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Crushing Performance Optimization

Achieving the highest percentage of quality in-demand product at the lowest cost with the least amount of waste.

By Alan R. Bessen and Sam Sawant

This is the second of a three-part series on crushing measurement and analysis. – Ed.

Performance Optimization: Pursuit of the point in your operation that yields the highest percentage of quality in-demand product at the lowest cost with the least amount of waste. It appears throughout the aggregates industry that management priority has shifted toward regulatory and corporate compliance; often resulting in a reactive approach to managing performance, too often with objectives limited to simply keeping the plant running.

There is no debate that compliance with environmental, safety, permitting, budgeting and personnel management priorities are all necessary. However, it is clear that the economic viability of an aggregates plant and its continued operation depend on profitability. Merely keeping the plant running regardless of effectiveness or profitability is simply not an acceptable performance objective.

Managing performance, maximizing saleable tons and minimizing surplus inventory reduces cost and increases profit. Operating performance directly relates to operating cost; operating cost and production yield directly relate to profitability. As an aggregates manager your job certainly includes regulatory and corporate compliance but must not neglect managing the performance of your process.

Accurate evaluation of the present state of your process is necessary to effectively manage it. The more accurate and timely data is, the higher the likelihood intended results will be achieved. By analyzing data from within the production process you pursue optimization by minimizing production losses and balancing production, sales, inventory and operating cost to achieve optimal profitability.

Identify and Minimize System Limitations
Developing and validating your process model provides product yield and capacity data for various operating configurations or modes. Most aggregate operations will define at least three standard operating modes generally intended to maximize yield of coarse aggregate sizes, medium aggregate sizes or fine aggregate sizes. It should be expected that, at minimum, between three and 10 operating modes could be defined in most aggregate plants depending on diversity of design and on market requirements. Some large plants will have more than 10 common modes; a few plants, limited by deposit, market or design will operate in a single mode.

It is not uncommon to find that those processes that have not been modeled or have not properly validated their model operate in what can be described as a “Universal Setup” or mode. This is often by default because they have no practical modeling capability to establish what they should be producing and no practical measurement to establish what they are producing. This generally results in reactive scheduling of overtime to compensate for material shortages, repeated inventory corrections, excessive production of by-product and higher than necessary unit production costs.

It is common in development of the flow model to establish the Design Rate or maximum in-feed rate for each mode. However, it is critical to avoid confusing Design Rate with Average Rate. The Design Rate as established by the flow model defines the maximum theoretical tph rate of any given mode. The Average Rate is the expected average tph during the time the plant is actually operating.

Individual product rates for each mode divided by the in-feed rate for the same mode provides a percentage yield for each product. Product percentage rates for each mode multiplied by the projected average in-feed rate define the average ton per operated hour for each product.

The next step in defining process capability is to establish a daily operating schedule including number of shifts, scheduled hours per shift and actual operated hours during scheduled production. Applying forecast operating hours to yield rates established for selected modes defines the expected production capability of the crushing and screening process.

The final step is to ensure that pit capacity can be scheduled to supply material at an appropriate rate for each operating mode. If not, then your system is limited by pit capacity and evaluation of improvement potential should occur in that area. If so, then each mode should be evaluated for potential improvement. Improvement plans are developed and implemented incrementally, results are verified and a new rate and yield capability is established for each mode.

Pursuing Market Demand
Monthly projections of expected sales are critical to effectively manage both cost and profit. Sales cannot occur if adequate inventory is not available to meet customer requirements for volume and timing. Without a reasonably accurate sales forecast there is no clear target for production to pursue and therefore no short-term ability to judge the effect of current operating performance on future sales and cost expectations.

It can be seen in Figure 1 that pursuing projected sales tons without attempt to balance product yield with sales mix generates an inventory increase of 477,440 tons to achieve the 1 million tons of forecast sales. Figure 2 shows the effect of this surplus production on operating cost and on margin.

Figure 3 shows an idealized balance with an operating cost reduction and increased margin of almost $4 million; demonstrating the significant value lost by operating blindly, driven to achieve sales tons without consideration of the cost/profit impact of the unmanaged balance between sales mix and product yield.

It is interesting to note that much of the cost impact resulting from an out of balance process often gets lost within accounting systems that allocate production credit. The result is a short-term positive accounting profit while consuming massive amounts of working capital; at least until rules change and inventory caps are imposed to force accurate reflection of production costs and profit.

By comparing Figure 2 and Figure 3 it becomes clear that the point in an operation that yields the highest percentage of in-demand product at the lowest cost with the least amount of waste is the point which provides the optimal balance between product yield and sales mix.
Achieving this in an aggregates operation requires:
1. Development of a valid process model accurately reflecting the impact of changes in setup on the yield and capacity of the production system.
2. Current and dynamic sales forecasting driving monthly production, inventory, cost and profit.
3. Timely measurement and management of current performance.
4. Strategic marketing and sourcing with consideration for deposit, process and cost issues.

