How to Reduce Maintenance Costs | Augury

Your asset list keeps growing, your maintenance budget keeps shrinking, and now leadership wants to know where you can spend less. The pressure is real, but blindly cutting your spending can impact your machine uptime. The good news is that most maintenance programs have more room to reduce spend than teams realize, without touching reliability.

This guide walks you through five practical maintenance cost reduction strategies to lower your costs while keeping production running, no full-scale overhaul required.

Key highlights:

• Maintenance costs are the expenses required to keep production assets running reliably, spanning labor, parts, contractors, software, and downtime losses.
• Prioritizing assets by criticality means your best resources go where they matter most.
• Shifting from reactive to planned maintenance is one of the highest-impact moves for reliability teams.
• A machine health platform gives your team the data to schedule work around actual asset health, reducing emergency repairs and extending equipment life.

What are maintenance costs in the manufacturing industry?

Maintenance costs in the manufacturing industry are the expenses required to inspect, service, repair, and monitor equipment so that production assets continue to operate reliably. Managing these costs helps you support uptime, control spending, and align maintenance activity with production goals.

Of the five types of maintenance costs, downtime-related ones are the hardest to track. An unplanned failure doesn’t appear as one line item. It ripples across labor, parts, and lost production at once. That’s why a complete cost picture matters before you start cutting.

Maintenance cost control challenges

You’re likely fighting a few of the same challenges as every other plant. None of these mean your program is broken. They’re just where the money quietly leaks. Recognizing where costs are leaking and why is the first step toward addressing them:

• Reactive maintenance: Shifting even a portion of unplanned repairs to scheduled work cuts emergency labor, expedited parts costs, and collateral equipment damage. Most programs move the needle here without a full-scale transformation.
• Poor planning and scheduling: Tightening how your team plans, schedules, and sequences work is one of the highest-leverage changes a reliability team can make and one of the easiest to start without new tools or headcount.
• Inefficient spare parts management: Auditing inventory against actual failure patterns typically surfaces both dead stock tying up capital and gaps that force emergency procurement. Closing that gap on even a handful of high-cost parts compounds into meaningful savings over a year.
• Limited machine visibility: Adding real-time visibility into asset health reduces the time your team spends chasing problems that were already developing and gives them the confidence to act before a fault becomes a failure.

5 maintenance cost reduction strategies

You already know costs are climbing. The hard part is knowing where to push without risking uptime, but you don’t have to choose between the two. The right maintenance cost reduction strategies get you both. The stakes are clear: in ITIC’s Hourly Cost of Downtime Survey, 41% of respondents said a single hour of downtime costs them from $1 million to over $5 million.

Let’s break down five strategies to help you get control of your spending.

1. Establish your maintenance cost baseline

Getting control of your costs starts with knowing where your money is going. Map your maintenance spend by asset, work order type, and department before you cut anything. Here’s how to break your maintenance costs down systematically:

1. Organize spending by asset, work order type, and department
2. Flag your top cost drivers and compare them against production output
3. Set a documented baseline to measure future changes against

2. Prioritize your assets by criticality

Your best resources deserve to go where they’ll have the biggest impact. Asset criticality scoring gives you a structured way to rank assets based on their effect on safety, production throughput, and cost if they fail. To build your tiering:

1. Score each asset based on its impact on safety, throughput, and replacement cost
2. Group your asset portfolio into critical, important, and general tiers
3. Align your maintenance strategy and resource allocation to each tier

3. Minimize reactive and unnecessary maintenance

Every repair you move from unplanned to planned puts money back in your budget. An emergency breakdown can lead to overtime rates, rushed parts orders, and damage to whatever is next to the failed asset. The same fix, scheduled, costs a fraction of that and barely touches production.

Reducing reactive maintenance starts with understanding where it’s concentrated:

• Audit your last 12 months of work orders and calculate the share that were unplanned
• Identify assets generating the most emergency callouts
• Move assets to a condition-based or scheduled maintenance cadence

Case in point: at Nestlé Purina’s Hartwell facility, the team caught a critical motor fault early enough to schedule the repair, avoiding eight hours of downtime and $117K in lost production.

4. Improve your maintenance planning and parts management

The less your team scrambles on the day of a job, the less it costs. When the parts are staged, the permits are pulled, and the sequence is confirmed in advance, your technicians spend their time fixing equipment, not tracking down what they need. Start with tightening your spare parts inventory strategy. Overstocking ties up capital and inflates storage costs, while understocking forces delays and premium-priced emergency procurement.

Pair smarter strategic spare parts planning with better scheduling practices for savings that compound over time. This approach includes:

• Stacking work orders
• Coordinating shutdowns
• Reducing technician travel time

5. Use predictive maintenance to target the right work

Knowing exactly what each of your assets needs, and when, eliminates the cost-versus-reliability trade-off. Predictive maintenance in manufacturing uses real-time machine data to flag developing faults before they cause failures, so maintenance is scheduled based on each asset’s actual needs. That leads to fewer emergency repairs, less unnecessary preventive work, and a maintenance schedule built around the machine’s actual condition.

Follow these steps to get started:

1. Deploy continuous condition monitoring on your highest-criticality assets
2. Use fault detection and diagnostics to pinpoint what’s wrong and why
3. Build your maintenance schedule around actual asset health data

When DuPont made the shift from route-based maintenance to predictive maintenance with Augury, they achieved 7x ROI in under a year, with 100% accuracy on fault predictions.

How predictive maintenance solutions reduce maintenance costs for manufacturing equipment

The benefits of a predictive maintenance solution are wide-ranging, but they all start from the same place: real data about what your assets actually need. According to Deloitte, well-executed predictive maintenance solutions can reduce facility downtime by 5%-15%.

Predictive maintenance helps you:

Lower instances of emergency repairs and overtime

With a predictive maintenance strategy in place, your team spends more time on planned work and less time responding to unplanned failures. In our Machine Health Is Business Health report, 28% of manufacturers cited unexpected equipment failures as the biggest risk to meeting their production targets. Fewer surprises mean lower labor costs, less overtime, and a team that isn’t constantly in firefighting mode.

Identify the correct repair sooner

Early fault detection means you identify the exact fix faster, without costly trial and error. Fault detection and diagnostics help pinpoint what’s wrong and where, giving your technicians a clearer starting point before they ever set foot on the floor.

A prominent building materials manufacturer using Augury identified a developing fault early enough to schedule the repair, avoiding a failure that would have cost roughly $6.5 million in downtime and lost production.

Limit secondary equipment damage

Catching a developing fault early protects more than just the at-risk asset. Left undetected, many failures spread to connected components, turning a manageable repair into a much larger and more expensive one. Predictive maintenance stops small issues from cascading into line-wide failures.

Extend useful asset life

Getting more years out of your existing equipment is one of the most direct ways to reduce your overall maintenance cost base. With continuous insight into asset health, your team intervenes early, reducing wear, preventing premature failure, and pushing back capital replacement costs.

Control maintenance costs without sacrificing reliability

Reducing maintenance costs isn’t about spending less everywhere. It’s about spending where it counts. With Industrial AI condition monitoring and real-time diagnostics, every repair dollar goes to the asset that actually needs it, guided by data instead of a fixed calendar.

When you have real-time visibility into every critical asset, the guesswork goes away. You plan around actual machine health, schedule the right work at the right time, and stop spending on repairs that weren’t necessary. That’s what it looks like to reduce maintenance costs without trading away reliability.

The numbers back it up: a Forrester Total Economic Impact™ (TEI) study* commissioned by Augury found that the composite organization achieved a 15% reduction in maintenance spend and a 310% ROI over three years.