MEC-E7001 - Production Systems Modelling D, Lecture, 11.1.2022-22.2.2022

Guest access
Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

After the course the student:

  1. Knows the basics of manufacturing systems and process modelling using queuing theoretical, mathematical programming (optimization), and data modelling (linear regression, neural networks) approaches.
  2. Knows basic concepts of production planning and control and is familiar with the practical approaches and more theoretical analysis methods related to them.
  3. Is able to do basic modelling of manufacturing systems, especially in the context of production planning and control, using the am. methods with the following software: Microsoft Excel Solver and OPL/CPLEX (optimization) and Matlab (data modelling).
  4. Is able to do systematic experimentation with the am. models and interpret the results.
  5. Is able to participate in an industrial scale development project that utilizes the am. methods.

Credits: 5

Schedule: 11.01.2022 - 22.02.2022

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Esko Niemi

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content

  • valid for whole curriculum period:

    The following methods are studied: queuing networks, optimization, regression analysis, and neural networks. The application of the methods to production systems planning and control: Hierarchical production planning, cost functions, Little's law, scheduling, lot sizes and set-ups, capacity planning, aggregate planning, facility location. The basics of the methods and software are learned in guided tutorials (computer classes) and exercises (assignments).

Assessment Methods and Criteria

  • valid for whole curriculum period:

    Lectures, excercises, and examination.

Workload

  • valid for whole curriculum period:

    Lectures 20 h

    Computer classes 8 h

    Group assignments 60 h

    Self study 45 h

    Examination 3 h

DETAILS

Study Material

  • valid for whole curriculum period:

    Factory physics: foundations of manufacturing management / Wallace J. Hopp, Mark L. Spearman.

    Design and analysis of lean production systems / Ronald G. Askin, Jeffrey B. Goldberg.

    Planning and scheduling in manufacturing and services / Michael L. Pinedo.

    Lecture notes.

Substitutes for Courses
Prerequisites

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Teaching Period:

    2020-2021 Spring III

    2021-2022 Spring III

    Course Homepage: https://mycourses.aalto.fi/course/search.php?search=MEC-E7001

    Registration for Courses: In the academic year 2021-2022, registration for courses will take place on Sisu (sisu.aalto.fi) instead of WebOodi.

    WebOodi.

Rules of Conduct - Students´ Rights and Responsibilities (in force from 1 August 2020)

Aalto University Code of Academic Integrity and Handling Violations Thereof