Which is better, preventive maintenance or predictive maintenance?

Predictive maintenance is better for critical assets where unplanned downtime is costly, but preventive maintenance is often better for simple, low-cost equipment where monitoring sensors are not worth the investment.

Is predictive maintenance more expensive than preventive maintenance?

Predictive maintenance has higher upfront costs for sensors and software, but it can lower long-term costs by reducing unnecessary part replacements and emergency repairs.

Does predictive maintenance reduce safety risks compared to preventive maintenance?

Yes, predictive maintenance reduces safety risks by catching failures early with real-time data, whereas preventive maintenance can still miss sudden breakdowns that occur between scheduled checks.

Can predictive maintenance be used on all types of machinery?

No, predictive maintenance works best on rotating equipment like motors and pumps with measurable vibration or temperature, but it is impractical for simple mechanical parts that lack reliable sensor data.

What is a common mistake when switching from preventive to predictive maintenance?

A common mistake is installing sensors without first collecting baseline data, which leaves you with no reference point to distinguish normal operation from early failure signs.

Are preventive maintenance and predictive maintenance interchangeable terms?

No, they are not interchangeable because preventive maintenance relies on calendar-based schedules while predictive maintenance relies on condition-based triggers from live equipment monitoring.

What is a real-world example of predictive maintenance in action?

A factory uses vibration sensors on conveyor motors to predict bearing wear, allowing teams to replace the bearing during a planned break instead of during a sudden production stoppage.

Can I switch from preventive maintenance to predictive maintenance without stopping production?

Yes, you can switch gradually by adding sensors to one critical machine first, then expanding the program as your team learns to interpret the data without halting operations.

Why would a small business choose preventive maintenance over predictive maintenance?

A small business chooses preventive maintenance because it requires no specialized software or training, making it simpler and more affordable for managing a handful of basic machines.

Difference Between

Difference Between Preventive Maintenance and Predictive Maintenance

Written byNex Virox Team

Editorial Team

Reviewed byVarshal Nirbhavane

Senior SEO & Organic Growth Professional · 5+ years

Published: September 2, 202621 min read

Quick answer

The main difference between Preventive Maintenance and Predictive Maintenance is that preventive maintenance runs on a fixed schedule, while predictive maintenance triggers based on real-time equipment condition. Preventive Maintenance is time-based servicing performed at regular intervals to prevent failures, while Predictive Maintenance is condition-based monitoring that uses data to predict when maintenance is actually needed.

Key takeaways

Core distinction: Preventive maintenance follows a fixed schedule, while predictive maintenance triggers action based on real-time equipment condition data.
How each works: Preventive maintenance uses time or usage intervals, whereas predictive maintenance relies on sensors, vibration analysis, and machine learning algorithms.
Cost and effort: Preventive maintenance costs less upfront but risks over-maintenance; predictive maintenance requires higher initial investment but reduces unnecessary labor and parts.
Best-fit use case: Preventive maintenance suits low-criticality assets with stable failure patterns; predictive maintenance excels for high-value, rotating machinery where downtime is expensive.
Most common mistake: Assuming predictive maintenance replaces preventive maintenance, when both should combine to optimize reliability and minimize total maintenance spend.

Table of Contents16 sections

What Is Preventive Maintenance?

Preventive maintenance is scheduled upkeep performed on equipment before failure occurs. It reduces unplanned downtime, extends asset lifespan, and lowers long-term repair costs. Unlike reactive repairs, preventive maintenance follows a fixed calendar or usage-based interval, ensuring machinery operates reliably and safely within its designed parameters.

Definition of Preventive Maintenance

Preventive maintenance is a systematic strategy involving routine inspections, lubrication, cleaning, and part replacements at predetermined intervals. Its purpose is to detect minor wear early and correct it, preventing catastrophic breakdowns. This discipline relies on manufacturer specifications, historical failure data, and operational schedules to determine optimal service timing for each individual asset.

