Simulation Of A Hot Strip Mill Manufacturing Facility

Modeling, Simulation, and Productivity Analysis of a
Hot Strip Mill Manufacturing Facility




A Special Project
Submitted to the College of Engineering,
Technology, And Computer Science
of
Tennessee State University
in
Partial Fulfillment of the Requirements
for the Degree of
Master of Engineering


WithConcentration in
Manufacturing Engineering












Juan Carlos Guisao J.
August 2009


To the Dean of the College of Engineering, Technology and Computer Science:
We are submitting a project report by Juan Carlos Guisao J, “Modeling, Simulation and Productivity of a Hot Strip Mill Manufacturing Facility”. We recommend that this be accepted in partialfulfillment of the requirements for the degree of Master of Engineering, with a concentration in Manufacturing Engineering.


____________________________________
Committee Chairman

____________________________________ Committee Member

____________________________________ Committee Member

____________________________________ Department Head

____________________________________Associate Dean and Head of
Graduate Program

Accepted for the College Of Engineering, ___________________________________
Technology and Computer Science Dean of the College of Engineering
Technology and Computer Science





ABSTRACT


MODELING, SIMULATION, AND PRODUCTIVITY ANALYSIS OF A HOT STRIP MILL MANUFACTURING FACILITY.


Juan Carlos Guisao J., Graduate StudentDepartment Of Mechanical and Manufacturing Engineering


The Hot Strip Mill (HSM) under study is a facility that produces twelve different types of Steel Coils by the system of hot rolling metal strips. The strips are then coiled, cooled, and transported to a storage field. This project consisted of the design and construction of a model and posterior simulation with the purpose ofstudying the variables of Output and Profits as they were affected by the transportation cost, transportation capacity, cooling times, and yield loss due to damage, caused by handling of the hot Coils. Three different model configurations were compared using dynamic, stochastic, discrete-event driven simulation. Statistical analysis, including goodness to fit tests, hypothesis testing, andconfidence intervals were used to draw conclusions. Out of the three model configurations studied the best results in the Average Weekly output (AWO) and Average Weekly profits (AWP) variables were given by the current configuration (configuration #1) characterized by the use of tractor carriers with a Ram length of 400 cm, a requirement for cooling of 1.4 min/Mg, and a yield loss due to damage duringtransportation of 0.5% of the total weight produced.

TABLE OF CONTENT



ABSTRACT-------------------------------------------------------------------------------------------------------------- i

CHAPTER I INTRODUCTION 1

1.1 Background 1

1.2 Problem Statement 2
1.2.1 Operation Details 4

1.3 Project Goal 9

1.4 Objectives 10

1.5 Description of Alternative SystemConfigurations 11
1.5.1 Configuration # 2: Tractor Capacity Enhancement from a Ram Length of 400 cm to a Ram Length of 450 cm. 11
1.5.2 Configuration # 3: Yield Improvement 12

1.6 Methodology 13

1.7 Report Organization 14

CHAPTER II SUPPORTING THEORY 15

2.1 Systems Simulation 15

2.2 Statistical Concepts 18
2.2.1 Confidence Intervals 18
2.2.2 Hypothesis testing 20CHAPTER III MODEL CONSTRUCTION 22

3.1 Conceptual Model 22
3.1.1 Control Variables and Dependent variables 25
3.1.2 System Parameters 26
3.1.3 Input Probability Distributions 28
3.1.4 Assumptions 32

3.2 Construction of the Model in Arena 34
3.2.1 Data Modules 34
3.2.2 Logic Modules 47

3.3 Alternative Configurations 80
3.3.1 Configuration # 2 – New Carriers...