What is CBM (Condition-Based Maintenance)?
Oded Ran, CEO and Co-Founder of Clue since 2019, expertly integrates AI and data tools to revolutionize construction equipment management and maintenance, positioning Clue as a premier software choice in the construction industry.
What if your equipment could let you know when it needs attention before something gets in your way during work?
With Condition Based Maintenance (CBM), that’s the promise.
CBM differs from traditional maintenance practices that schedule maintenance based on fixed intervals, or wait until equipment fails to operate.
CBM uses real-time information to keep your equipment running in top condition and reduces equipment downtime and the expense of repairs.
So how does it work, and is it the right fit for your operations?
Get up to speed on the revolutionary technology behind CBM and what it might do to transform your world of maintenance in this guide.
So begins your journey into smarter maintenance.
Clue has what you need – whether you want to get rid of wasting precious money on needless construction equipment maintenance spending, ramp up reliability, or start taking this next step in your industry.
With our Conditions Based Maintenance (CBM) expertise, we use real-time data and predictive insights to extend operations, lower costs and deliver peak performance.
What is Condition-Based Maintenance?
Condition-based maintenance (CBM) is a type of maintenance, which works under some actual condition of a piece of equipment instead of some predetermined schedule.
Key data such as vibration levels, temperature, or flow rates can be provided to the maintenance teams that help in getting insights into their construction asset’s health and track the asset’s health.
By putting data at the center of the maintenance strategy, they can avoid the unpredictability of reactive maintenance and the inefficiency of overly rigid preventive maintenance schedules, to maintain their assets more smartly and more efficiently.
Many organizations that have successfully implemented CBM have used advanced computerized maintenance management systems (CMMS).
Today's cloud-based CMMSs can link to data sources, including vibration sensors and SCADA systems into the maintenance process without impacting engineering or production data.
Both these systems also support automated workflows that send alerts or even work orders when early signs of failure are detected.
An example is that construction equipment maintenance practices seem to be changing by the day because of the Industrial Internet of Things (IIoT) and artificial intelligence (AI) flooding the world of smart factories today.
CBM plays a pivotal role in this transformation, working alongside complementary strategies such as:
- Preventive maintenance: Avoid failure of planned checks and tasks.
- Usage-based maintenance: Operating time-based or cycle interventions.
- Run-to-failure maintenance: Allowing for the failure of less critical components naturally before replacement.
Importance of Condition-based Maintenance
Condition-based maintenance involves monitoring equipment to identify the possibility of failure early on to schedule maintenance before failure occurs — and thereby avoid unnecessary work.
This approach guarantees that maintenance work starts with sufficient lead time before equipment performance declines or a complete equipment failure is observed; repairs or adjustments can therefore be made effectively.
If condition-based maintenance is to work, certain foundational elements need to be in place.
This consists of a structured maintenance schedule that provides regular temperature checkups of assets so they first can be inspected and issues may be identified early on plus also scheduled follow-up work orders.
Making this approach even better, with AI-powered reports, you can predict which work orders are most likely to prevent equipment failures.
It's also important to keep a good stock of parts and supplies so you can remedy performance problems quickly when they are discovered and tasks are assigned.
Types of Condition-Based Maintenance
The word ‘proactive maintenance’ is often used by practitioners in CBM and this refers to a method of maintenance where one assess equipment health by real time or periodic examination and uses that information in conjunction with assumptions to detect a sign of deterioration or failure.
Analysis of some parameters allows to schedule maintenance activities only when necessary, to reduce unexpected downtime, and prolong machine life.
1. Vibration Analysis
CBM is primarily vibration analysis of rotating machinery on construction sites such as motors, pumps, and gearboxes.
It can locate misalignment, imbalances, and bearing faults by measuring vibration levels.
Insights from methods such as the Fast Fourier Transform (FFT) are used to plan maintenance by converting vibration data into frequency domain spectra to identify specific fault frequencies.
It allows one to take targeted maintenance actions to avoid additional damage and keep the machine in a state of maximal operation.
2. Infrared And Thermal Analysis
CBM uses infrared and thermal analysis methods which is the non-contact method used to detect abnormal temperature patterns on equipment surfaces.
Early solutions to avoid hotspots related to electrical faults, misalignment, or lubrication-related problems, enable maintenance teams to respond in advance.
This technique is very versatile and can provide maintenance of both electrical and mechanical systems to minimize risks and improve system reliability.
3. Ultrasonic Analysis
An ultrasonic analysis uses high-frequency sound waves to detect leaks, cavitations, and mechanical defects.
This is particularly effective for early detection of bearing failures or insufficient lubrication making it an extremely useful precursor to predictive maintenance.
Ultrasonic analysis gives support to complete machinery CBM strategy when combined with vibration analysis and thermal imaging.