Key Characteristics of Preventive Maintenance

Characteristic	What It Means in Practice
Scheduled timing	Maintenance occurs at fixed calendar intervals, such as every 30 days or 500 operating hours, regardless of current condition.
Proactive approach	Actions are taken before breakdowns happen, shifting focus from emergency response to planned, controlled interventions.
Documented procedures	Each task follows written checklists and standards, ensuring consistency and traceability across all technicians and shifts.
Inventory planning	Spare parts and consumables are stocked in advance, eliminating delays caused by waiting for replacement components.
Labor allocation	Technicians are assigned to tasks based on availability, avoiding overtime premiums and urgent call-out fees.
Asset history tracking	Maintenance logs record every service event, building a data trail that supports future replacement or overhaul decisions.
Cost predictability	Budgets are set annually based on known service frequencies, reducing financial surprises from sudden equipment failures.
Safety compliance	Regular checks on guards, sensors, and emergency stops help meet occupational safety regulations and audit requirements.
Performance baseline	Routine measurements of temperature, vibration, and pressure establish normal operating ranges for each machine.
Wear management	Components like belts, filters, and seals are replaced at recommended intervals before reaching their failure point.

Common Examples of Preventive Maintenance

Oil changes - Replacing lubricant in engines and gearboxes at set intervals prevents metal-on-metal wear and overheating.
HVAC filter replacement - Swapping air filters monthly or quarterly maintains airflow efficiency and indoor air quality.
Conveyor belt inspection - Checking belt tension and tracking weekly prevents misalignment, slippage, and premature edge damage.
Fire extinguisher checks - Verifying pressure gauges and seals monthly ensures extinguishers function during an emergency.
Elevator brake testing - Testing brake pads and governors quarterly confirms safe stopping capability for passenger use.
Pump seal replacement - Changing mechanical seals annually avoids leaks that cause bearing failure and fluid loss.
Electrical panel thermography - Scanning connections yearly detects hot spots from loose terminals before they cause arc faults.
Cooling tower cleaning - Removing scale and algae every season maintains heat exchange efficiency and prevents Legionella growth.
Forklift battery watering - Topping up electrolyte levels weekly extends battery life and prevents plate sulfation.
Roof inspection - Examining flashing and membrane twice yearly catches small cracks before they become structural leaks.

Advantages and Limitations of Preventive Maintenance

Advantages	Limitations
Reduces unexpected equipment failures that halt production lines and disrupt delivery schedules.	Performs maintenance on healthy components, wasting labor and materials that could have served longer.
Extends asset lifespan through consistent lubrication, cleaning, and timely replacement of wearing parts.	Requires dedicated maintenance windows that may conflict with peak production demand or tight customer deadlines.
Lowers overall repair costs by addressing minor issues before they escalate into major, expensive overhauls.	Demands a comprehensive inventory of spare parts, tying up capital that could be used elsewhere in operations.
Improves worker safety by ensuring guards, emergency stops, and safety interlocks remain functional at all times.	Cannot predict random failures caused by operator error, material defects, or undetected design flaws.
Provides predictable maintenance budgets based on fixed service intervals and known labor requirements.	Incurs unnecessary downtime when over-servicing occurs on equipment that operates far below rated capacity.
Creates a documented maintenance history that supports warranty claims and asset resale value negotiations.	Requires skilled technicians who understand complex machinery, creating training costs and staffing challenges.
Enables better production planning since maintenance windows are known in advance and can be scheduled.	Misses early-stage degradation that occurs between scheduled intervals, allowing faults to progress unnoticed.
Helps meet regulatory compliance for industries like food processing, pharmaceuticals, and aviation.	Generates administrative overhead for work orders, checklists, and record keeping that adds no direct product value.
Reduces energy consumption by keeping equipment properly lubricated, aligned, and free from excess friction.	Offers no feedback on actual component condition, so failures can still occur immediately after a service pass.
Builds a culture of proactive ownership among operators who understand their equipment's service needs.	Struggles to justify itself for low-criticality assets where replacement cost is cheaper than scheduled upkeep.

What Is Predictive Maintenance?

Predictive maintenance uses sensor data and machine learning to forecast equipment failure before it happens. It monitors real-time conditions like vibration, temperature, and acoustics to schedule repairs only when needed, reducing downtime and extending asset life compared to reactive or time-based strategies.

Definition of Predictive Maintenance

Predictive maintenance is a condition-based maintenance strategy that analyzes historical and live operational data to predict the optimal intervention point for machinery. It employs statistical models and IoT sensors to detect anomalies, enabling proactive repairs that prevent unexpected breakdowns and optimize maintenance costs across industrial assets.

