Define, measure, analyze measurement

DMADV Define — measure — analyze - improve - control... 

DMAIC Define - measure - analyze - design - verify... 

Finally, a major challenge for both developers and regulators of biologic-device combination products is the potential need to reconsider the way that certain key parameters typically associated with preclinical assessment, such as dose in the case of the biologic and durability in the case of the device, are defined, measured, and analyzed. 

The final product quality must satisfy the demands of the initial objectives. That means that along all the different operations/processes, the transformations will be controlled not only to define, measure, optimize the operating conditions but to be able to analyze the constituents, to describe the history of evolution of physical and chemical structures. As usual, adapted analyses are a very important complementary part of processing. 

The Six Sigma approach is composed by five steps, i.e. the DMAIC algorithm (Fig. 1) Define, Measure, Analyze, Improve and Control. 

Many readers will know that Six Sigma practitioners utilize a similar process. Its acronym is DMAIC, which stands for Define-Measure-Analyze-Improve-Control. This cycle is similar to PDCA either approach is valid. 

DMIAC Define, Measure, Analyze, Improve, and Control. A process for implementing supply chain changes associated with the Six Sigma improvement process. (A foundation for operational excellence, Supply Chain Management Review, March/April 2003)... 

Six sigma Six sigma is one of the more recent popular approaches to QA that is based on a tight statistical approach to the production of a product. The name arises from a desire to limit the tolerance of a product to plus or minus six standard deviations and thus have only 3.4 defects per million. (This is the fraction outside - - 4.5 standard deviations from the mean the method allows for some measurement uncertainty.) In order for the statistics to hold, the system must be in statistical control and the defects must be random and normally distributed. There is a heavy reliance on control charts and the system is built around what to do if there is evidence for nonconformity. For a nonconforming product six sigma institutes an approach with the acronym DMAIC — define, measure, analyze, improve, control. This has been implemented in some organizations, such as pharmaceutical companies, which produce large volumes of chemicals. However, strict statistical control of chemical products is not always easy, and considerations of the measurement process also needs to be taken into account. 

DMAIC define, measure, analyze, improve, control... 

Some of the Six Sigma models are DMAIC (Define, Measure, Analyze, Improve, Control), which is used to improve the existing process, and DMADV (Define, Measure, Analyze, Design, Verify), which is used to employ the new products. 

DMAIC Define, Measure, Analyze, Improve, and Control... 

The physical techniques used in IC analysis all employ some type of primary analytical beam to irradiate a substrate and interact with the substrate s physical or chemical properties, producing a secondary effect that is measured and interpreted. The three most commonly used analytical beams are electron, ion, and photon x-ray beams. Each combination of primary irradiation and secondary effect defines a specific analytical technique. The IC substrate properties that are most frequendy analyzed include size, elemental and compositional identification, topology, morphology, lateral and depth resolution of surface features or implantation profiles, and film thickness and conformance. A summary of commonly used analytical techniques for VLSI technology can be found in Table 3. 

AH three parameters, the cut size, sharpness index, and apparent bypass, are used to evaluate a size separation device because these are assumed to be independent of the feed size distribution. Other measures, usually termed efficiencies, are also used to evaluate the separation achieved by a size separation device. Because these measures are dependent on the feed size distribution, they are only usefiil when making comparisons for similar feeds. AH measures reduce to either recovery efficiency, classification efficiency, or quantitative efficiency. Recovery efficiency is the ratio of the amount of material less than the cut size in the fine stream to the amount of material less than the cut size in the feed stream. Classification efficiency is defined as a corrected recovery efficiency, ie, the recovery efficiency minus the ratio of the amount of material greater than the cut size in the fine stream to the amount of material greater than the cut size in the feed stream. Quantitative efficiency is the ratio of the sum of the amount of material less than the cut size in the fine stream plus the amount of material greater than the cut size in the coarse stream, to the sum of the amount of material less than the cut size in the feed stream plus the amount of material greater than the cut size in the feed stream. Thus, if the feed stream analyzes 50% less than the cut size and the fine stream analyzes 95% less than the cut size and the fine stream flow rate is one-half the feed stream flow rate, then the recovery efficiency is 95%, the classification efficiency is 90%, and the quantitative efficiency is 95%. 

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