5. Acoustic Analysis
The equipment emissions acoustic sounds are monitored for defects.
It operates in audible sound frequencies, similar to ultrasonic analysis, but is much less powerful than ultrasonic energy transmitting units.
This technique can be used to detect such problems as mechanical looseness, impacts, or flow disturbances in, for example, valves or pumps.
6. Oil Analysis
Machine health can be assessed through lubricant property investigations under oil analysis.
It gives information on the state of internal component conditions like the wear particles, contamination levels, and viscosity.
The capabilities of oil analysis are to detect contamination, oxidation, and additive depletion to facilitate more timely maintenance actions.
7. Electrical Analysis
Electrical Signature Analysis (ESA) is the method that uses current and voltage signals analysis to evaluate the condition of the electrical equipment.
It monitors motor and generator electrical imbalances, insulation degradation, anomalies, and other fault indicators.
The benefits of ESA are that continuous maintenance can be achieved with all operations running indefinitely.
8. Pressure Analysis
On one of the hydraulic systems, you see these consistent pressure levels are needed for machines such as excavators, loaders and cranes in construction equipment.
Pressure deviations can be a sign of a blocked hose or leak in a hydraulic circuit compromising the functioning of that equipment.
Pressure analysis allows them to identify these issues early before the equipment fails when it most needs it at critical job sites.
Optimal Scenarios for Implementing Condition-Based Maintenance
Condition Based Maintenance (CBM) is proactive maintenance based on the actual condition of equipment and not on a scheduled basis.
Particularly beneficial for assets where operational parameters such as temperature, pressure, and oil quality are key to performance and life, this approach can provide incremental benefits in both time and money.
Temperature-Sensitive Assets
CBM is invaluable for equipment where temperature is a key performance indicator.
Maintenance can be performed precisely in terms of temperature at the right timing, avoiding overheating and potentially failing.
- Hydraulic Excavators: Excavator hydraulic systems require proper temperatures for proper efficiency. System failure or reduced performance can result from over heating. Infrared Thermography is a CBM tool that can detect hotspots in hydraulic circuits.
- Engines in Heavy Equipment (e.g., Bulldozers, Loaders): Continuous load causes engines to overheat. The monitoring temperatures of coolant and exhaust helps spot inefficiencies or the risk of overheating.
Pressure-Sensitive Applications
Large hydraulic and pneumatic systems, such as those used on many construction machines, require that pressure remain within specified ranges, both for the safety and performance of the machine.
- Hydraulic Cranes: Either unsafe operations or mechanical wear can result from uneven pressure levels in cranes. Passive can then monitor pressure sensors for leaks, blockages, and any other abnormality.
- Concrete Pumps: Pump pressure monitoring ensures constant material flow and stops unexpected stoppage or system failure.
Oil-Reliant Equipment
Construction equipment has vital lubrication systems to minimize friction, heat generation, and wear. Monitoring oil quality makes these systems function effectively.
- Articulated Trucks and Dumpers: Components in engines and transmissions can degrade, so regular oil analysis helps identify wear particles, contamination or viscosity change, alerting you to potential component degradation.
- Rollers and Compactors: High friction operations depend heavily on lubrication and these machines depend on that. Monitoring of oil quality guarantees bearing lifetime and operating efficiency.
Key Components of CBM Workflow
1. In-depth Monitoring and Data Collection
Continuous equipment data gathering throughout all aspects of an operation is considered in deep monitoring.
The installed sensors on critical components capture parameters such as temperature, vibration, pressure, and oil quality.
Real-time data from these sensors and their effects on equipment conditions in varying loads and environmental conditions.
Manual errors are also minimized by automatic systems like IoT-supported devices or SCADA platforms.
2. Various Means of Collecting Data
The type of equipment and parameters to be monitored in CBM determines the type of data collection employed.
Vibration sensors detect issues like misalignment, infrared thermography finds overheating components and ultrasound sensors find leaks or tell you that a bearing is worn.
In addition, oil analysis kits monitor lubricant conditions, pressure sensors are available to indicate possible deviations in hydraulic or pneumatic systems.
Furthermore, these methods ensure coverage of critical equipment metrics in their entirety.
3. Data Analysis and Interpretation
Combined with additional research, the collected data is analyzed to determine patterns, anomalies, or warnings of impending failures.
Interpreting data of course means, advanced software tools and especially algorithms, such as machine learning or predictive analytics, are being used for that.
Vibration frequency data may for instance be transformed to frequency domain spectra and frequencies of fault are pinpointed.
It helps turn raw data into actionable insights, so maintenance teams spend less time on areas of least concern and more on areas of interest.
4. Defining Failure Modes and Establishing Trigger Points
Effective CBM therefore requires the understanding of possible failure modes.
