david james raistrick shrink wrap conveyor line submitted in · pdf file 2012. 12....

Discrete Event simulation

Shrink Wrap Conveyor Line

Submitted in partial fulfilment of the requirements of

Advanced E

Faculty of Art’s, Environment and

Discrete Event simulation

David James Raistrick

Shrink Wrap Conveyor Line

Submitted in partial fulfilment of the requirements of Leeds Metropolitan University

for the Degree of Advanced Engineering Management

Faculty of Art’s, Environment and Technology

December 2011

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Submitted in partial fulfilment of Leeds Metropolitan University

ngineering Management

Technology

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Authorship Declaration

I, David James Raistrick confirm that this dissertation/assignment and the work

presented in it are my own achievement.

Where I have consulted the published work of others this is always clearly

attributed;

Where I have quoted from the work of others the source is always given. With the

exception of such quotations this dissertation is entirely my own work;

I have acknowledged all main sources of help;

If my research follows on from previous work or is part of a larger collaborative

research project I have made clear exactly what was done by others and what I

have contributed myself;

I have read and understand the penalties associated with Academic Misconduct.

I also confirm that I have obtained informed consent from all people I have

involved in the work in this dissertation following the School's ethical guidelines

Signed:

Date: 02/01/2012

Student ID No: C3153272

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Abstract

This report has been published on the results which investigate various

scenarios for how the Shrink Wrap Conveyor line at a large glass bottle

manufacturing plant can transport the pallets out of the building to the dispatch

area where they will be loaded onto the wagons for shipping. This investigation

will be carried out using Discrete Simulation modelling software to reconstruct

real time outputs.

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Contents

1.0 INTRODUCTION ....................................................................................... 7

2.0 DISCRETE EVENT SIMULATION ................................................................. 8

2.1 Basic Concept .......................................................................................................................................... 9

2.2 Benefits of Discrete Event Simulation ................................................................................................ 11

2.3 Deterministic and Stochastic Distribution .......................................................................................... 13

3.0 PROJECT ..................................................................................................... 15

3.1 Packing Procedure ................................................................................................................................ 16

3.2 Production Area .................................................................................................................................... 17

3.3 Current data .......................................................................................................................................... 18

3.4 Breakdown Evaluation 1 ...................................................................................................................... 19

3.5 Breakdown Evaluation 2 ...................................................................................................................... 21

4.0 USING BACK UP SHRINK WRAP MACHINE ............................................. 23

4.1 Backup Shrink Wrap Breakdown Evaluation 1 ................................................................................. 25

5.0 USING BACKUP SHRINK WRAP MACHINE METHOD 2 .......................... 27

5.1 Using Backup shrink wrap machine method 2, Evaluation .............................................................. 28

6.0 CONCLUSION .............................................................................................. 32

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List of Figures

Fig1 Diagram 4 steps of Discrete Event Simulation 10

Fig2 layout of conveyors and shrink wrap machines 15

Fig3 Break down Evaluation 1 - Line after 24 hours 19

Fig4 Break down Evaluation1 - Queue data after 24 hours 20

Fig5 Break down Evaluation 2 - Line after 24 hours 21

Fig6 Break down evaluation2 - Queue data after 24 hours 22

Fig7 Layout of Back up shrink wrap machine 23

Fig8 Back up machine, Break down Evaluation - Line after 24 hours 25

Fig9 Backup machine, Break down Evaluation - Queue data at 24 hours 26

Fig10 Layout of Back up shrink wrap machine method 2 27

Fig11Back up machine method 2, Break down Evaluation 28

Fig12 Backup machine, Break down evaluation - Queue data 29

Fig13 Model results reducing breakdown to 1 every 5 hours 30

Fig14 Queue data results reducing breakdown to 1 every 5 hours 31

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Acknowledgements

Tony Pawinski

Senior Engineering Manager at AGC

Providing technical information on conveyor and process speeds, and proposed

solutions to the problems.

Ian Pickersgill

Cold End Production Manager at AGC

Providing the technical information on the current production times for pallets

produced, timing for fork truck travel and costing for down time.

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1.0 Introduction

This report shows how software can be used to model a process or factory without

the need of physically building or utilising hardware or production time. The

particular software been used is called Flexsim which is a USA based company who

state on their website

www.flexism.com

Accessed 01/11/2011

“Flexsim is the most powerful tool for modelling, analyzing, visualizing, and

optimizing any imaginable process - from manufacturing to supply chains, abstract

examples to real world systems, and anything in between.”

Learning outcomes within this module are

• Identify where and how simulation can benefit an organisation and its role in

design, planning and control of production systems.

• Critically evaluate the statistical data a discreet event simulation package can

produce via different data points including throughput, content, machine state

and utilization,

• Interpret the financial analysis data generated by a discreet event simulation

package and defend a strategy of improvement.

• Model discrete event data and processes using techniques at the forefront of

current best practice to recommend optimized scenarios for a given situation.

Within this report a large bottle manufacturing plant based in Leeds will have a

section of its production facility modelled and performance analysed using various

scenarios. The aim of this research and modelling is to determine which would be

the most efficient way to use the backup shrink wrap machine, potentially saving

money and down time.

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2.0 Discrete Event Simulation

Discrete event simulation is a method used widely today to analyse and investigate

processes without actually producing a physical model or factory. Software is used

to simulate all factors of a desired project and statically predict outcomes and effect

within the processes.

A proposed project can be completely modelled with all the known and predicted

parameters to evaluate the outcome and the streamline the process to prove or

disprove whether the proposed project could actually work in the real world.

http://www.telecom.otago.ac.nz/tele302/ref/Banks_DES.pdf

Document read 12/12/2011

Jerry Banks Marietta, Georgia 30067, Initially published in the Proceedings of the 1999 Winter

Simulation Conference

Stated

“A discrete-event simulation model is defined as one in which the state variables

change only at those discrete points in time at which events occur.”

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2.1 Basic Concept

Discrete Event Simulation works on simple concepts of how long it takes for things to

happen, and what implications arise after a period of time. To break this down it can

be said that there are 4 simple steps.

As shown in Fig1

Website accessed 09/12/2011

http://www.coensys.com/discrete_event_simulation.htm

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Fig1 Diagram 4 steps of Discrete Event Simulation

1. Source – This is the beginning of any process were an action or object will

arrive and be distributed into the sequence of event it must go through before

it can be dispatched at the end.

2. Queue – This is the holding area were the object will wait until the next action

is ready to accept it

3. Delay – This is the action which the object must go through

4. Sink – This is the exit or dispatch when the process is complete

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