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The utility of observability and redundancy in characterizing the performance of process data estimators was established in previous studies [10].
Generally, it is challenging to evaluate the performance of process designs on the basis of a large number of indicators.
We develop a distribution-free model to evaluate the performance of process flexibility structures when only the mean and partial expectation of the demand are known.
A knowledge of hydrodynamic characteristics is important because it helps in design, control, analysis, optimization, operation, and modelling of the system, which enhances the performance of process unit.
The objective of this work was to develop a model to evaluate the performance of process safety management systems of paint manufacturing facilities.
It is shown that these concepts are useful in characterizing the performance of process data estimators with regard to bias and uniqueness of an estimate, convergence of estimation procedures and the feasibility and implications of problem decomposition.
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The second goal is to use the OHS parameters to benchmark the performance of process-based hydro-geochemical (HG) models.
The detailed reaction kinetics and effect of reaction temperature on the performance of processes are fully analyzed.
When quantifying the performance of processes and assessing the effects of improvement projects, performance indicators are an essential tool (Leyer et al. 2015).
These external indicators are in the first place meant to measure the quality of data registry and in second place to measure the performance of processes (process indicators).
Both defined and complex media have been employed for PGA production, but no reported studies have addressed the influence of medium composition on the performance of processes used for PGA recovery from cell lysates.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com