Reference ID: MET-4E75 | Process Engineering Reference Sheets Calculation Guide
Introduction & Context
In size-reduction circuits, hammers, screens, and rolls lose mass and geometry through impact, abrasion, and fatigue. Predicting the hours between replacement avoids unplanned shutdowns, balances spares inventory, and sets realistic maintenance budgets. The worksheet below converts three material indices—throughput T, abrasiveness A, and hardness H—into a first-order life estimate for each wear part. It is intended for front-end engineering checks, maintenance scheduling, and as a feeder to reliability-centred maintenance (RCM) packages.
Methodology & Formulas
Life is treated as a deterministic inverse proportionality between a calibrated constant and the damage driver. Abrasion dominates hammer and roll wear; hardness dominates screen wear. Mesh size is used only for range validation, not for life calculation.
Roll life: \( L_{\text{r}} = \dfrac{C_{\text{r}}}{T \cdot A} \)
Empirical Validity Windows
Parameter
Symbol
Unit
Lower Limit
Upper Limit
Throughput
T
tons h⁻¹
1
10
Abrasiveness index
A
dimensionless
1
5
Hardness (Mohs)
H
dimensionless
1
10
Screen mesh
M
mm
0.5
5
Constants C are back-calculated from field data and carry units that cancel to leave life in hours. Replace them with site-specific regression values when higher accuracy is required.
Start with the OEM’s recommended life, then refine using your own data:
Collect MTBR (Mean Time Between Replacement) from the last 12–18 months.
Adjust for duty cycle changes, feedstock abrasiveness, and lube or cooling upgrades.
Run a Weibull analysis on failure times to find the 10% failure probability point; schedule replacement just before this point to balance risk vs. utilization.
Lock the final interval into the CMMS as a time-based trigger, but add a vibration or temperature alarm as an early-warning override.
Advance the shutdown when any of the following occur:
Rate of wear debris doubles in weekly oil analysis.
Surface temperature rises >15 °C above baseline under identical load.
Dimensional check shows 80% of allowable wear limit reached.
Acoustic emission or ultrasonic trending exceeds the “yellow” control limit two consecutive readings.
Use a risk-based min-max model:
Calculate lead time × daily failure probability × daily downtime cost to get expected loss.
If expected loss exceeds the carrying cost of one spare, stock one; if not, rely on vendor consignment or 24 h delivery contract.
Review quarterly as failure data and lead times evolve.
Prioritize by the “cost of wear index”:
(Annual replacement cost + Lost production during downtime) ÷ hours of life.
Rank components; upgrade the top 20% using higher-grade alloys, ceramic liners, or surface hardening.
Validate with a six-month pilot on one unit before fleet-wide roll-out.
Worked Example: Wear Parts Replacement Schedule
A processing plant operates a grinding mill that uses three critical wear parts: the head liner, the screen, and the rotor. The engineering team wants to estimate the annualized cost of replacing these parts over a 5-year planning horizon, taking into account their individual lifetimes and replacement costs.
Knowns
Cost of head liner, \(C_h = 1000\) USD
Cost of screen, \(C_s = 800\) USD
Cost of rotor, \(C_r = 1200\) USD
Planning horizon, \(T = 5\) years
Adjustment factor for operating intensity, \(A = 3\)
Baseline intensity factor, \(H = 4\)
Screen mesh count (used for reference), \(screen\_mesh = 2\)
Lifetime of head liner, \(L_h = 66.667\) hours
Lifetime of screen, \(L_s = 40.000\) hours
Lifetime of rotor, \(L_r = 80.000\) hours
Step-by-Step Calculation
Calculate the cost per operating hour for each wear part:
\[
\begin{aligned}
C_{h,hr} &= \frac{C_h}{L_h} = \frac{1000}{66.667} = 15.000\ \text{USD/h} \\
C_{s,hr} &= \frac{C_s}{L_s} = \frac{800}{40.000} = 20.000\ \text{USD/h} \\
C_{r,hr} &= \frac{C_r}{L_r} = \frac{1200}{80.000} = 15.000\ \text{USD/h}
\end{aligned}
\]
