Se ha denunciado esta presentación.
Utilizamos tu perfil de LinkedIn y tus datos de actividad para personalizar los anuncios y mostrarte publicidad más relevante. Puedes cambiar tus preferencias de publicidad en cualquier momento.

R Software and Reliability

556 visualizaciones

Publicado el

Looking for an inexpensive and powerful data analysis tool? R is free. R is an open source statistical programing language. Let’s explore R’s many capabilities concerning reliability statistics from field data analysis, to statistical process control.

Detailed Information: Reliability engineering relies on reliability statistics. We need software tools that allow us to explore and model data on a regular basis. Simply plotting the data, from a histogram to a probability plot allows us to ask better questions and solve problems faster. There are commercial software packages available from general purpose statistics, JMP or MiniTab, to specialized reliability packages, Weibull++ or Reliability and Maintenance Analyst. There are versatile math packages like MathCad or Mathematica. All are expensive and provide customer support and, training. R is a statistical programing language. It’s free. It has an extensive library of speciality packages. And, an immense supportive community.

It’s powerful, capable of producing publication ready graphics, includes basic and advance statistical tools, and you only need to learn a few basics to get started. Let’s explore using R for a range of common reliability statistics problems. Plotting field data, exploring process capability with statistical process control examples will highlight the power and versatility of this amazing resource.

This Accendo Reliability webinar originally broadcast on 10 March 2015.

Publicado en: Tecnología
  • Sé el primero en comentar

  • Sé el primero en recomendar esto

R Software and Reliability

  1. 1. R Software and Reliability Fred Schenkelberg
  2. 2. Reliability Statistics?Estimating reliability performance
  3. 3. Everything Varies
  4. 4. Starting Off • • • Code School “Try R” • •
  5. 5. Test Drive
  6. 6. Weather Data 1990 - 2010 California Temperatures (°C) Celisus Density -10 0 10 20 30 40
  7. 7. Do you deal with data?
  8. 8. Better Question s
  9. 9. Which is better: a plot or a number?
  10. 10. What are your Questions? Thanks for participating.