After improved control comes
optimisation, the capability of pushing the process towards desired goals such as higher yield, higher throughput, greater efficiency, more consistent quality, less waste...or any combination of these.
Importantly, there is a simultaneous requirement to obey limits on multiple process variables; these may be due to the product specification, process equipment or production constraints. A model-based optimiser is used to seek out the most economical solution, whilst honouring all these limits.
Using configurable templates for model, constraint and cost function entry, the user can quickly determine the optimal mode of operation for both batch and continuous manufacturing processes.
Explore optimisation scenarios that show the best solution possible, as well as the lost opportunity from
not implementing the optimal strategy.
Key features include:
Easy configuration of the model, constraint limits and cost function
Model selection and constraint limits can be linked to tags for programmable configuration
Throughout development to manufacturing, data is key to enable rapid response to market demand. The knowledge to enable intelligent decisions and the wisdom to optimise the complete product lifecycle is now at your fingertips. The latest release of PerceptiveAPC v8.0 delivers the next
PD2M May 18-20 2021 Virtual This is the place to explore what pharmaceutical manufacturing will look like in 2030, sharing discussions on new ways to develop medicines. How will Industry 4.0 enable us to respond to market demand, delivering flexible, modular manufacturing and bringing
18-19 May 2021 Virtual Perceptive Engineering - an Applied Materials company - is looking forward to participating in the Bionow Pharma Manufacturing Conference 2021. We will be joining AstraZeneca and Bristol Meyers Squibb in session 2, discussing the ‘Digitisation of Pharma
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