UNIVERSITY OF BRIDGEPORT School of Engineering COURSE OUTLINE. TCMG 540-9T1 Simulation and Modeling

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1 UNIVERSITY OF BRIDGEPORT School of Engineering COURSE OUTLINE TCMG 540-9T1 Simulation and Modeling Semester Offered: Spring 2016 Instructor: Elif Kongar Course Number: TCMG 540 Office: 141 TECH Credit Hours: 3 SH kongar@bridgeport.edu Office Hours: Tuesday : 12:30 2:30 PM Phone: (203) Thursday : 12:30 2:30 PM Prerequisite: Basic computer skills. Course Description: The purpose of this course is to provide an in depth coverage of the use of simulation as an analysis tool for the study of production and distribution processes. The course aims to develop a sense of critical thinking, learning and problem solving. Topics include: problem formulation, data collection and analysis, random variable generation, and statistical analysis of output. Utilizes a major simulation language, SIMAN. Course Prerequisites: Basic knowledge of probability and statistics. Basic computer programming experience. General spreadsheet skills and familiarity with industrial engineering, operations research, and manufacturing systems Course Objectives: To successfully meet course requirements, students must complete the following tasks and demonstrate competencies in the following skills: To successfully meet course requirements, students must complete the following tasks and demonstrate competencies in the following skills: 1. Develop a comprehensive component model of a dynamic discrete-event system, 2. Generate a physical flow, process, or event-tracking model of a dynamic, discrete-event system, 3. Independently code, debug, compile, and run a simulation scenario, obtaining valid output, 4. Analyze output data and apply results in operational decision-making process, 5. Identify relevant practical problems as viable candidates for simulation analysis, 6. Demonstrate a comprehensive understanding of the elements and processes of simulation modeling and analysis. 1

2 Course Topics: Introduction to basic concepts of simulation modeling Systems, models and simulation Problem formulation Data collection and analysis Random variable generation Dynamic event programming Statistical analysis of output Practical interpretation of results Model verification and validation Schedule and Classroom: Tuesday: 9:45 a.m. - 12:15 p.m. MAN 218 Please note that Technology Building Laboratory Tech Lab 112 is reserved for this classroom on Tuesdays between 8 a.m. and 1 p.m. Examinations and Grading Criteria: Attendance/Assignments: 30% - Announced throughout the semester Midterm exam: 35% Final Exam (Project/Paper): 35% - To be explained in detail during the course Bonus points will be credited throughout the course. The grading is subject to change and the changes will be communicated with the students. Textbook: Simulation with Arena, by Required Reading: W. David Kelton, University of Cincinnati Randall P. Sadowski, Rockwell Software David T. Sturrock, Rockwell Software, 6 th Edition McGraw-Hill, ISBN-10: , ISBN-13: (Both 5 th or 6 th Editions are accepted) 1. Perry, R.F., Kim, J., & Jaeger, B.K. Class Packets for Digital Simulation, N.U. Reprographics, Additional handouts may be providing during the semester. Recommended (Optional) Reading: 1. Introduction to Operations Research, 8/e, by Frederick S Hillier, Stanford University and Gerald J Lieberman, Stanford University, ISBN: Operations Research: An Introduction by Taha, ISBN: Probability and Statistics for Engineers and Scientists Sixth Edition by Walpole, Myers and Myers, 1998, ISBN: An Introduction to Management Science by Anderson, Sweeney and Williams. ISBN:

3 Software: This course will use a special purpose programming languages (SIMAN) throughout the course. SIMAN/ARENA software is available in the UB lab. Canvas usage is essential for the successful completion of the course. Policies: Late homework / project assignment submission will not be accepted. Three or more unexcused absences will result in an automatic failure. Make-up exams / quizzes will not be allowed (except for prior instructor approval for a documented emergency) Homework assignments and programs are due within a week from the assignment date, unless the instructor notes otherwise. All homework assignments are to be typed. Programs are to be submitted with all I/O files and source code hardcopies. Extra credit quizzes, assignments, and programs (if any) will be announced by the instructor. It is the student's responsibility to familiarize himself or herself with and adhere to the standards set forth in the policies on cheating and plagiarism as defined in Chapters 2 and 5 of the Key to UB or the appropriate graduate program handbook. As a UB policy, it is expected that each student that attends one hour of classroom instruction will require a minimum of two hours of out of class student work each week for approximately fifteen weeks for one semester. Assignment Submission Guidelines 1. Computer-type your assignments (preferably MS-Word format). 2. Save your file with a proper filename format: e.g: If the student name is Elif Kongar, student ID# , Homework Assignment 1; the filename should be: TCMG540_Elif_Kongar_ _HW1. 3. Login to myub and click on the Canvas link under Library & Technology Resources. Use the first part of your UB as username (for example: jbond, without and follow the instructions to set up your password. 4. Sign in to your UB Canvas account and then into the course, e.g. Statistical Simulation and Modeling to submit your assignments. To access Canvas tutorial for faculty: UB Canvas account can also be accessed through the URL: 3

4 Important Dates Classes Begin Monday, 1/19 Spring Break No Classes Sunday, 3/13 3/20 Midterm Exam Tuesday, 3/22 Final Exam Tuesday, 4/26 Last Day of Classes Friday, 4/29 Final Grades Due Monday, 5/9 Grading scale Letter Grade Percentage A % A % B % B % B % C % C % C % D % D % D % F Below 60% 4

5 Weekly Schedule (1/19/16 5/3/16) Please note that the class notes and Handouts are updated every week Week Date Topic 1 1/19 Syllabus Introduction to the Class 2 1/26 Basic Definitions and Terminology Flowchart Quality of conformance Control Charts for Variables and Attributes History of Quality Improvement Statistical Methods for Quality Improvement Assignment 1 3 2/2 Fundamental Simulation Concepts Decompose the problem Terminology Simulation by hand Some basic statistical issues Overview of a simulation study Assignment 1 is due Assignment 2 4 2/9 Arena Load, explore, run an existing model Construct the same model from scratch Tour menus, toolbars, drawing, printing Help system Options for running and control 5 2/16 Modeling approaches New Arena modules (Decide, Record) Resource Schedules, States, and Failures Frequency outputs More on utilizations Queues, Entity Pictures, Resource Pictures Adding Plots and Variables Assignment 2 is due Assignment 3 6 2/23 Guest Lecturer (may include additional lecture instead) Assignment 3 is due 7 3/1 Enhancing the Animation Fitting Distributions to Data with the Arena Input Analyzer Assignment 4 8 3/8 Multi-way decisions, Sets, Variables, Expressions, Submodels, Duplicating entities, Holding entities Terminating vs. steady-state simulations Sets and Resource logic, nonstationary arrival process Built exclusively via SIMAN Blocks, Elements Assignment 4 is due 9 3/15 Spring Break 3/13-3/20 5

6 Week Date Topic 10 3/22 Midterm Exam 11 3/29 Lower-level modeling, Advanced Process panel Three-way decisions, Variables, Expressions, Storages Blocks panel Terminating vs. steady-state operation Logical ( fake ) entities Terminating Condition in Run > Setup Assignment /5 Output Analyzer Evaluating Many Scenarios with the Process Analyzer Assignment 5 is due Assignment /12 Time frame of simulations Strategy for data collection and analysis Confidence intervals 14 4/19 Comparing two alternatives Comparing many alternatives via the Arena Process Analyzer (PAN) Searching for an optimal alternative with OptQuest Assignment 6 is due 15 4/26 Last Day of Classes Final Project Due 6