System Simulation, putting science into automation investment decisions

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1 em ation 2005 Irish Automation Seminar Enterprise Ireland and the Automation Research Centre UL System Simulation, putting science into automation investment decisions by Garret O D Dept. of Mechanical and Manufacturing Engineerin TCD

putting science into automation investment decisions by

2 uction Topics System simulation in the context of a Holistic approach to automation Using decision support tools Building models and simulating processes Visualisation Complexity Productivity and Costing Advantages and disadvantages of simulation modelling Concluding comments

and simulating processes Visualisation Complexity Productivity and

3 tem tion in text Modeling Before purchasing a car, it makes sense to take a test drive.. Likewise, before spending hundreds of thousand Euros on an automation project it would make se to take it for a test run. Simulation allows you to take a concept for a te run! Use the developed simulation model to: Visualise the problem.convince the laype Compress time.examine output up to 201 Evaluate alternatives. Put science into the cost and ROI.

for a test run. Simulation allows you to take a concept for a te run!

4 tem lysis nd elling Systems analysis and modelling System analysis is the application of scientific method, modified to capture the holistic nature the real world, to solve complex problems What is a model?... 2 definitions A simple definition is that a model is a set of assumptions that describe how something works More formally, a model is an abstract generalisat or representation of a system

5 elling ples Model types There are many different types of models: Descriptive models Iconic, Graphic, and Diagrammatic models Analogue models Mathematical or Symbolic models Decision models

6 elling mple: lisation Layout Process layout.difficult to visualise

7 elling mple: plexity Product Mix Simple product mix.that becomes complex to implem Possible use of FMS Iconic, Graphic, and Diagrammatic models Analogue models Mathematical or Symbolic models Decision models

Iconic, Graphic, and Diagrammatic models Analogue

8 elling mple: ng and power Man power allocation and utilisation Resource allocation.machines and manpower Headline and screenshot Possible use of FMS Iconic, Graphic, and Diagrammatic models Analogue models Mathematical or Symbolic models Decision models

machines and manpower Headline and screenshot Possible use of

9 ation s Main areas of simulation usage Experimentation with internal interactions of complex systems Knowledge gained about system during model building Finding most important variables in a system A pedagogical device to reinforce analytical solutions Permit visualisation of a complex system

model building Finding most important variables in a system A pedagogical

10 lation cation eas Common areas of application for simulation Analysing manufacturing systems Military operations and logistics Hardware and protocols for communication system Designing and operating transportation systems Evaluating service strategies Reengineering of business processes Inventory systems Analysing financial or economic systems

system Designing and operating transportation systems Evaluating service strategies

11 ntages ulation Advantages of simulation are Simulation models can be explored without affecting real systems Often not necessary to contribute serious resources Hypothesis can be tested Time scale can be compressed or expanded Insight to variable interaction and importance Visualisation of the system

serious resources Hypothesis can be tested Time scale can be compressed or

12 antages ulation Disadvantages Model building requires specialist training Simulation results can be difficult to interpret Simulation modeling can be time consuming and expensive Often misused, e.g. where an analytical solution is possible.

interpret Simulation modeling can be time consuming and

13 tem lysis nd lation Rules to determine when simulation is NOT appropr if problem can be solved by common sense! if the problem can be solved analytically Banks and Gib if easier to perform direct experiments if the costs exceed the savings if the resources or time are not available if data is not available if model can not be validated if management have unreasonable expectations If system behavior is too complex or ill defined

if the problem can be solved analytically Banks and Gib if easier to perform direct experiments if the

14 details Contact details Department of Mechanical and Manufacturing Engine Parsons Building Trinity Colle Dublin 2 Phone: Fax: Garret.OD@tcd.ie

15 ation ation Relevant links Simulation software Extend Arena Witness Enterprise dynamics Flexsim Simulation organisations

lanner.com/ Enterprise dynamics http://www.incontrol.

MANAGEMENT INFORMATION. Prepared By: Hardeep Singh

MANAGEMENT INFORMATION. Prepared By: Hardeep Singh MANAGEMENT INFORMATION SYSTEM Definition A Management Information System is an integrated user-machine system, for providing information, to support the operations, management, analysis & decision-making