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METTLER TOLDEO Announces a White Paper on

publication date: Dec 12, 2012
 | 
author/source: METTLER TOLEDO AG

METTLER TOLEDO today announced the release of a white paper on the topic of gravimetric sample preparation. It compares the advantages and disadvantages of gravimetric vs. volumetric sample preparation methods, with particular reference to recognizing and acting to reduce errors associated with each step in the sample preparation workflow

 

Gravimetric Sample PreparationAnyone working in a regulated analytical laboratory or a Quality Assurance (QA) / Quality Control (QC) environment will identify with the potentially costly and time-consuming process of investigating Out-of-Specification (OOS) results. More than 50% of OOS results in analytical workflows are reportedly caused by sample processing and operator errors. Implementing automated Gravimetric Sample Preparation and following Good Weighing Practice™ (GWP®) can help reduce data variability and OOS results. Consistent product quality is in direct correlation with validated weighing results, so it is important to ensure accuracy at all times. The issue is that a weighing error at the start of a process can be carried through multiple steps before a problem is identified.


Weighing and dilution errors can be removed by using automation to dispense solids and liquids. This allows precise concentrations to be prepared without relying on the human element, and ensuring that you are within the specifications. Commonly, 60% of FTE time in an analytical laboratory is spent on sample processing, a tedious and time-consuming job.


On top of this, many laboratories tend to test their weighing equipment too often and perform the wrong kinds of tests, further reducing the productivity of their scientists.


the new white paper compares gravimetric dispensing to traditional volumetric methods and gives insight into innovative ideas to help you simplify your work and free more time to concentrate on more productive tasks.


The white paper can be downloaded at: www.mt.com/whitepaperGSP


 



 

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