Key Characteristics of Predictive Maintenance

Characteristic	What It Means in Practice
Continuous monitoring	Sensors collect vibration, temperature, and pressure data every few seconds, not just during periodic inspections.
Data-driven triggers	Maintenance alerts fire from algorithm thresholds, not calendar intervals, so work happens only when asset health degrades.
Failure prediction window	Models estimate remaining useful life in days or weeks, giving planners time to order parts and schedule labor shifts.
IoT sensor integration	Wireless accelerometers and thermocouples feed cloud platforms, enabling remote fleet-wide visibility from a single dashboard.
Machine learning models	Algorithms learn normal operating baselines per asset, then flag deviations that human analysts would miss in raw data.
Root cause analytics	Predictive alerts include diagnostic context, such as bearing wear patterns versus lubrication loss, speeding up repair decisions.
Condition-based work orders	Systems auto-generate repair tickets with severity scores, prioritizing critical assets over less urgent maintenance tasks.
Historical trend analysis	Past failure records combine with live data to refine prediction accuracy, improving precision each operating cycle.
Cost optimization focus	Labor and parts are deployed only when failure probability exceeds a set threshold, avoiding unnecessary preventive replacements.
Integration with CMMS	Predictive outputs sync directly with computerized maintenance management systems, closing the loop from detection to work completion.

Common Examples of Predictive Maintenance

Vibration analysis on motors – Accelerometers detect bearing race defects weeks before audible noise or heat appears, preventing unplanned production stops.
Oil particle counting in gearboxes – Laser sensors count metal shavings in lubricant, signaling gear wear that would otherwise cause catastrophic transmission failure.
Thermography on electrical panels – Infrared cameras spot loose connections running hot, enabling safe shutdowns before arc flashes or fires occur.
Acoustic monitoring on valves – Ultrasonic microphones catch internal leakage in steam traps, reducing energy waste and preventing pipe erosion.
Current signature analysis on pumps – Motor current waveforms reveal impeller imbalance or cavitation, allowing trim adjustments without disassembly.
Pressure pulse monitoring in hydraulics – High-frequency sensors detect piston seal wear in cylinders, avoiding sudden actuator failure in critical lifting applications.
Corrosion probes on pipelines – Electrochemical sensors measure wall thickness loss, enabling targeted repairs before leaks contaminate soil or water.
Bearing temperature trending in conveyors – Thermal couples log gradual heat rise, triggering grease replenishment before seizure halts the entire material flow line.
Air gap monitoring in generators – Proximity sensors track rotor-stator clearance, preventing costly winding damage in hydro or wind turbines.
Software log analysis on servers – Anomaly detection scans error rates and response times, predicting disk failures or memory leaks before user-facing outages occur.

Advantages and Limitations of Predictive Maintenance

Advantages	Limitations
Reduces unplanned downtime by up to 70% compared to reactive strategies, directly improving production throughput.	High upfront investment in sensors, gateways, and software platforms can exceed $50,000 per facility, deterring small plants.
Extends asset lifespan by catching minor faults early, avoiding secondary damage to connected components like shafts or housings.	Requires skilled data scientists to build and tune models, a scarce talent pool that many maintenance teams lack internally.
Lowers maintenance labor costs by eliminating unnecessary routine checks, freeing technicians for higher-value repair work.	False positives from noisy sensor data can trigger needless inspections, wasting crew time and eroding trust in the system.
Improves safety by predicting failures in high-risk equipment like cranes or pressure vessels, preventing catastrophic accidents.	Legacy machines without built-in sensors need retrofitting, which often costs more than the asset's remaining book value.
Optimizes spare parts inventory by predicting failures in advance, reducing emergency stockouts and expedited shipping fees.	Model accuracy depends on years of clean historical failure data, which many organizations simply do not have on file.
Enables remote monitoring of multiple sites from one control room, cutting travel costs for field engineers.	Connectivity gaps in remote or underground locations can interrupt data streams, leaving blind spots in coverage.
Provides measurable ROI through reduced maintenance spend, typically showing payback within 12 to 18 months for large fleets.	Integration with existing CMMS or ERP systems often requires custom APIs, adding months of IT project time and cost.
Supports condition-based warranty claims with documented sensor logs, strengthening negotiations with equipment vendors.	Sensor drift or calibration errors degrade prediction quality over time, demanding regular verification and recalibration routines.
Facilitates predictive scheduling that aligns maintenance with low-demand periods, minimizing revenue loss from planned stops.	Smaller facilities with fewer than 50 critical assets may never recoup the fixed costs of a full predictive infrastructure.
Creates a digital twin of asset health, enabling what-if simulations for process changes without risking physical equipment.	Cybersecurity risks increase with networked sensors, requiring robust encryption and access controls to prevent sabotage.

