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Design of Experiments
Techniques for quality problem-solving and reduction of process variation. There are 3 types: Classic, Taguchi and Shainin. The classic techniques were developed by Sir Ronald Fisher in the 1920s in agriculture field and originated a productivity increase in the United Kingdom. The goal of the Design of Experiments is to study the behaviour of a process by measuring its results or critical characteristics - called Y(s). A group of possible combinations of inputs or process variables is defined – called X - and several experiments are performed to measure the resulting Y. Then, based on the experiment results, it is determined which inputs have a relevant effect on the process and what are the interactions between the different factors. In other words, we aim at determining the optimum combination of process inputs in order to achieve a robust process, that is, with less quality deviation.
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DFSS - Design For Lean Six Sigma
Methodology for the development of products/services and processes which aims at obtaining processes with built in eficiency and robustness, capable of meeting in full the customer requirements. It uses several tools such as the Kano Model, Quality Function Deployment, 3P and FMEA.
The process can follow one of the predefined improvement models such as:
- DICOB: Define, Investigate, Conceptualize, Optimize, Build
- DMEDI: Define, Measure, Explore, Develop, Implement
- IDOV: Identify, Design, Optimize, Verify
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Differential Analysis
Analysis and problem-solving methodology developed by Charles Kepner and Benjamin Tregoe in the 1950s
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DMAIC
Data-based improvement roadmap, central to the Six Sigma strategy, as introduced by Motorola in the late 80’s. DMAIC structures the utilization of a set of tools in a logical sequence, which results in a far higher improvement effectiveness.
DMAIC stands for Define, Measure, Analyze, Improve and Control, the five improvement steps. It is the most used roadmap in Lean Six Sigma.