The job of an enlightened operations manager is to maximize profit by managing performance, cost and the sales production mix; it is not just to make tons.

Minimizing Waste and By Product
The chart shown as Figure 4 demonstrates how variation in equipment configuration and flow can affect demand product (3/8-in.) yield as well as the yield of waste and by-product (Scr).

It is clear from the data that minimum by-product yield occurs when coarse products are allowed to flow to stockpile. Re-crushing creates a dramatic increase in by-product yield while the re-crushed 3/4-in. and 5/8-in. product yields drop to 5 percent or less.

It can also be seen in Figure 4 that 3/8-in. product yield increases from 13 percent to nearly 25 percent by re-crushing various combinations of non-demand products. However, with screenings yield increasing from 16 percent to 23 percent, in approximate correlation to the yield of 3/8-in. product, it will ultimately become necessary to recognize, address or accept added cost associated with re-stockpiling, reprocessing or wasting by-product tons created while optimizing demand product yield.

Care in mode selection and accuracy in yield evaluation is critical to managing both demand product and by-product yield. Equipment selection, operating condition and plant design must also be considered in any effort to minimize waste and by-product both in existing plants and in the design of new processing systems.

Managing Inventory Surplus and Shortage

Accurately establishing process capabilities in appropriate configurations enables daily production to be scheduled with reasonable expectation of what will be produced. Figure 5 and Figure 6 provide examples of basic data sheets used for calculating expected production by operating mode.

In Figure 5, max tph-opr is determined by field measurement or from the flow model and represents the maximum or design capacity for each mode. The tph factor is applied to the design factor to represent the expected average tph for each hour that a plant actually operates. Percent yield factors are also obtained from the flow model or field measurement.

In Figure 6, scheduled hours of operation are reduced by the percent uptime factor to calculate the expected hours of actual production.

Neither scheduled nor operated production hours should be confused with scheduled labor hours which includes pre-shift inspection, scheduled breaks, end of shift clean out, etc. Scheduled labor hours must always be greater than production hours.

Pursuing the combination of modes and operating schedules that yield the highest percentage of in-demand product with the least amount of waste and by-product invariable results in the lowest cost per ton.

However, it is also invariable that normal operations require the plant to run out of balance to meet sales commitments. It should be expected, that sales will generate adequate revenue to offset costs and maintain the projected profit margin.

When they don’t, it is usually a result of inadequate communication between sales and operation regarding process capacity, yield limits and marketing commitments.

Without acceptable sales and process forecasts the plant is driven blindly by short-term sales demand without realistic regard for managing production cost. Appropriately forecasting production and sales makes it possible to effectively project inventory shortages and surplus months ahead enabling adjustment to both sales sourcing and to production schedules.

Optimal performance comes from measuring and managing your processing equipment and flow configuration. Optimal profit comes from balancing plant performance and capacity with sales demand.

Keep in mind that even a butcher knows before he starts that there is a limited quantity of filet mignon available in his process. He knows that there will be a lot more hamburger along with various roasts and steaks. He also knows that there is a significant amount of hoof, hide and miscellaneous waste. The butcher learns to price and plan accordingly.

Without an effective means of forecasting there is no practical means of creating a common understanding
of capabilities and limits among sales and operations managers and therefore no hope of optimizing profit.

The spreadsheet shown as Figure 7 is a simplified example of the basic details included in modeling and balancing sales, production, inventory and cost. Key sales, production and inventory details are projected months ahead.

Results are used to adjust schedules, modes, sales sourcing and pricing with a common target of
optimizing profit.

The final segment in this three-part series on performance management will describe both manual and technology based methods of measurement and management of aggregates performance and will include:

  • Advanced performance measurement using real-time belt scale systems.
  • Basic trending and control chart applications showing acceptable and problematic variability.
  • Statistical methods of establishing and monitoring KPI’s.
  • Web based management interface, reporting and alarming technology.

Alan R. Bessen, P.E., is a process-design, automation and performance optimization consultant with more than 35 years of experience in the aggregates and mining industries.  He can be reached at This email address is being protected from spambots. You need JavaScript enabled to view it. .

Sam Sawant has more than 30 years of experience developing new and innovative products for the aggregate and mining industries. He holds two masters degrees in Mechanical Engineering, and worked with Nordberg Inc. before starting Innotech Solutions in January of 2000. He has extensive experience analyzing mining and aggregate circuits, proposing substantial improvements and implementing the changes that have met or exceeded customers’ expectations. He can be reached at This email address is being protected from spambots. You need JavaScript enabled to view it. .