# Products

## Using the MEboost Tolerance Calculator

The MEboost tolerance calculator allows you to see the potential rejection rate given a probability distribution for a dimension.  This allows you to estimate rejection rate while balancing the necessary tolerance for functionality. A tolerance range is specified by a range of sigmas (standard deviation) around the nominal dimension, or you can directly specify the …

## Interpolating S-N Data

When doing stress life fatigue analysis of spectral loading, interpolating S-N data becomes necessary.  MEboost has three methods to do this, depending on the data available. Background on Cumulative Fatigue Damage Before proceeding, let’s briefly explain why we need to interpolate.  With spectral loading, the stress cycles are varying with time.  The first step is …

## Modeling Tip: Sum Random Variables

An easy to make mistake when modeling identically distributed random variables is to use a single variable to model several identically distributed values.  We could easily assume that several random variables that have the same probability distribution could be modeled by sampling a single variable and multiplying by the total number of variables.  This is …

## The Risks Hidden in Single Point Estimates

Building a spreadsheet model for a business case, product profitability projection, etc. often entails estimating some input factors.  The estimates are often a most likely value, an estimated average, or median.  These are single-point estimates since you’re only using one number (a single data point) for each input.  Finally, you get an output number from …

## Sampling from an Empirical Distribution

When data is available, an empirical distribution can be used in a Monte Carlo simulation.  In this article we’ll cover the basics of the empirical distribution and how to use it in your models. Empirical vs. Parametric Distributions Before we get into details, let’s look at the big picture for a minute.  A parametric probability …

## Optimizing a Design with Monte Carlo Simulation

Performance and cost trade-offs are a constant in engineering design.  Optimizing a design to balance these competing forces can be challenging to quantify and we often have to resort to experience or intuition.  One of the traditional cost drivers is specifying tolerances.  Part dimensions are naturally random variables since each part manufactured will not be …

## Tolerance Analysis in Excel with MEboost

MEboost allows for easy analysis of a tolerance stack.  In this article we’ll show how to perform worst case, root sum squared (RSS), and Monte Carlo tolerance analysis in Excel using MEboost.  If you want more background information on the three methods, check out the tolerance analysis article. The MEboost tolerance analysis tools are capable …

## Why Do Machine Learning in Excel?

If you want to wade into the world of machine learning, there are open-source solutions that will usually meet your needs.  The question arises as to why anyone would do machine learning entirely in Excel?  If you were to go to Reddit or Stack Exchange and ask a question about it, you should be prepared …

## Monte Carlo Simulation for Business

Monte Carlo simulation for business purposes is a great tool to have in your toolbox.  If you’re a business owner or a product line owner in a larger enterprise, chances are you’ve created a spreadsheet to model a business case or something similar.  Anytime you have a spreadsheet that contains estimates that are inputs to …

## Creating a Vibration Transmissibility Plot

A vibration transmissibility plot is a useful way of seeing the response of a harmonic oscillator.  In this article we’ll go over the basics of undamped and damped vibration as well as understanding what a vibration transmissibility plot means. In the context of this article, we will be considering spring – mass and spring – …