Simulation and Monte Carlo Analysis

Speaker

Instructor: Daniel O Leary
Product ID: 704856

Location
  • Duration: 90 Min
Simulations and Monte Carlo methods are powerful tools in quality improvement. They can help explore proposed changes to methods and processes and avoid potential problems. They can also help optimize QMS activities. In this presentation, attendees learn methods in Excel, which means that projects do not need special purpose and expensive software packages.
RECORDED TRAINING
Last Recorded Date: Aug-2016

 

$249.00
1 Person Unlimited viewing for 6 month info Recorded Link and Ref. material will be available in My CO Section
(For multiple locations contact Customer Care)

$299.00
Downloadable file is for usage in one location only. info Downloadable link along with the materials will be emailed within 2 business days
(For multiple locations contact Customer Care)

 

 

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Bonus Material:

An Excel spreadsheet with the examples from the presentation

Why Should You Attend:

Simulation is a powerful tool to help understand production process, projects and quality assurance activities. Monte Carlo simulation uses random numbers from statistical distributions to help model the activities of interest.

Microsoft Excel, with its built-in functions, allows generation of random numbers from a variety of statistical distributions. These results combined in a simulation can help in understanding processes and activities. This is especially true when the model is difficult or impossible to calculate using analytical methods.

The presentation explains some concepts of statistical distributions needed to generate random numbers. It then explains the methods in Excel, using a random number generator and various inverse functions to illustrate the methods. Example illustrate the methods so participants can see the application and the results. The examples also explain how to construct Excel spreadsheets for simulations.

Areas Covered in the Webinar:

  • The use of models to help understand activities and process
  • The role of Monte Carlo simulation in the model
  • Using Excel to generate random numbers
  • The relationship between probability density functions and cumulative density functions
  • Excel functions that can produce random numbers from various statistical distributions
  • Combining the random numbers in the model to produce results

Who Will Benefit:

Manufacturers involved in process improvement projects

  • Quality Managers
  • Quality Engineers
  • Manufacturing Managers
  • Design Project Team Members
  • Data Analysts
  • Statistical Analysts

Instructor Profile:

Dan O'Leary is President of Ombu Enterprises, LLC, a company offering training and execution in Operational Excellence, focused on analytic skills and a systems approach to operations management. Dan has more than 30 years’ experience in quality, operations, and program management in regulated industries including aviation, defense, medical devices, and clinical labs. He has a Masters Degree in Mathematics; is an ASQ certified Biomedical Auditor, Quality Auditor, Quality Engineer, Reliability Engineer, and Six Sigma Black Belt; and certified by APICS in Resource Management.

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