In mining, construction and industrial crushing scenarios, the purchasing decisions for crusher parts are often simplified to an intuitive judgment that “the lower the unit price, the more cost-effective it is”. However, this single-dimensional assessment neglects the comprehensive consumption cost of parts during their actual service life – parts with the same unit price may have vastly different actual costs per ton of material processed due to differences in wear resistance, applicable working conditions, and maintenance frequency. Building a scientific “cost per ton” analysis model is the key to optimizing procurement strategies and balancing short-term expenditures with long-term benefits.
First, why is “unit price” not the only criterion? The implicit cost logic of fragmented scenarios
From the traditional procurement perspective, “unit price” only reflects the single expenditure when purchasing parts, but does not incorporate the hidden costs during their usage process: for instance, parts with low wear resistance may need to be replaced more frequently, leading to increased downtime and higher labor maintenance costs. Parts with poor compatibility may accelerate the wear and tear of other related components, indirectly increasing the overall operation and maintenance investment.
Take the mortar wall in a cone crusher as an example. If only two sets of parts with similar quotations are compared, it seems that the procurement expenditure is the same on the surface. However, if one set can only maintain a processing capacity of 2,000 tons when crushing high-hardness ores due to differences in material or heat treatment process and needs to be replaced, while the other set can stably support 5,000 tons, then the “cost per ton” of the latter is only 40% of that of the former. This difference will be significantly magnified in the long-term operation and may even become a core variable affecting the overall economy of the production line.
Second, the core calculation dimensions and data anchor points of the “cost per ton” model
To accurately calculate the “cost per ton” of crusher parts, it is necessary to establish an analysis framework that includes four key variables: the unit price of parts purchase, the theoretical service life (processing capacity), the additional costs related to maintenance, and the correction of the working condition adaptation coefficient.
1. Basic formula: Cost per ton = (Purchase unit price + maintenance additional cost)/Actual processing capacity
Among them, “Purchase unit price” refers to the direct cost of a single purchase expenditure. “Maintenance additional costs” cover hidden expenditures such as installation and commissioning labor, downtime losses (converted based on production capacity), transportation and warehousing. The “actual processing capacity” refers to the total material processing capacity of the part when it operates stably under specific working conditions (such as the wear threshold after processing 5,000 tons of ore on the mortar wall of a cone crusher).
2. Dynamic correction: Influence weight of the working condition adaptation coefficient
The hardness, moisture content and the proportion of impurities (such as clay and metal foreign objects) of different crushed materials will significantly change the wear rate of parts. For instance, the impact strength of granite (with a Mohs hardness of 6-7) on the jaw plate or hammer head is much higher than that of limestone (with a Mohs hardness of 3-4). The actual processing capacity of the same part under the former working conditions may decrease by 40% to 60%. Therefore, it is necessary to introduce a “working condition adaptation coefficient” based on the specific material characteristics – through historical operation data or laboratory simulation tests, determine the “effective processing capacity converted value” of the part under the target working conditions, and then correct the accuracy of the cost per ton.
3. Long-term perspective: The cumulative effect of costs throughout the entire life cycle
The “cost per ton” model also needs to take into account the impact of the replacement frequency of parts on the continuity of the production line. Frequent shutdowns for parts replacement not only increase labor and energy consumption (such as the no-load energy consumption of restarting a crusher), but also may lead to capacity waste in downstream processes (such as screening and conveying). After converting these hidden losses into the apportioned cost per ton of material, the originally “low unit price but short lifespan” parts may instead become more expensive options.
Third, the value of model application: The leap from passive procurement to active cost control
Through the “cost per ton” analysis model, purchasing decisions can shift from a single price comparison to a comprehensive benefit assessment:
For high-hardness material production lines: Give priority to choosing parts with slightly higher unit prices but better wear resistance (such as using high-chromium alloys or surface spraying processes). Although the single purchase expenditure increases, their longer service life can significantly reduce the allocated cost per ton of material.
For scenarios where multiple types of materials are alternately processed: The average working condition adaptation coefficient should be weighted and calculated based on the proportion of different materials to avoid chain losses caused by insufficient adaptability of a single part.
For long-term operating production lines: Verify the accuracy of the model through historical data backtracking (such as statistics on the actual processing volume and replacement frequency of similar parts in the past three years), and further optimize the procurement parameters (such as bulk purchasing of spare parts to reduce marginal costs).
The essence of this model is to convert “procurement costs” into a part of “operating costs”, helping decision-makers predict the economic viability of parts throughout their entire life cycle at the part selection stage. Thus, while ensuring crushing efficiency, more sustainable cost control can be achieved.
Conclusion
In the procurement decision-making of crusher parts, “cost per ton” is not merely a numerical calculation, but also a profound understanding of the production logic – it requires purchasers to break away from the habitual thinking of “unit price orientation”, and combine material performance, working conditions and long-term operational goals through quantitative analysis. When every expenditure can be clearly mapped to the actual consumption of each ton of material, the procurement strategy is upgraded from passive response to active optimization, ultimately providing a more solid support for the stable and efficient operation of the production line.
Post time: Nov-19-2025