Difference between revisions of "Template:Article of the week"

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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Melanitis MATECWebConf21 349.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Karaattuthazhathu NatJLabMed23 12-2.png|260px]]</div>
'''"[[Journal:Designing a knowledge management system for naval materials failures|Designing a knowledge management system for naval materials failures]]"'''
'''"[[Journal:Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study|Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study]]"'''


Implemented materials fail from time to time, requiring [[failure analysis]]. This type of scientific analysis expands into [[Forensic science|forensic]] engineering for it aims not only to identify individual and symptomatic reasons for failure, but also to assess and understand repetitive failure patterns, which could be related to underlying material faults, design mistakes, or maintenance omissions. Significant [[information]] can be gained and studied from carefully documenting and managing the data that comes from failure analysis of materials, including in the naval industry. The NAVMAT research project, presented herein, attempts an interdisciplinary approach to [[materials informatics]] by integrating materials engineering and [[Informatics (academic field)|informatics]] under a platform of [[Information management|knowledge management]]. Our approach utilizes a focused, common-cause failure analysis methodology for the naval and marine environment. The platform's design is dedicated to the effective recording, efficient indexing, and easy and accurate retrieval of relevant information, including the associated history of maintenance and secure operation concerning failure incidents of marine materials, components, and systems in an organizational fleet. ... ('''[[Journal:Designing a knowledge management system for naval materials failures|Full article...]]''')<br />
For the release of precise and accurate reports of [[Medical test|routine tests]], its necessary to follow a proper [[quality management system]] (QMS) in the [[clinical laboratory]]. As one of the most popular QMS tools for process improvement, Six Sigma techniques and tools have been accepted widely in the [[laboratory]] testing process. Six Sigma gives an objective assessment of analytical methods and instrumentation, measuring the outcome of a process on a scale of 0 to 6. Poor outcomes are measured in terms of defects per million opportunities (DPMO). To do the performance assessment of each clinical laboratory [[analyte]] by Six Sigma analysis and to plan and chart out a better, customized [[quality control]] (QC) plan for each analyte, according to its own sigma value ... ('''[[Journal:Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study|Full article...]]''')<br />
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Revision as of 16:52, 29 April 2024

Fig1 Karaattuthazhathu NatJLabMed23 12-2.png

"Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study"

For the release of precise and accurate reports of routine tests, its necessary to follow a proper quality management system (QMS) in the clinical laboratory. As one of the most popular QMS tools for process improvement, Six Sigma techniques and tools have been accepted widely in the laboratory testing process. Six Sigma gives an objective assessment of analytical methods and instrumentation, measuring the outcome of a process on a scale of 0 to 6. Poor outcomes are measured in terms of defects per million opportunities (DPMO). To do the performance assessment of each clinical laboratory analyte by Six Sigma analysis and to plan and chart out a better, customized quality control (QC) plan for each analyte, according to its own sigma value ... (Full article...)
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