CLIENT case study

Albemarle

With presence in over 100 countries, Albemarle is a major enabler of lithium-reliant technologies that touch countless facets of people’s lives and entire economies. On engaging BSC Global, Albemale needed to pre-optimize throughput of resources that would flow within a newly planned Lithium Hydroxide processing plant in Kemerton, Western Australia.

THE CHALLENGE
Planning ‘just right’ operational investments

At face value, the challenge seemed straightforward enough. The new plant would be divided into two distinct sections, each processing one of two critical components for producing lithium hydroxide, with each of those sections operating a maximum of five processing trains.

Key goals:

  • Effective project cost management
  • Optimal plant productivity from day-one
  • Sustained resource utilization efficiency


The key question?: Given that the two sections operate at different rates, with different operating and maintenance regimes, how many operating trains would be required for maximizing the plant throughput, without inadvertently, creating cost redundancy and operational bottlenecks?


SOLUTION
Accurately simulating efficiency and value

Before a single piece of new plan infrastructure would be laid, Albemarle needed resolute certainty with reliable, real-world projections of utilization and performance.

To achieve this, BSC proposed and custom-developed a rich model of the entire processing plant anatomy that could be used to test and simulate all possible processing-train configurations under various design rates.

Once actualized, the simulation model outputs would leverage a risk management technique, known as Monte-Carlo analysis, that would consider randomized equipment downtimes to assess variability in performance.

The simulated production outputs would then combine OPEX, CAPEX, and revenue estimates to generate probable profitably values for each of the possible processing-train configurations.



SUMMARY OUTCOMES
Projected 24% increase in project value

The final simulation model developed by BSC was able to accurately predict the likely range and high-level economics required for Lithium Hydroxide Monohydrate production, as well as where in each train-processing configuration bottlenecks were likely to emerge.

The model also showed that, maximizing capacity in the Hydromet section specifically, would yield a project-value increase of as much as 24%.

Business Unit
Productivity Science
Company
Albemarle

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