ISYE 3104
First MidTerm
Fall, 2014
Instructions: You have 75 minutes to solve this exam. You are allowed one doublesided page of
handwritten notes. You may use a calculator. All other items must be on the floor. Your cellphone
should be turned off and di
ISyE 3104  Homework 11
Section A Due: November 13, 2013
Section B Due: November 14, 2013
All homework is due at the beginning of the class.
1. (6 points) Recall the timephased net requirements for of drawer frame assemblies in
Question 1 of Homework 10.
Introduction to Supply Chain Modeling: Manufacturing & Warehousing
ISYE 3104

Spring 2013
HW 2 Solution
1. (16 pts)
D = 5000/yr, C = 600/unit,
1 year = 300 days,
i = 0.06,
Current ordering amount Q = 200
(a) T*=
(b) Total(Holding + Setup) cost would be
(c) The optimum cost would be
(d) T* is 12 days. The closest power of two is 16 days(16/300
Damon P. Williams, Ph.D.
7/10/15
1
Load YouTube Videos A Reminder
Amazon Distribution Center
http:/www.youtube.com/watch?v=yw5NcaMxfxU
Netflix Distribution Center
http:/www.youtube.com/watch?v=40OOBYOc5BQ
7/10/15
2
Overview
Introductions
I.
A.
I
Introduction to Supply Chain Modeling: Manufacturing & Warehousing
ISYE 3104

Spring 2013
ISyE 3104: Introduction to Supply Chain Modeling:
Manufacturing and Warehousing
Instructor: Spyros Reveliotis
Spring 2013
Homework #3
Due Date: 3/7/13
Reading Assignment:
This homework covers the statistical inventory control theory that we have discussed
ISyE 3104, Exam 2, November 05, 2012
Time Limit: 90 Minutes
Name:
This exam contains 9 pages (including this cover page) and 8 problems. Check to see if any pages
are missing. Enter all requested information on the top of this page, and put your initials
Introduction to Supply Chain Modeling: Manufacturing & Warehousing
ISYE 3104