Shared Aspect	How Preventive Maintenance and Predictive Maintenance Are Alike
Core Objective	Both preventive maintenance and predictive maintenance aim to reduce unplanned downtime and extend equipment lifespan.
Failure Prevention	Preventive maintenance and predictive maintenance both focus on preventing equipment failure before it occurs.
Asset Focus	Both preventive maintenance and predictive maintenance prioritize critical assets that impact production or safety.
Scheduled Action	Preventive maintenance and predictive maintenance both require planned, scheduled maintenance tasks rather than reactive fixes.
Data Reliance	Both preventive maintenance and predictive maintenance depend on historical data to determine maintenance timing.
Cost Reduction	Preventive maintenance and predictive maintenance both lower long-term repair costs by avoiding major breakdowns.
Inventory Management	Both preventive maintenance and predictive maintenance allow for better spare parts planning and inventory control.
Safety Improvement	Preventive maintenance and predictive maintenance both reduce workplace accidents caused by equipment failure.
Documentation Need	Both preventive maintenance and predictive maintenance require detailed maintenance logs and equipment records.
Technician Skills	Preventive maintenance and predictive maintenance both require trained technicians who understand equipment mechanics.
Quality Control	Both preventive maintenance and predictive maintenance help maintain consistent product quality by keeping machines calibrated.
Production Efficiency	Preventive maintenance and predictive maintenance both improve overall equipment effectiveness (OEE) and throughput.
Lifecycle Management	Both preventive maintenance and predictive maintenance track equipment age and wear to plan replacements.
Budget Planning	Preventive maintenance and predictive maintenance both enable predictable maintenance budgeting across fiscal years.
Compliance Support	Both preventive maintenance and predictive maintenance help meet regulatory inspection and audit requirements.
Warranty Protection	Preventive maintenance and predictive maintenance both preserve manufacturer warranties through documented service.
Energy Savings	Both preventive maintenance and predictive maintenance reduce energy waste from poorly running or failing equipment.
Root Cause Analysis	Preventive maintenance and predictive maintenance both use failure patterns to identify underlying equipment issues.
Continuous Improvement	Both preventive maintenance and predictive maintenance feed data into improvement cycles for maintenance strategies.
Team Coordination	Preventive maintenance and predictive maintenance both require coordination between maintenance, operations, and planning teams.
Vendor Collaboration	Both preventive maintenance and predictive maintenance often involve equipment manufacturers for service recommendations.
Software Integration	Preventive maintenance and predictive maintenance both integrate with CMMS or EAM software for tracking.
KPI Tracking	Both preventive maintenance and predictive maintenance measure success using metrics like MTBF and MTTR.
Risk Mitigation	Preventive maintenance and predictive maintenance both reduce operational risk from unexpected asset failure.
Training Investment	Both preventive maintenance and predictive maintenance require ongoing staff training on new procedures and tools.
Scalability	Preventive maintenance and predictive maintenance both scale across multiple sites or fleets with standardized processes.
Environmental Impact	Both preventive maintenance and predictive maintenance reduce waste and emissions from inefficient machinery.
Customer Satisfaction	Preventive maintenance and predictive maintenance both support on-time delivery by preventing production stoppages.
Audit Readiness	Both preventive maintenance and predictive maintenance provide verifiable maintenance history for internal and external audits.
Strategic Value	Preventive maintenance and predictive maintenance both transform maintenance from a cost center into a competitive advantage.

Preventive Maintenance or Predictive Maintenance: Which Should You Choose?

The deciding variable is your equipment's criticality and your budget for sensors. Choose preventive maintenance for low-cost, non-critical assets where failure is inconvenient but not catastrophic. Choose predictive maintenance for high-value, safety-critical machinery where unplanned downtime costs exceed $10,000 per hour.

When to Use Preventive Maintenance

Choose Preventive Maintenance when you operate fixed-schedule equipment like HVAC filters, conveyor belts, or pumps under 50 horsepower. It suits teams with limited technical skills, small budgets under $5,000 annually, and assets with predictable wear patterns. This time-based approach works best for regulatory compliance, like fire extinguisher inspections, where documented intervals are mandatory.

