Using Monte Carlo Simulation to Aid Your Medical Device Design – Webinar Recording/Transcript
Using Monte Carlo Simulation to Aid Your Medical Device Design
Determining the impact of risk and uncertainty in medical device design is critical.
Did you know that Microsoft Excel can help predict product outcomes when combined with Monte Carlo simulation?
Monte Carlo simulation uses random numbers from a variety of statistical distributions to assess risk and uncertainty in forecasting models. With its built-in functions, Excel can generate random numbers to inform simulation, helping practitioners evaluate processes and activities, particularly for models that are difficult to calculate using analytical methods.
Join Dan O’Leary and discover how to use Monte Carlo simulation for medical device design.
Key Presentation Takeaways:
- Determine the use of models in assessing activities and processes
- Critically evaluate the role of Monte Carlo simulation in the model
- Use Excel to generate random numbers
- Examine the relationship between probability density functions and cumulative density functions
- Apply Excel functions that can produce random numbers from various statistical distributions
- Combine the random numbers in the model to produce results
Understand the impact of risk and uncertainty in prediction and forecasting models.
Meet Your Presenter:
Your webinar leader is Dan O’Leary, President of Ombu Enterprises, LLC, a company offering training and execution in Operational Excellence that focuses on analytic skills and a systems approach to operations management. Dan has more than 30 years of experience in quality, operations, and program management in regulated industries including aviation, defense, medical devices, and clinical labs. He has a master’s degree in mathematics, is an ASQ certified Biomedical Auditor, Quality Auditor, Quality Engineer, Reliability Engineer, and Six Sigma Black Belt. He is also certified by APICS in Resource Management.
Who Will Benefit:
- Medical Device Manufacturers
- Quality Managers
- Quality Engineers
- Manufacturing Managers
- Design Project Team Members
- Data Analysts
- Statistical Analysts