However, each equipment type has its unique failure pattern: bearing wear, overheating, oil contamination, etc.
The trigger points are thresholds that mean that when they are exceeded, equipment conditions have deviated from the 'normal.'
For example, a given vibration amplitude or a temperature rise. Thresholds are set on historical data, manufacturer recommendations, or industry standards.
5. Identification of Abnormal Patterns or Trends
The onset of equipment failure is usually indicated by abnormal patterns or trends of the monitored parameters.
For example, if vibration levels are increasing, you are likely near bearing degradation, or if an oil temperature is climbing, you are likely going through lubrication problems.
Early detection of these patterns enables timely intervention early enough before the condition progresses to a critical failure.
6. Condition Assessment and Decision-Making
This is then condition assessment, in which we identify the detected abnormalities and evaluate their significance and thus determine what is to be done.
The severity and urgency of the issue guide the maintenance, however, factors such as operational demands and the criticality of the equipment are included.
For example, minor anomalies may require observation but significant defects will require immediate repairs or part replacement.
Having this done means that maintenance activities are targeted correctly and the cost is effective as much as possible, minimizing any disruptions that might be unnecessary.
Pros and Cons of CBM
Enhancing Condition-Based Maintenance (CBM) with Clue
Condition-Based Maintenance (CBM) strategies become easy with the support of Clue, a platform to manage comprehensive equipment in one place and provide advanced tools and integrations like real-time data collection, analysis, and actions insights.
Here's where Clue can be highlighted within the context of CBM:
- Data Integration and Monitoring: By means of advanced telematics, Clue merges data coming from vibration sensors, infrared thermography or oil analysis equipment, which enables it to support CBM. The user can monitor real time equipment parameters such as vibration, temperature and oil quality through these integrations.
- Automated Workflows: With Clue's automated workflows, CBM users can receive alerts when key thresholds are exceeded. For instance, if vibration levels indicate bearing wear, Clue can generate a work order automatically, streamlining the maintenance process and preventing downtime.
- Comprehensive Reporting and Analytics: Using powerful reporting features, Clue allows users to analyze trends, and even predict equipment failures. By means of its machine learning algorithms and predictive analytics, CBM practices become more efficient: maintenance teams are able to make informed decisions.
- Proactive Maintenance Scheduling: Using Clue, maintenance teams can shift from reactively maintaining equipment to proactively doing so because of the ability to base task prioritization on real-time equipment health data. For example, Clue can recognize abnormal patterns, (such as rising oil contamination levels, for example, and) suggest immediate interventions for equipment maintenance.
- Inventory Management: This inventory management feature of Clue makes sure there will always be enough parts and supplies to do maintenance in a timely manner when abnormally harsh conditions are discovered.
- Mobile Accessibility: Using Clue’s mobile app, maintenance teams have access to CBM insights in the field, allowing for faster response times and better coordination in the field.
- Industry-Specific Customizations: Clue works especially well for CBM solutions for industries such as mining, construction, and heavy equipment where it can provide customized solutions for temperature-sensitive, pressure-sensitive, and oil-dependent machinery.
Final Thoughts
Condition Based Maintenance (CBM) is a proactive maintenance that relies on real-time equipment data to maximize the maintenance.
With CBM, meaning narrowly focused on actual equipment conditions rather than fixed schedules, we minimize downtime, reduce repair costs, and extend machinery lifespan.
Actionable insights are provided by techniques such as vibration analysis, infrared thermography, and oil analysis, providing for timely intervention for temperature-sensitive, pressure-sensitive, and oil-dependent construction equipment.
Because of its integration with IoT and AI technologies, operation precision is improved and decision-making is automated.
This assures that maintenance is carried out only as needed and saves energy and reliability.
The CBM approach allows organizations to manage equipment performance more effectively, lower operating costs, and maintain operations by continuing to deliver required performance in ever more difficult and demanding environments.
FAQs
What is The Difference Between Predictive And Condition Based Maintenance?
Condition-based maintenance (CBM), and predictive maintenance (PdM) are two asset management strategies that leverage data to enable organizations to minimize equipment failure and maximize their asset lifespan. The difference between the two is that CBM responds only in periods of maintenance while PdM is proactive and predicts when it may have to do so.
What is Condition-based Maintenance?
On-condition maintenance is a maintenance strategy of regularly checking and testing items to see if they are still in good shape and are still useful for use. The point is to do maintenance only when it should be done, to minimize costs and downtime.
What is Condition-based Servicing?
Condition Based Servicing (CBS) is a vehicle maintenance system involving the use of sensors and algorithms that monitor a vehicle and decide if maintenance is needed. The alternative of CBS maintenance has the advantage of longer maintenance intervals, compared to time-based maintenance.
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