When to Use Predictive Maintenance

Choose Predictive Maintenance when you run rotating assets above 100 horsepower, such as turbines, compressors, or CNC spindles, where failure halts production. It fits facilities with vibration sensors, thermography cameras, or oil analysis programs, plus staff trained in data interpretation. This condition-based method pays off when unplanned downtime exceeds $50,000 per incident and maintenance teams can act on real-time alerts.

Common Misconceptions About Preventive Maintenance and Predictive Maintenance

Common Myth	The Reality
"Preventive maintenance and predictive maintenance are basically the same thing."	Preventive maintenance runs on fixed schedules, while predictive maintenance triggers actions based on real-time equipment condition data, making them fundamentally different strategies.
"Predictive maintenance always costs more than preventive maintenance."	Predictive maintenance reduces unnecessary part replacements and labor, often cutting total maintenance costs by 20-30% compared to preventive maintenance over a full asset lifecycle.
"Preventive maintenance is just changing parts before they break."	Preventive maintenance includes lubrication, cleaning, calibration, and inspections, not just part replacement; these tasks extend asset life and prevent secondary damage.
"Predictive maintenance requires expensive sensors on every single machine."	Predictive maintenance works with portable vibration meters, oil analysis samples, or thermography cameras; you do not need permanent sensors on every asset to start.
"Preventive maintenance guarantees zero equipment failures."	Preventive maintenance reduces failure probability but cannot stop random breakdowns from human error, material defects, or undetected root causes.
"Predictive maintenance only works for rotating equipment like motors and pumps."	Predictive maintenance also applies to static assets, including heat exchangers, pipelines, electrical switchgear, and structural components, using corrosion and thermal monitoring.
"You must choose between preventive or predictive maintenance for your whole plant."	Most reliability programs blend both: preventive maintenance for low-criticality assets and predictive maintenance for high-value or failure-prone equipment.
"Predictive maintenance gives you the exact failure date of a component."	Predictive maintenance provides a trend and a probability window, not a precise date; operators must still set thresholds and plan actions within that window.
"Preventive maintenance is only for large factories with big budgets."	Preventive maintenance scales down to small facilities; simple checklists and scheduled lubrication on a few machines cost less than one unplanned breakdown.
"Predictive maintenance eliminates the need for preventive maintenance tasks."	Predictive maintenance cannot replace lubrication, cleaning, or calibration; those preventive tasks still run on schedule to keep condition-monitoring data accurate.
"Preventive maintenance wastes money because you replace parts that are still good."	Preventive maintenance uses time-based intervals, so some good parts get replaced, but the avoided downtime and secondary damage usually outweigh that waste.
"Predictive maintenance is too complex for small or medium-sized teams."	Predictive maintenance starts with one vibration pen or an oil-analysis kit; many small teams adopt it successfully with minimal training and no software.
"Preventive maintenance is the same as reactive maintenance just done faster."	Preventive maintenance is planned and scheduled before failure, while reactive maintenance happens after failure; planning reduces overtime, rush parts, and safety risks.
"Predictive maintenance requires a dedicated data scientist on staff."	Modern predictive maintenance software automates trend analysis and alerts; technicians with basic training interpret the outputs without needing a data scientist.
"Preventive maintenance intervals are set once and never change."	Preventive maintenance intervals should be adjusted based on failure history, operating hours, and condition data; static intervals lead to over- or under-maintenance.
"Predictive maintenance is only useful for avoiding catastrophic failures."	Predictive maintenance also improves product quality, reduces energy consumption, and extends asset life by catching minor degradation early.
"Preventive maintenance always increases overall equipment effectiveness (OEE)."	Excessive preventive maintenance reduces OEE by taking machines offline too often; the right interval balances availability against failure risk.
"Predictive maintenance gives instant results after one measurement."	Predictive maintenance relies on baseline data and repeated measurements over time; a single reading only shows a snapshot, not a trend or failure trajectory.
"Preventive maintenance is the same as condition-based maintenance."	Preventive maintenance follows a calendar or usage schedule, while condition-based maintenance acts on measured parameters like temperature or vibration readings.
"Predictive maintenance is only for expensive or critical assets."	Predictive maintenance is cost-effective for many mid-value assets when the cost of downtime exceeds the cost of monitoring; it is not reserved for top-tier equipment only.
"Preventive maintenance does not require any training for maintenance staff."	Preventive maintenance tasks require proper training on torque specs, lubrication types, and inspection criteria; untrained staff can cause more damage than they prevent.
"Predictive maintenance always reduces the total number of maintenance tasks."	Predictive maintenance shifts tasks from fixed schedules to condition-triggered actions; total task count may stay similar, but the timing and necessity of each task improves.
"Preventive maintenance is a one-time program you set up and forget."	Preventive maintenance needs continuous review of work orders, failure codes, and interval adjustments; a static program becomes ineffective as equipment ages or changes.
"Predictive maintenance cannot be used on equipment that runs intermittently."	Predictive maintenance works on intermittent assets by measuring during run cycles or using off-line testing like motor current analysis or acoustic emission.
"Preventive maintenance is always cheaper than predictive maintenance in the short term."	Preventive maintenance may have lower startup costs, but predictive maintenance often pays back within 6-12 months through reduced downtime and fewer emergency repairs.
"Predictive maintenance requires a complete digital twin of your factory."	Predictive maintenance works with simple spreadsheets or standalone monitoring devices; digital twins are optional enhancements, not prerequisites for success.
"Preventive maintenance is the best strategy for all asset types."	Preventive maintenance is suboptimal for assets with random failure patterns; predictive or run-to-failure strategies may be more effective for those specific cases.
"Predictive maintenance only detects mechanical problems, not electrical or process issues."	Predictive maintenance detects electrical faults via thermography and motor analysis, plus process issues like flow restrictions or heat exchanger fouling.
"Preventive maintenance does not need any data collection or record keeping."	Preventive maintenance relies on work order history, task completion records, and failure data to refine intervals and justify program changes.
"Predictive maintenance is a magic solution that works immediately after installation."	Predictive maintenance requires a learning period to establish baselines, set alarms, and train staff; expecting instant failure prediction leads to disappointment and abandonment.

