Great stories others want to hear. Common challenges we have all faced before (or might even be facing right now). Discovering new tools in Minitab software as shared by peers. Engaging walkthroughs of finding insights in your data, and recommendations on how to act on them. All packed into a few days of learning and fun.Continue Reading
Definitive Screening Designs (DSDs) are a new class of Designs of Experiments (DoE) that have generated a lot of interest for product and process optimization. They are available in Minitab Statistical Software.Continue Reading
Process validation is vital to the success of companies that manufacture pharmaceutical drugs, vaccines, test kits and a variety of other biological products for people and animals. According to FDA guidelines, process validation is “the collection and evaluation of data, from the process design state through commercial production, which establishes scientific evidence that a process is capable of consistently...Continue Reading
Confidence intervals show the range of values we can be fairly, well, confident, that our true value lies in, and they are very important to any quality practitioner. I could be 95% confident the volume of a can of soup will be 390-410 ml. I could be 99% confident under 2% of the products in my batch are defective.Continue Reading
You might be thinking, six weeks and you’re still not telling us what happened? When you are solving a manufacturing or development problem you might hear the same thing from your leadership – when will we get the results?Continue Reading
The potential benefit of the data stored on servers is huge. Banks, insurance companies, telecom companies, manufacturers — in fact organizations from across all industries need to make good use of the data they own to improve their operations, better understand their customers and find competitive advantage.Continue Reading
Previously in our designed experiment on driving the golf ball as far as possible from the tee, we tested our four experimental factors and determined how many runs we needed to produce a complete data set.
Now let’s analyze the data and interpret the covariates and blocking variables.Continue Reading
In our continuing effort to use experimental design to understand how to drive the golf ball the farthest off the tee, we have decided each golfer will perform half the possible combinations of high and low settings for each factor. But how many times should each golfer replicate their runs to produce a complete data set?
Tomorrow marks the 47th anniversary of the premiere of the great 1971 movie Willy Wonka and the Chocolate Factory, wherein the reclusive owner of the Wonka Chocolate Factory decides to place golden tickets in five of his famous chocolate bars, and allow the winners of each to visit his factory with a guest. Since restarting production after three years of silence, no one has come in or gone out of the factory....Continue Reading
As we broke for lunch, two participants in the training class began to discuss, debate, and finally fight over a fundamental task in golf —how to drive the ball the farthest off the tee. Both were avid golfers and had spent a great deal of time and money on professional instruction and equipment, so the argument continued through the lunch hour, with neither arguer stopping to eat. Several other class participants...Continue Reading