Repair vs. Replace: Using CMMS Data to Make the Multi-Million Dollar Decision

Every Maintenance Manager eventually faces the "Money Pit" dilemma.

Asset #42 (the old compressor) has broken down again. The repair will cost $5,000. You spent $3,000 fixing it last month. A brand new compressor costs $25,000.

Do you fix it again to keep production running today? Or do you fight for the budget to replace it?

This isn't just a maintenance decision; it is a Financial Strategy decision.

Without data, you are stuck begging for budget. Paula (the CFO) sees a request for $25,000 and says "No, just fix the old one."

With data, you can prove that fixing the old one is actually destroying the company's margins.

Here is how to move from "Gut Feeling" to "Data-Driven" asset lifecycle management.

The Problem: The "Sunk Cost" Invisible Leak

Legacy assets bleed money in three ways, and only one is obvious on a standard invoice.

1. Direct Maintenance Costs (Visible): Parts and Labor.

2. Energy Inefficiency (Hidden): Old motors and compressors often consume 20-30% more power than modern equivalents.

3. Unplanned Downtime (The Killer): The lost production profit while the machine is down.

If you only track #1, the machine looks "cheaper to fix." If you track #1, #2, and #3, the machine is likely costing you more than a replacement every 18 months.

The Strategy: The Data-Backed Argument

To win the "Replace" argument, you need to present a Total Cost of Ownership (TCO) curve.

You need a CMMS that tracks costs against the specific asset over time.

1. The "50% Rule" Report

Standard reliability logic suggests that if a repair costs >50% of the asset's current value, you replace.

How Fabrico helps: Fabrico stores the "Purchase Date" and "Purchase Value" in the asset profile. It also sums up the "Total Maintenance Cost Year-to-Date." You can instantly see if you are approaching that 50% threshold.

2. The "MTBF" Trend Line

A machine nearing end-of-life doesn't just break; it breaks more often. Its Mean Time Between Failures (MTBF) shrinks.

How Fabrico helps: Fabrico calculates MTBF automatically based on closed Work Orders. If you can show Paula graphs where the MTBF has dropped from "Every 3 Months" to "Every 2 Weeks," the reliability risk becomes undeniable.

3. The "Downtime Cost" Calculator

This is the nail in the coffin.

• Old Machine Downtime: 50 hours/year.

• Cost of Downtime: $1,000/hour (lost profit).

• Annual Loss: $50,000.

How Fabrico helps: By linking Maintenance to OEE, Fabrico captures the exact duration of downtime events. You aren't guessing "about 50 hours"; you have the timestamps to prove it.

The Workflow: From Chaos to CapEx

Stop having emotional arguments about budget. Follow this workflow:

1. Tag Every Asset: Use Fabrico to build a hierarchy. Every cost must be assigned to a specific machine (Parent), not just a "Line" or "Department."

2. Log Every Spare Part: Technicians must scan parts used. This captures the hidden "nickel and dime" costs of small repairs.

3. Review Quarterly: Pull the "Top 10 Cost Consumers" report in Fabrico.

4. Build the Case: Export the Asset History report. Attach it to your CapEx request.

Summary: Data Wins Budgets

The CFO doesn't care about bearings and seals. She cares about ROI (Return on Investment) and Risk.

When you use Fabrico to show that Asset A is consuming 115% of its replacement value in maintenance and lost production every two years, the decision to replace becomes automatic.

Stop fixing the money pit. Use data to bury it.

Ready to see your true asset costs?

See how Fabrico tracks Total Cost of Ownership and MTBF automatically.

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