These things make work worth doing

Six Sigma with R (Springer)

Today a user of my R package SixSigma
and reader of its motivating book, Six Sigma with R, made my day. The book was published in 2012 by Springer, and it was my first scientific publication (even before any article). Later (2015) Quality Control with R came with new and improved content.

Back to what I wanted to talk about: Paul, a user from a company in Germany, reported a “bug” in a function of the package. After telling him how I was going to solve it and some new plans to improve the whole thing, he gave me two senteces that encourage me to continue working on the topic:

  1. I use your package on daily basis, as user I really appreciate your work
  2. Regarding the book, I think it should be present in each personal library of a black belt

So, someone working in the “real world” uses on daily basis the open source software that one has developed, and says that your book should be a must for a black belt (see wikipedia for newcomers to Six Sigma). Sometimes one does things apparently nonsense, but later the reason appears.

Yeah, all right. It’s free software. I do not earn anything, beyond a few lines in the curriculum to fight in the academic career, and the satisfaction of doing things that serve society. Maybe I could be making more money. But what I would really like is to get funding to hire young researchers and take this development further and faster, so that we can bring these advances to companies nearby.

Six Sigma R package new release (0.9-4)

I have just released a new version (0.9-4) of the SixSigma R package, with functions and data used in the books Six Sigma with R and Quality Control with R. This new version contains some bug fixes and improvements for the ss.rr function, for measurement systems analysis (Chapter 5 of Six Sigma with R).

I have made the changes after the feedback received by package users from industry (thank you very much Luc and Austin). It is really encouraging such input and motivates me to continue developing the package. In fact, my research group is looking for funding to develop a complete R infrastructure for quality control and improvement standardised statistical methods. There is a real need for that, see for example one of the messages from a real world user:

This morning I discussed Gage R&R with my “Minitab” collaegue. As we now calculate 144 Gage R&R’s, he could not even generate those in Minitab, the advantages of R are becoming more and more clear to him. […]

— Luc Castermans, Philips Lighting

Awesome, isn’t it?