Case Studies and White Papers
Coding Products’ Hot Ink Rollers, pre-inked foam rollers measuring approximately one inch in diameter, are impregnated with ink before being sent to our wide variety of customers. Before they used DOE to improve the rollers, a customer might get 65,000 impressions from one of our rollers, while the next roller would produce anywhere from 30,000 to 120,000 impressions. Consistency in the number of impressions is crucial because it allows customers to schedule roller changes. Using DOE, the scientists revealed which factors were most critical, leading to decreased manufacturing time, improved productivity, and increased capacity.
Forma Scientific’s cooling unit is a critical component that sits within a blood analyzer being built by Ortho-Clinical Diagnostics, a Johnson & Johnson company. To do its job well, the cooler’s specification called for a constant 6°C temperature with enough capacity to remove heat introduced during operation. Scientists used DOE to identify several factors and interactions that were affecting its performance and prove that cooling coil temperature could be decreased while still providing ample refrigerating capacity. The savings from this finding exceeded $18,000 because an environmentally controlled testing facility was not needed.
Practical Aids for Teaching Experimental Designs
Design of Experiments (DOE) is an essential tool for product and process improvement. Good software now makes the set up for design and analysis of experiments very easy, but many engineers and/or non-statisticians feel intimidated by statistical outputs. For that reason, non-statisticians need training in proper designing and conducting of experiments. Ideally the DOE training is best when provided on a just-in-time basis - prior to actually doing an experiment. However, an in-class experiment is a reasonable substitute.
(This is the manuscript submitted for publication.)
How to Design and Analyze Mixture Designs that Include Process Factors and/or Categorical Variables
The latest versions of dedicated DOE software exhibit more versatility than ever before to create optimal designs that handle any combination of mixture components, processing factors (such as time or temperature) and categorical variables (such as supplier and material type). These computer programs easily manipulate almost any number of responses in powerful optimization routine that reveal "sweet spots" - the operating windows that meet all specifications at minimal cost. In this paper, we review the basic principles of mixture design. Then we apply state-of-the-art tools for optimal design to the formulation of a coating.
Computer-Aided Tools for Optimal Mixture Design
See how statistically-based mixture design of experiments (DOE) make breakthrough improvements in cost and performance of paints and coatings. Dedicated DOE software exhibit make it easy to create optimal designs that handle any combination of mixture components, processing factors (such as time or temperature) and categorical variables (such as supplier and material type). They easily manipulate almost any number of responses in powerful optimization tools that reveal "sweet spots" - the operating windows meeting all specifications at minimal cost.
Quality managers who understand how to apply statistical tools for design of experiments (DOE) are better able to support use of DOE in their organizations. Ultimately, this can lead to breakthrough improvements in product quality and process efficiency.
Revealing Interactions From Fractional DOEs
Fractional two-level factorials are a powerful tool for making significant improvements to product quality and process efficiency. Unfortunately, this approach to design of experiments (DOE) may alias the main effects with their interactions. Then it is no longer clear which factors truly influence the process. In part 1, this paper illustrates the use of graphical technique for the viewing alternative aliased interactions. The graphical procedure enhances, but does not remove, the guesswork required when a highly-fractional design produces significant effects. The only sure way to pin down the actual effects will be to perform follow up experiments, which will be discussed in Part 2. A technique called "foldover" is tailor-made for de-aliasing effects. This sequential approach to DOE offers a great deal of flexibility to the quality engineer.
In this article from Quality Digest, the author explores the basics of design of experiments (DOE) and why industry needs to adopt it. He specifically explores how DOE software can help an experimenter make breakthrough discoveries.
Nonexperimenter Tries Design-of-Experiments Software
A basic article to build awareness of the benefits of DOE and response surface methods (RSM) for process optimization.
Statistical Design of Experiments for Quality Improvements of Fertilizer Products
Statistical tools, especially design of experiments (DOE), provides the means for quality improvement of diammonium phosphate (DAP) and related fertilizer products. Depletion of high grade phosphate ores in Florida and elsewhere makes it increasingly difficult to meet customer specifications for nitrogen content of DAP. Urea or ammonia can be used as nitrogen supplements, but this adds cost to the final product. This paper lays out a special form of DOE, called two-level factorial design, which helped to maximize nitrogen content in DAP and make it less susceptible to impurities in lower grade phosphates.