Discrete-Event Simulation: Methodology and Practice

November 21-22, 2005 Warsaw University of Technology Lect. Jelena Pecherska

DiscreteDiscrete--Event Simulation:Event Simulation:Methodology and Practice Methodology and Practice

byProf., Dr.sc.habil.ing. Yuri Merkuryev

Lect., M.Sc. Jelena Pecherska

Department of Modelling and SimulationRiga Technical University

Riga, [email protected]

www.itl.rtu.lv/mik/ymerk


Simulation tools Simulation tools –– A surveyA survey


Simulation software in universities


Simulation software reports and visualization. Example

Arena histogram


Simulation software reports and visualization. Example

Extend Gantt chart


Simulation software examples.Extend

www.imaginethatinc.com


Simulation software examples.AutoMod

http://www.automod.com/products/products.asp


Simulation software examples.Arena

www.arenasimulation.com


Arena Arena –– An OverviewAn Overview


What is Arena?

Arena is the preeminent solution for better business decisions with simulation. Arena is an easy-to-use, powerful tool that allows you to create and run experiments on animated models of your systems


Arena simulation concepts• Entities and Attributes • Queues • Resources • Statistics • Sets • Stations and Activity Areas • Storages • Sequences • Conveyors • Transporters


Arena product overview (1)Arena Basic is the most effective when analyzing business,

service, or (non material handling intensive) manufacturing processes or flows. Includes: Basic Process Template

Arena Professional is most effective when analyzing complex, medium to large-scale projects related to supply chain, manufacturing, processes, logistics, distribution, warehousing, and service systems. Arena PE is used to create customized templates focused on specific applications or industries. Includes: Basic Process, Advanced Process, Advanced Transfer, Flow Process, Blocks, Elements, OptQuest for Arena

http://www.arenasimulation.com/products/default.asp


Arena product overview (2)

The Arena Enterprise Suite offers a convenient bundle of products for the organization with a wide range of modelling problems. It includes all the features of Arena Factory Analyzer, plus Arena Contact Center and Arena 3DPlayer.

Includes: Basic Process, Advanced Process, Advanced Transfer, Flow Process, Blocks, Elements, Packaging, Contact Script, Contact Data, Arena 3DPlayer, OptQuest for Arena, RealTime




Arena Contact Center is most effective when analyzing customer service delivered by an organizations call center. Includes: Basic Process; Advanced Process; Advanced Transfer, Blocks and Elements, and Contact Center (Contact Data and Script)

Arena Factory Analyzer is most effective when analyzing super high-speed manufacturing packaging lines and batch processes that are fundamental to the manufacturing processes of several industries.Includes: Basic Process, Advanced Process, Advanced Transfer, Flow Process, Blocks, Elements, Packaging, OptQuest for Arena and RealTime




The Arena Packaging Template is effective when analyzing manufacturing packaging lines that are fundamental to the manufacturing processes of several industries, including food and beverage; pharmaceutical; tobacco; chemical; electronics; and health and beauty.

Arena® 3DPlayer™ is a post-process tool that provides the ability to create and view 3D animations of your Arena models.



Arena templates and panels


Arena Hierarchy and SIMAN (1)

• In Arena modules are defined utilizing another modules.

• The base modules in Arena hierarchy represent SIMAN language.

• A specific set of modules forms a panel.• A number of panels is a template (e.g.

SIMAN, Arena, Basic process, etc.)


Arena Hierarchy and SIMAN (2)

Multi-layered hierarchy (2)

Single level of module hierarchy


Arena Input Analyzer

• The Input Analyzer is a standard component of the Arena environment.

• The Input Analyzer can be used to determine the quality of fit of probability distribution functions to input data. The Input Analyzer can generate sets of random data.

• The data files processed by the Input Analyzer typically represent the time intervals associated with a random process.


Arena Input Analyzer example

Data Distribution fitting to the data


Interpreting Results/Reports in Arena

There are ten reports provided by Arena. They are:• Category Overview • Category by Replication • Activity Areas • Entities• Processes • Queues • Resources• Transfers• User Specified• Frequencies


Arena statistical report example


Arena Output Analyzer

The Output Analyzer component of Arena provides an interface for data analysis and allows you to create:– Correlogram– Classical confidence interval of mean– Standardized time series – Confidence interval of standard deviationto compare:– means– variancesto perform one-way ANOVA


Arena Process Analyzer

• The Process Analyzer assists in the evaluation of alternatives presented by the execution of different simulation model scenarios. This is useful to simulation model developers, as well as decision-makers

• The Process Analyzer is focused at post-model development comparison of models. The role of the Process Analyzer then is to allow for comparison of the outputs from validated models based on different model inputs.


OptQuest for Arena

• OptQuest allows to search for optimal solutions within simulation models

• OptQuest is designed to find solutions, that satisfy a wide variety of constraints

• OptQuest controls Arena to set variable values, start and continue simulation runs and retrieve simulation results


Arena simulation examples

• Restaurant • Banking transactions• Hospital department• AGV operation• Distribution centre• Flexible manufacturing• Baltic container terminal• Simple model development example


Restaurant example


Restaurant example

• Simulated system – typical restaurant• Simulation goal – to evaluate and to improve the

performance • Performance measures:

– Number of customers served– Queue length– Cook and waiters “utilisation”– ...

• How to improve ?


Banking transactions


Banking transactions

• Simulated system – bank office• Simulation goal – to evaluate and to improve the

performance • Performance measures:

– Queue length– Automatic teller machine utilization – Teller utilization– Drive-through teller utilization– ...



Hospital department


Hospital department• Simulated system – hospital department• Simulation goal – to analyze facility utilization

and compare alternative organizational settings• Performance measures:

– Room utilization– Examination time– Patient total time in system– Queue length

...• Which alternative?


AGV operation


AGV operation

• Simulated system – production bay• Simulation goal – to evaluate the performance of

AGV and conveyors • Performance measures:

– Facility utilization– AGV and conveyor utilization– Number of produced items



Distribution centre


Distribution centre

• Simulated system – order picking and distribution center

• Simulation goal - to compare a manual picking process is with an automated process

• Performance measures:– Order time in system– Number of shipped orders– ...

• How to improve?


Flexible manufacturing


Flexible manufacturing

• Simulated system – factory• Simulation goal: to analyze facilities utilization

and to improve performance• Performance measures:

– Number of produced items– Facility and AGV utilization– ...

• How to improve?


Baltic container terminal


Baltic container terminal

• Simulated system – container transportation processes

• Simulation goal – support decision – making in– Planning of concrete shipment – Planning of device modernization– Demonstrating terminal operation to potential clients– ...

• How to improve?


References1. Kelton W. D., R. Sadowski, and

D. Sturrock, (2004), Simulation with Arena. 3d ed., McGraw-Hill.

2. Arena professional Edition Reference Guide

3. OptQuest for Arena User’s Guide

Discrete-Event Simulation: Methodology and Practice

Documents

Transcript of Discrete-Event Simulation: Methodology and Practice