hand.

- Validate the best solution method for the specific planning problem.

The skills acquired can be applied to quality management in organizations in the civil, industrial, and service sectors, in accordance with Goals 9, 11, and 12 of the United Nations 2030 Agenda for Sustainable Development.

Course Structure

- Frontal lessons

- Practical applications

Required Prerequisites

- Basic knowledge concerning MS Excel and programming languages

- Matlab editing

- Development and implementation of Mathematical programming models

Attendance of Lessons

Frequency is mandatory

Detailed Course Content

Introduction to scheduling. Scheduling theory. Single machine problem: problems with no due dates, problems with due dates. Optimization methods for the single machine scheduling problem. heuristic methods for the single machine problem. Earliness and tardiness costs. Mathematical programming models for the single machine problem. Stocastic scheduling problem. Extensions of the single machine basic problem. Parallel machines scheduling problem. Flow shop scheduling. Flowshop stochastic scheduling problem. Classification of assembly lines manufacturing systems. Single model assembly lines. Mixed-model assembly lines. Sequencing in assembly lines. VBA based procedures for evaluative and generative methods.

Textbook Information

1	Production Scheduling and heuristic optimization	Principles of Sequencing and scheduling, K. R. Baker and D. Trietsch, Wiley, New Jersey, 2009, ISBN 978-0-470-39165-5.
2	Medium- and short-term production planning	Balancing and sequencing of assembly lines, A. Scholl, Physica-Verlag, 1999, ISBN 3-7908-1180-7.

Course Planning

	Subjects	Text References
1	Production scheduling	1
2	Blanacing and sequencing assembly lines	2

Learning Assessment

Learning Assessment Procedures

Students whose course attendance is higher than a certain threshold will be allowed applying a preliminary exam, at the end of the course. During the course, a series of practical applications will be executed and the students will be invited to develop and solve a specific project work inspired to a real-world case study. Whether a student passes the final exam mentioned above, he/she can discuss his/her project work at the earliest session to improve the score obtained so far. Despite the preliminary exam, only written exams will be carried out and the project work discussion is not mandatory. However, a maximum score equal to 28/30 can be reached if the student refuses to develop the project work.

To guarantee equal opportunities and in compliance with current laws, the Interested students can request a personal interview in order to schedule any compensatory and/or dispensatory measures, based on educational objectives and specific needs. It is also possible to contact the CInAP reference teacher (Centre for Active Integration and Participated - Services for Disabilities and/or DSA) of your Department.

Examples of frequently asked questions and / or exercises

- Defining the difference between exhaustive and heuristic methods, also through a series of practical examples.

- Drawing the simulated annealing algorithms flow chart

- What is a "feasible line balance" in a single model assembly line?

Degree Course in

Management Engineering