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This paper considers aspects of a series of complex issues involving unacceptable/unusual characteristics primarily in the context of USP's work but with implications for manufacturing science via considerations of process capability and Quality by Design and to measurement science.
This paper has three objectives: to explore the nature of the problem implicit in the term "risk acceptability," to examine the possible contributions of scientific information to risk standard-setting, and to argue that societal response is best guided by considerations of process rather than formal methods of analysis.
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We believe one reason for this is insufficient consideration of process management aspects such as process design, description, and deployment.
The solution approach utilizes Discrete Event Simulation (DES) to model the performance measure under consideration of process constraints and variability.
In this control design, equipment are grouped and segmented with a careiiil consideration of process system design, interaction, and operation.
Removing the composition dependency from the design problem enables the simultaneous consideration of process and product selection and optimization.
This work introduces an optimization-based approach to the simultaneous consideration of process safety and process scheduling during the design phase.
Such procedures have recently been extended to allow for the consideration of process variability within a catchment by a flood-type specific construction of design hydrographs.
In this work, property clustering techniques and group contribution methods are combined to enable simultaneous consideration of process performance requirements and molecular property constraints.
To obtain reliable flood estimates, there is a need for an approach that allows for the consideration of process variability in the construction of synthetic design hydrographs in ungauged catchments.
At the second tier, actual control actions are determined in consideration of process constraints by solving a QP problem, which is formulated by linearizing the nonlinear model around the LQI trajectory.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com