Conclusion

Difference Between Preventive Maintenance and Predictive Maintenance comes down to scheduling versus condition monitoring. Preventive maintenance runs on fixed intervals, while predictive maintenance triggers based on real-time equipment data. Choose preventive maintenance for simple, low-cost assets. Choose predictive maintenance for critical, expensive machinery where downtime costs are high.

FAQs on Difference Between Preventive Maintenance and Predictive Maintenance

What is the main difference between preventive maintenance and predictive maintenance?: Preventive maintenance schedules tasks at fixed time intervals, while predictive maintenance performs tasks only when sensor data shows a machine is about to fail.
Which is better, preventive maintenance or predictive maintenance?: Predictive maintenance is better for critical assets where unplanned downtime is costly, but preventive maintenance is often better for simple, low-cost equipment where monitoring sensors are not worth the investment.
Is predictive maintenance more expensive than preventive maintenance?: Predictive maintenance has higher upfront costs for sensors and software, but it can lower long-term costs by reducing unnecessary part replacements and emergency repairs.
Does predictive maintenance reduce safety risks compared to preventive maintenance?: Yes, predictive maintenance reduces safety risks by catching failures early with real-time data, whereas preventive maintenance can still miss sudden breakdowns that occur between scheduled checks.
Can predictive maintenance be used on all types of machinery?: No, predictive maintenance works best on rotating equipment like motors and pumps with measurable vibration or temperature, but it is impractical for simple mechanical parts that lack reliable sensor data.
What is a common mistake when switching from preventive to predictive maintenance?: A common mistake is installing sensors without first collecting baseline data, which leaves you with no reference point to distinguish normal operation from early failure signs.
Are preventive maintenance and predictive maintenance interchangeable terms?: No, they are not interchangeable because preventive maintenance relies on calendar-based schedules while predictive maintenance relies on condition-based triggers from live equipment monitoring.
What is a real-world example of predictive maintenance in action?: A factory uses vibration sensors on conveyor motors to predict bearing wear, allowing teams to replace the bearing during a planned break instead of during a sudden production stoppage.
Can I switch from preventive maintenance to predictive maintenance without stopping production?: Yes, you can switch gradually by adding sensors to one critical machine first, then expanding the program as your team learns to interpret the data without halting operations.
Why would a small business choose preventive maintenance over predictive maintenance?: A small business chooses preventive maintenance because it requires no specialized software or training, making it simpler and more affordable for managing a handful of basic machines.