Topic outline

  • General

    Not available unless: You are a(n) Student

    The exam on Tuesday 22.2.2022 13:00-16:00 will take place in ME Department building (K1, Otakaari 4) in class rooms 213, 216, 326 and 202. The building entrance is open, but the class rooms may be locked. Wait outside or inside keeping distances. The places are indicated with exam papers and empty answer papers when you enter the room. Do not turn the exam paper before the exam starts. It will only start after everybody is in place.


    The course will start  8:15 on Tuesday the 11th of January 2022 in Teams.

    You should receive a Teams code by email before the first lecture, provided that you have signed-up in Sisu.

    Lectures are given in Teams on Tuesdays 8.15 - 9.45 and on Thursdays 14.15 - 15.45 during period III.

    Computer classes take place in Teams (remotely and in Maari-C) 14:15-16:00 on Fridays 21.1. (Optimization / Excel Solver), 28.1. (Data fitting) and 4.2. (Optimization / CPLEX)

    Four project assignments are done in groups of 2 students. Pair formation is free: find a friend, work together and submit one report for each project assignment with the names of both members of the group on it. You can find your group (and data) number beside your study book number in the first assignment data file. For a group of two students, select the first in the list. If you wish, you may do the assignments alone.

    Assignment report dead lines are two weeks from computer classes or relevant lecture at noon: 1)  Optimization/Factory location 4.2., 2) Data fitting 11.2., 3) Optimization/Flow shop 26.2., 4) Optimization/Aggregate planning 4.3. - Submission in MyCourses.

    Literature

    The following are listed in Oodi:

    - 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.

    In addition:

    - In Aalto library e-books / Knovel you can find Operations Research /  Yadav, S.R.; Malik, A.K. (2014). This covers optimization and queuing theory, but since it is a text book, presented differently form lectures and lecture material.

    - Matlab Neural Network Toolbox help contains a thorough introduction to neural networks.

    - Any statistics textbook covers linear regression modeling.

    Grading of Course

    • Based on total points: maximum 40 p. for assignments + 20 p. for examination = 60 p


    Grading of assignments

    • Based on report; see separate instruction
    • Same general criteria as is used for any other report (see e.g. School of Engineering ”Master’s thesis guidelines”) is applied
    • Scale 1 – 10 p / assignment:
    • 1-2 points: you have done some modeling and experimentation, but your models are seriously wrong and your experimentation is rubbish.
    • 3-4 points: you have done the modeling and experimentation, but there are deficiencies and/or analysis is not adequate
    • 5-6 points: experimentation is well designed and analysis and conclusions are covering and correct
    • 7-8 points: extra problems are answered in addition to basic problem.
    • 9-10 points: All basic and extra modeling, experimentation, analysis and conclusions are complete and correct. Report is logical, well organized and easy to read.
    In your analysis, explain what you get as your results and try to explain why the system and results behave as they do. Make academic and/or practical conclusions.

    Remember to include your results and model file in the submission!

    Grading of examination
    • There will be four questions, each 0 - 5 p. => max. points 20