Evidence-first editorial standard
This guide separates observed facts, engineering assumptions and data that still require confirmation. It does not promise a universal service life or replace the exact product data and project specification.
Why this page contains no figures
A life-cycle cost is specific to one plant: your production value per hour, your labour rates, your crane and scaffolding costs, your shutdown frequency and your safety rules. Any supplier publishing a universal cost comparison is publishing their own assumptions, not your economics. What follows is the method, so that the numbers you put into it are yours and the result is defensible internally.
Build the cost of one replacement cycle first
Add the lining material, the consumables, the labour hours including access and preparation, the equipment needed to reach the surface, the disposal of the removed material, and the production not made while the asset is down. In most bulk-handling plants the last item dominates all the others combined — which is why a lining that halves the number of interventions can be worth several times its purchase premium even if it costs more per square metre.
Express everything per unit of service, not per purchase
The comparable quantity is cost per operating hour, or per tonne handled, over the period between interventions. This is the step that reverses many intuitive conclusions: a cheaper material replaced twice as often is more expensive on both counts, while a premium construction that only pays off if it lasts three times longer must be treated as an assumption to verify, not a saving to book.
Count the interventions you avoid, and the ones you add
A construction that can be repaired locally without stopping the line, or replaced in defined zones rather than wholesale, changes the intervention count and not just the unit price. Conversely, a method requiring hot-work permits, confined-space entry or a longer cure window may add planning cost and outage time that never appear on the material quotation.
Handle uncertainty honestly instead of hiding it in an average
You will not know the service life of a new construction in your duty. Rather than adopting a supplier figure, run the calculation across a range — pessimistic, expected and optimistic intervals — and see whether the decision changes. If the conclusion holds across the whole range, the decision is robust. If it only holds at the optimistic end, you are buying a hypothesis, and a controlled trial area with a measured baseline is the cheaper way to test it.
Record the baseline so the next calculation uses evidence
Note the installation date, the construction used per zone, dated photographs, reference measurement locations and the condition at each inspection. After one or two cycles the intervals in your model stop being assumptions and become site data. That record is what turns life-cycle costing from a procurement argument into a reliability tool — and it is worth more than any figure a supplier could have published here.