Översikt

  • General

    Tillgänglig om: Fältet E-postadress innehåller @aalto.fi
    The course will start  8:15 on Tuesday the 10th of January 2023 in U351.

    Lectures are given on Tuesdays 8.15 - 9.45 in Otakaari 1/U351 and on Thursdays 14.15 - 15.45 in Otakaari 4/ K1/215 during period III. There is no lecture on 7.2. On Thursday 9.2. 14:15, we will have Mr. Raimo Puro, CEO of Delfoi Ltd., delfoi.fi, giving a lecture on the Delfoi Planner MES/MRP software.

    Computer classes take place in Maari-C 14:15-16:00 on Fridays 20.1. (Optimization / Excel Solver), 27.1. (Data fitting) and 3.2. (Optimization / CPLEX).

    Four project assignments are done in groups of 3 students. Group formation is free: find friends, work together and submit one report for each project assignment with the names of all 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 three students, select the first in the list.

    Assignment report dead lines are two weeks from computer classes or relevant lecture at noon: 1)  Optimization/Factory location 3.2., 2) Data fitting 10.2., 3) Optimization/Flow shop 17.2., 4) Optimization/Aggregate planning 3.3. - Submission in MyCourses. Attach your model and results files in the submission.

    Literature

    The following are listed in SISU:

    - 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

    Exams

    • According to SISU, we have exams on 21.2.2023 and 20.4.2023

    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. You do not provide complete results and you have not attached your model file(s) to the submission.
    • 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