User:Apipersburgh/sandbox

Process Engineering


 * References on the topic has been around the last 40 years
 * Some references are require more effort on the reader's part; might hurt the chances of someone wanting to go deeper on the subject.
 * Article carries several links that go more into detail of what is presented; provides a clear avenue into what a user might specifically want to focus on.
 * May be worth editing in another note P&IDs to clarify since its own Wikipedia article doesn't even include a reference to the information they present.

From the Article(in bold) with my edits

Manufacturing in the field of process engineering involves an implementation of process synthesis steps. Regardless of the exact tools required, process engineering is then formatted through the use of a process flow diagram (PFD) where material flow paths, storage equipment (such as tanks and silos), transformations (such as distillation columns, receiver/head tanks, mixing, separations, pumping, etc.) and flowrates are specified, as well as a list of all pipes and conveyors and their contents, material properties such as density, viscosity, particle-size distribution, flowrates, pressures, temperatures, and materials of construction for the piping and unit operations.

P&ID are meant to be more complex and specific than a PFD. They represent a less muddled approach to the design. The P&ID is then used as a basis of design for developing the "system operation guide" or "functional design specification" which outlines the operation of the process. It guides the process through operation of machinery, safety in design, programming and effective communication between engineers.

'''Process design: synthesis of energy recovery networks, synthesis of distillation systems (azeotropic), synthesis of reactor networks, hierarchical decomposition flowsheets, superstructure optimization, design multiproduct batch plants. Design of the production reactors for the production of plutonium, design of nuclear submarines.'''

Process control: model predictive control, controllability measures, robust control, nonlinear control, statistical process control, process monitoring, thermodynamics-based control. Denoted by three essential items, a collection of measurements, method of taking measurements, and a system of controlling the desired measurement.

Supporting tools: sequential modular simulation, equation-based process simulation, AI/expert systems, large-scale nonlinear programming (NLP), optimization of differential algebraic equations (DAEs), mixed-integer nonlinear programming (MINLP) , global optimization, quality function deployment (QFD)

Reference

https://www.aiche.org/sites/default/files/docs/webinars/BarkelB-PIDs.pdf