Plant Optimisation

Find that sweet spot the design team had in mind

Get the most out of your plant by trialling multiple scenarios in parallel plant simulations. Optimise set-points, start-up and shutdown procedures, batch process interactions, maintenance schedules, surge capacity and process control schemes.

Where is my bottle-neck? Why am I not achieving design production? Why are my operating costs higher than design? If a close examination of available plant data fails to identify an answer then simulation of the existing process can help. By flexing the virtual plant an understanding of fundamental causes is built up in the engineering team and a solution to the problem will usually become self-evident.

Once a systemic weakness in the existing process is identified trial solutions to the problem can be simulated in order to find an optimal outcome. For example a poor understanding of the water balance of a hydrometallurgical process will often result in poor recovery of metal values and high effluent treatment costs. Steady-state modelling of this plant would identify the problem within hours. Where a problem relates to transient events such as batch cycling, weather events or equipment down-time dynamic simulation will be more appropriate. Ultimately the solution in these cases may be as simple as modifying operating procedures, for example carbon handling routines in a CIL circuit, or effluent treatment rates during a low-rainfall period.

Our role in optimisation is to provide a means for your experts to visualise the effects of changes made to the process - be it a change of set-point, surge capacity, batch cycle time or operating procedure - without needing to make unsafe or impractical trial changes to the real operation.

Simple Example Scenario

Given the following system of first-order reactions:

$A+B \overset{k_1}{\longrightarrow} C$

$A+C \overset{k_2}{\longrightarrow} D$

$A+D \overset{k_3}{\longrightarrow} E$

optimisation of initial reagent concentrations and reactor residence time for maximum production of D is facilitated by comparing simulations of a range of starting conditions, two of which are illustrated below.

Solution A: Initial [A]:[B] = 5:1

Solution A shows generation of 0.25 M D in 9 minutes however at a much higher total gas pressure and at higher final concentration of E (a waste product) than in the second solution.

Solution B: Initial [A]:[B] = 1:1

Solution B requires 60 minutes to generate 0.20 M D but with the advantage of lower total pressure and lower final E. Depending on engineering and economic constraints, one or the other of these extremes will be more attractive and can be further optimised.

We bring a personal and effective approach to every project we work on, which is why our clients keep coming back.
Director & Principal Engineer, Oliver Kloiber-Deane BEng(Chem) MSc(Math)

Our Services

Steady-State Modelling Dynamic Modelling & Simulation Process Optimisation Operability Studies

Further Info

Fidelity

The degree of fidelity to reality required of a model should be judged carefully: the solution must be sufficiently accurate to correctly answer the questions posed without wasting time modelling features that have no significant impact on outcomes. For this reason process models built over the life of a project typically range from very simple at the desktop-study stage to highly detailed at the engineering and commissioning stages. Models may then continue to be evolved during plant operation in order to optimise the process for new feed-stock, de-bottleneck for greater throughput, etc.

Workflow

Close communication with our client and adherence to client specification documents (process design criteria, process flow diagrams, control philosophy, etc) is our standard approach. Client input is typically required on a range of issues throughout a modelling project. For example process modelling during a flow-sheet development stage often uncovers issues in the process design that had not yet been considered by the design team - commonly water balance, impurities build-up and related effluent treatment issues for hydrometallurgical flow-sheets.

We also find that a period of time spent in the same physical location as the client in the early stages of modelling a complex flowsheet can speed up delivery by removing communication delays.

Deliverables

Our typical deliverable is an electronic file containing neatly formatted process simulation output data and a report that illustrates the model flow-sheet; demonstrates the model's fidelity to the client's design criteria; lists and justifies any assumptions made; and provides a brief analysis of outcomes. If necessary a section will also illustrate any process risks and sensitivities that may have been uncovered. We are also happy to supply the live model files which thereafter allows the client to view and modify the models themselves.

Pricing

Please contact us with details of your job for an obligation-free discussion and a competitive quote. For a well-defined scope of work we are happy to offer a fixed price.

Contact Us

Please contact us for an obligation-free discussion of your needs.

PO Box 3354 Newmarket QLD Australia
info@elementrescon.com.au
+61 (0)408 949 793
elementrescon.com.au