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BlendOpt configured for manganese

Manganese Mining Optimisation: Stockpiles, Processing and Product Portfolio

Simultaneous optimisation of process feed control strategies, stock inventories and product portfolio using BlendOpt.

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Manganese operations can have a high level of complexity associated with ROM stocks and quality management, with implications for contract delivery, sales and the overall product portfolio.

Plans for processing, stockpiling, satisfying contractual requirements and product portfolio optimisation are difficult to align with enterprise objectives if each planning activity is developed separately instead of holistically. In practice, value-chain optimisation is only achievable through integrated planning. By integrated planning, we mean coordinated planning of decisions from run-of-mine (ROM) stocks through processing, logistics and sales. While the importance of integrated planning is recognised, its execution is difficult without the right tools to support this process.

BlendOpt is Paradyn’s configurable optimisation platform. Configured for manganese, it is the first mathematical optimisation software tool that supports complete integrated planning of sales and manganese value-chain strategies. Starting with the mine schedule as an input, BlendOpt discovers strategies for how product should be processed, blended and allocated to different product concentrates, with the objective of maximising profit while satisfying contract specifications.

Mathematically optimised plans are created using algorithms that test thousands of possible plans in search of the highest profit from the data provided.

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Decision support

BlendOpt for manganese mining and processing

The BlendOpt solution has been engineered to manage the complexity of the manganese value chain, and can support decision making in the areas listed here.

  • Mn
  • Fe
  • P
  • SiO2
  • CaO
  • Mg:Fe ratio
  • sale price penalties
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BlendOpt’s Collaborative Mathematical Optimiser (CMO) →
  1. 01
    Manage price volatilityIn recent years manganese ore price volatility has been quite high. BlendOpt can help manage volatility by supporting decision makers within the operation to make high-quality, cost-effective decisions in the context of unpredictable price changes, leading to dependable quality outcomes.
  2. 02
    Simplify ROM stockpilingManganese operations can have an unnecessary level of complexity in their stock yards. With BlendOpt’s Collaborative Mathematical Optimiser (CMO) it is possible to discover ROM stockpiling strategies which simplify reserving decisions and eliminate complexity while still providing robust quality control.
  3. 03
    Feasible plant feed streamsBlendOpt can generate schedules and plans that support feed streams to processing plants that satisfy operational constraints.
  4. 04
    Align multi-horizon contractsBlendOpt aligns multi-time-horizon contracts (for example, 1-year to 5-year contracts) and integrates these contractual obligations with scheduled activities.
  5. 05
    Satisfy every quality constraintSatisfy all of your value-chain quality constraints, including Mn, Fe, P, SiO2, CaO, Mg:Fe ratio and many others that impact processing, while minimising the impact of sale price penalties. BlendOpt can incorporate complex penalty functions and quality constraints and discover integrated schedules and plans that maximise the revenue potential of your operation.
  6. 06
    All of it, simultaneouslyBlendOpt can do all of the above, and much more, simultaneously, so decisions for one objective are not in opposition to another at different decision points or points in time, but align silos across the operation.
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Tell us about the decision you are trying to make. We will show you how BlendOpt models it, whether you license the platform, commission a study, or have our specialists run it for you.

  • Do you optimise product placement into the market?
  • Can you spot when demurrage is value-justified?
  • Do you know when your stockpile quality models increase contract rejection risk?
  • Does your planning software assume stable operations and predictable markets?
  • Can you run scenarios quickly to understand your options?
  • Does your tactical schedule stay in sync with your longer-term plans?
  • Do your schedules reflect conditions on the ground?
  • Are your schedules thrown out on day one?