Spring 2013
ISyE 3104: Manufacturing Systems
Instructor: Spyros Reveliotis
Spring 2013
Homework #2
Due Date: Thursday, 2/14/13
Reading Assignment:
This homework covers the deterministic inventory control theory that we have discussed
in class. In your textbook, this
Inventory Control
PART 2: STOCHASTIC DEMAND: NEWSVENDOR AND
BASE STOCK MODELS
Georgia Tech, 2015
ISyE 3104 Summer 2015
1
Recap of Part 1
Specified a procedure for selecting the appropriate size of a replenishment quantity under constant and deterministic
Inventory Control:
Introduction
ISYE 3104
1
Material Flow for a Manufacturing Enterprise
What is Inventory?
Material that has been
purchased from a supplier, may
have been partially or completely
converted, but not yet sold to the
customer
Raw material
Co
L06.1 Variability,
Flow and Capacity
Laws
Georgia Tech
ISyE 3104
1
Basic Principle
As variability increases, performance declines
CTq V U t
ca2 ce2 u 2(m1) 1
te
2 m(1 u)
100
WIP = CT*TH
90
80
70
60
This basic structure is reflected in all
the Ch. 8 mo
Ch 10: Push vs. Pull
Systems
Georgia Tech
ISyE 3104
1
Learning for Today
Semantics of Push and Pull
Implementation of Push and Pull
Push and Pull process maps
Analyzing Pull with Mean Value Analysis
Comparing analytic and simulation models
Georgia
Week4.Lecture1.ICE KEY
_ _
Print: Lastname, Firstname
Sign
_ _
Print: Lastname, Firstname
Sign
This is a team assignment.
1. Consider R2D2 with 6 servers (in parallel), each requiring 7.389 hours of process time per job with 2 = 6.389. Each R2D2
machine c
L04.1 Queueing and VUT
Approximation
Georgia Tech
ISyE 3104
1
Motivation
Up till this point we
Learned how to calculate the capacity of a flow line
Computed the best case, worst case and practical worst case performance
Used best case, worst case and
3104 Intro &
Overview:
SUPPLY CHAIN MODELS: MANUFACTURING SYSTEMS
Georgia Tech
ISyE 3104
1
What will we do today
Introductions: Who am I? Who are you?
What this course is about and what you will learn
Expectations: Professor to Student & Student to Profe
Basic Flow
Dynamics Penny
Fab 1
Georgia Tech
ISyE 3104
1
Follow Up
FROM THE VIDEOS
What did you learn about process mapping?
What did you learn from the three scenarios?
Georgia Tech
ISyE 3104
2
Motivation
Basic semantics of process flows
A highly styli
To Begin
* Group: Process Map from HW 2
* Group: Matlab #2 from HW 2
* Group: In Class Exercise from Week 2 Folder
Georgia Tech
ISyE 3104
1
L03.1 Capacity &
Utilization
CAPACITY DETRACTORS: PREEMPTIVE AND NONPREEMPTIVE FAILURES;
Georgia Tech
ISyE 3104
2
ISyE 3104 Exam 1 — Part I
Instructor: Damon P. Williams, Ph.D.
Name (Print Neatly): 0 a1: (Syb—
Section (8am or 9am):
Quiz Number (Print Neatly}:
l’oint values are indicated ne\:t to each problem  pleaae take these into consideration a*; you budget
your
ISyE 3104 Exam 1 — Part I
Instructor: Damon P. Williams, I’h.D.
Name {Print Neatly }: M 50%
Number {Print Neatly}:
l’oint values are indicated next to each problem  please take these into consideration as you budget
your time during the exam. lfyou are h
Nave Bayes and
logistic regression
Le Song
Introduction to Computational Data Analysis
CX4240, Spring 2017
Classification
Represent the data
A label is provided for each data point, eg.,
1, 1
Classifier
2
Boys vs. Girls (demo)
3
Decisionmaking: divide hi
Regression
Le Song
Introduction to Computational Data Analysis
CX4240, Spring 2017
Machine learning for apartment hunting
Suppose you are to move to Atlanta
And you want to find the most
reasonably priced apartment satisfying
your needs:
squareft., # of
Regression and CrossValidation
Le Song
Introduction to Computational Data Analysis
CX4240, Spring 2017
Apartment hunting
Suppose you are to move to Atlanta
And you want to find the most
reasonably priced apartment satisfying
your needs:
squareft., # of
Chapter 7.2
Terms:
Workstation: collection of machines that perform the same function
Part: Piece of raw material, component, etc. that is worked on at workstations
Raw Material: parts purchased outside the plant
End Item: part sold directly to customer
C
Material Flow
Systems
EXAMPLES, TERMINOLOGY AND CONCEPTS
Georgia Tech, 2015
ISyE 3104 Summer 2015
1
Content
Examples of material flow systems
Common features
Some helpful concepts
Georgia Tech, 2015
ISyE 3104 Summer 2015
2
Healthcare
Example
Georgia
Question 1 Pooled vs. separate queues:
The arrival rate to the R2D2 workstation is 0.5 jobs per hour and follows a Poisson process. Compare the average cycle time at
R2D2 under the following scenarios for the system configuration
Scenario
Configuration
Week2.Lecture2.ICE KEY
_ _
Print: Lastname, Firstname
Sign
_ _
Print: Lastname, Firstname
Sign
This is a team assignment.
Open the "PennyFab_Stochastic.slx" model, and check to see that it is properly configured with
exponential service times and number o
Practical Worst Case
Georgia Tech, 2016
ISyE 3104 Fall 2016
1
Practical Worst Case
Question: Can we find an intermediate case between best case and worst case that:
Distinguishes good and bad lines, and
is computable?
We are looking for a maximum rando
ISyE 3104 Exam 1 Part I
Instructor: Damon P. Williams, Ph.D.
Name (Print Neatly): _
Number (Print Neatly): _
Point values are indicated next to each problem please take these into consideration as you budget
your time during the exam. If you are having di
Part I
1b
2a
3c
4d
5b
6e
7b
Part II
1T
2F
3F
4F
5T
6T
7T
Part III
p1.a)
Reducing Manufacturing Costs
Reducing Variability
Improving quality
Maintaining flexibility
Facilitating Work Ahead
b) Since WIP = CT * TH, one can have the same TH with high WIP leve
Part I MCQ
1b
2b
3c
4a
5a
6a
7a
Part II T/F
1F
2F
3F
4T
5T
6T
7F
Part III short answer
1 a. Natural Variability, Random outages, Setups, Operator availability, and rework
b. CTq =V U T
2
3 a) arrival = 5 jobs/hour
b) TH = 3.513 jobs/hour
c) lost = 35.6
ISyE 3104 Exam 1 Part I
Instructor: Damon P. Williams, Ph.D.
Name (Print Neatly): _
Number (Print Neatly): _
Point values are indicated next to each problem please take these into
consideration as you budget your time during the exam. If you are having
di
ISyE 3104 Exam 1 Part I
Instructor: Damon P. Williams, Ph.D.
Name (Print Neatly): _
Number (Print Neatly): _
Point values are indicated next to each problem please take these into
consideration as you budget your time during the exam. If you are having
di