Beyond Hardness: A Total Cost of Ownership and Application-Environment Framework for Wear Resistant Steel Selection in Indonesian Mining - Jordan Suharto (Politeknik Siber Cerdika Internasional, 2026)
Background: Wear resistant (WR) steel selection in Indonesian mining is typically driven by nominal hardness and unit price, criteria that overlook the dominant MRO cost drivers: service life, change-out frequency, and downtime. No published framework integrates application-environment classification, multi-grade benchmarking, mill test certificate (MTC) verification, and parametric Total Cost of Ownership (TCO) analysis for this context. Objective: This study develops a four-step evaluation framework connecting application environment, material technical parameters, quality verification, and lifecycle cost, applied to Indonesian coal and gold/copper-gold mining. Methods: A mixed-methods applied engineering evaluation combined: structured consultation with three informants — an end-user metallurgy manager at a Central Sulawesi gold operation and two mineral processing equipment OEM engineers — cross-checked against maintenance-scheduling records and throughput data; benchmarking of seven WR steel grades against manufacturer datasheets (JFE EVERHARD, Hardox 400/450) and a representative MTC; and a parametric 34-component TCO model with three-scenario (conservative, base-case, optimistic) sensitivity testing, supported by eight peer-reviewed sources selected on defined inclusion criteria. Results: Coal mining represents a continuous-abrasion environment requiring medium-to-high hardness with good weldability; gold and copper-gold mining represent high-impact, severe-abrasion environments requiring verified toughness alongside hardness. Across the representative component set evaluated and across all three sensitivity scenarios, downtime and installation cost reduction consistently outweighed material cost as the dominant driver of estimated annual savings. Notably, the upgrade pathway with the highest estimated saving (mild steel to NM400) involves a grade priced above the material it replaces, yet still generates the largest net saving through reduced shutdown frequency — indicating that unit price is not a reliable proxy for total ownership cost. These findings are outputs of a parametric simulation model and should be read as directional estimates pending field validation, not as field-measured results. Conclusion: WR steel selection should be treated as an integrated technical and operational decision, not a price-per-kilogram procurement exercise. The four-step framework offers decision-makers a replicable, low-cost screening tool — environment classification, material benchmarking, MTC verification, TCO evaluation — that procurement and maintenance teams can apply before formal investment decisions, shifting the basis of selection from a unit-cost basis toward evidence-based lifecycle cost. Field validation of downtime rates and actual service life remains the priority next step.