1006 XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3
process’s limitations, and then develops a tailored imple-
mentation plan to streamline changes as shown in Figure 3
(Chandramohan 2021).
An optimization study begins with discerning the
opportunities that add value to the process. This is impor-
tant as it sets the focus of the assessment and aligns stake-
holders on achieving a set of targets. A baseline is developed
from operational data and used to understand the process,
gaps in knowledge, and any significant risks. If opportu-
nities are not apparent, the process can be benchmarked
against similar operations to determine the potential for
improvement. Once the value has been defined, the optimi-
zation can then identify the constraints preventing the plant
from achieving its goals. Constraints can come in a variety
of forms including process control, equipment limitations,
or even management. Following the Theory of Constraints,
baseline models can be used to diagnose issues and evalu-
ate the effects of operational changes. The most common
issues typically arise from ignoring the basics, poor control,
incorrect key performance indicators (KPIs), or the lack of
stability (Chandramohan 2021). Once potential technical
solutions are determined, they must be assessed based on
the relevant performance metric before being accepted into
the implementation plan. The balance between economic
feasibility and achieving the desired targets will determine
the value of the changes and which solutions will proceed.
The implementation plan can take a variety of pathways
depending on the overall goals of the study as shown in
Figure 4. Successful implementation plans depend on
effective communication, stakeholder alignment, and
building trust to deliver results (Lane 2007).
Example—Optimization of a Simple Leach Circuit
Mineral processing plants looking to perform ESG opti-
mization can utilize Ausenco’s Process Optimization
Framework with the following focusing questions:
• What opportunities are there to add economic or
ESG value to the process?
• What is constraining the existing process from
achieving an optimized state?
• What solutions are available to mitigate the risk and
how much capital is required?
• Do the proposed changes make sense when balancing
the time-value of money and goals of the operation?
• Is their sufficient alignment amongst stakeholders to
implement these changes?
Take a simple leaching circuit operating on electricity
supplied by a diesel generator as an example (Figure 5).
Operations suspects the circuit may be underperforming
resulting in higher emissions and costs. An optimization
study is initiated with the intent to reduce emissions and
minimize operational expenditure. Using process instru-
mentation data, a mass and energy balance model is
developed to baseline the process and confirms the poor
performance of the circuit relative to industry benchmarks.
A constraints assessment is then performed which identi-
fies poor agitation to be causing lower leaching kinetics
Figure 3. The Ausenco optimization pathway which looks to define the value, understand the constraints, and develop a
quantitative implementation plan
process’s limitations, and then develops a tailored imple-
mentation plan to streamline changes as shown in Figure 3
(Chandramohan 2021).
An optimization study begins with discerning the
opportunities that add value to the process. This is impor-
tant as it sets the focus of the assessment and aligns stake-
holders on achieving a set of targets. A baseline is developed
from operational data and used to understand the process,
gaps in knowledge, and any significant risks. If opportu-
nities are not apparent, the process can be benchmarked
against similar operations to determine the potential for
improvement. Once the value has been defined, the optimi-
zation can then identify the constraints preventing the plant
from achieving its goals. Constraints can come in a variety
of forms including process control, equipment limitations,
or even management. Following the Theory of Constraints,
baseline models can be used to diagnose issues and evalu-
ate the effects of operational changes. The most common
issues typically arise from ignoring the basics, poor control,
incorrect key performance indicators (KPIs), or the lack of
stability (Chandramohan 2021). Once potential technical
solutions are determined, they must be assessed based on
the relevant performance metric before being accepted into
the implementation plan. The balance between economic
feasibility and achieving the desired targets will determine
the value of the changes and which solutions will proceed.
The implementation plan can take a variety of pathways
depending on the overall goals of the study as shown in
Figure 4. Successful implementation plans depend on
effective communication, stakeholder alignment, and
building trust to deliver results (Lane 2007).
Example—Optimization of a Simple Leach Circuit
Mineral processing plants looking to perform ESG opti-
mization can utilize Ausenco’s Process Optimization
Framework with the following focusing questions:
• What opportunities are there to add economic or
ESG value to the process?
• What is constraining the existing process from
achieving an optimized state?
• What solutions are available to mitigate the risk and
how much capital is required?
• Do the proposed changes make sense when balancing
the time-value of money and goals of the operation?
• Is their sufficient alignment amongst stakeholders to
implement these changes?
Take a simple leaching circuit operating on electricity
supplied by a diesel generator as an example (Figure 5).
Operations suspects the circuit may be underperforming
resulting in higher emissions and costs. An optimization
study is initiated with the intent to reduce emissions and
minimize operational expenditure. Using process instru-
mentation data, a mass and energy balance model is
developed to baseline the process and confirms the poor
performance of the circuit relative to industry benchmarks.
A constraints assessment is then performed which identi-
fies poor agitation to be causing lower leaching kinetics
Figure 3. The Ausenco optimization pathway which looks to define the value, understand the constraints, and develop a
quantitative implementation plan