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Process optimization is the discipline of adjusting a process so as to make the best or most effective use of some specified set of parameters without violating some constraint. Common goals are minimizing cost and maximizing throughput and/or efficiency. Process optimization is one of the major quantitative tools in industrial decision making.
The challenge to date with PAT for pharmaceutical manufacturers is knowing how to start. A common problem is picking a complex process and getting mired in the challenge of collecting and analyzing the data. The following criteria serve as a basic framework for successful PAT roll-outs: (From A PAT Primer) Picking a simple process.
This model does however still have a number of unknown free parameters which can be estimated using system identification. [5] [6] One example [7] uses the Monod saturation model for microbial growth. The model contains a simple hyperbolic relationship between substrate concentration and growth rate, but this can be justified by molecules ...
A process capability analysis may be performed on a stable process to predict the ability of the process to produce "conforming product" in the future. A stable process can be demonstrated by a process signature that is free of variances outside of the capability index. A process signature is the plotted points compared with the capability index.
Process design then proceeds on the basis of the flow sheet chosen. Physical property data are the other component needed for process design apart from a flow sheet. The result of process design is a process flow diagram, PFD. Detailed engineering for the project and vessel specifications then begin. Process flowsheeting ends at the point of ...
The engineering design process, also known as the engineering method, is a common series of steps that engineers use in creating functional products and processes. The process is highly iterative – parts of the process often need to be repeated many times before another can be entered – though the part(s) that get iterated and the number of such cycles in any given project may vary.
One way to determine the parameters for the first-order process is using the 63.2% method. In this method, the process gain ( k p ) is equal to the change in output divided by the change in input. The dead time θ is the amount of time between when the step change occurred and when the output first changed.