Deliver maintenance-based insight into the equipment driving your operations ensuring safety, reducing downtime, and improving reliability.
What is the Difference Between Condition-Based & Predictive Maintenance?
Predictive and condition-based maintenance are both proactive maintenance approaches that occur before breakdowns happen. They both help increase reliability, reduce maintenance costs, and decrease downtime. Predictive maintenance uses sensor data to anticipate when maintenance is needed and relies on advanced statistical methods, such as machine learning, to optimize maintenance. Condition-based maintenance also relies on sensors, but it can only alert you when equipment begins to display problems.
The primary difference between them is the way in which maintenance is measured. Predictive maintenance relies on precise formulas in addition to sensor measurements (temperature, vibration, noise), and technicians perform maintenance work based on the analysis of these parameters. In this way, predictive maintenance predicts future maintenance events.
On the other hand, CBM relies only on real-time data from sensors or manual measurements. Once a parameter reaches an unacceptable level, maintenance workers are scheduled or dispatched depending on the severity.
Both predictive and condition-based maintenance can be expensive to initiate, though they both justify their upfront investment by saving money on downtime and equipment maintenance. These technologies are best deployed initially on critically important assets and with an understanding of what is causing your assets to fail to ensure that the right condition monitoring equipment is utilized.
The selection of predictive versus condition-based maintenance is probably more about the maturity of an organization. Typically, you would want to deploy condition-based maintenance before predictive maintenance. The condition-based maintenance approach is more mature and better understood. It is also useful in gathering metrics and data that would eventually feed into a predictive maintenance model.
What are the Various Types of Condition-Based Maintenance Monitoring Technologies?
Vibration Analysis
Infrared Thermography
Ultrasonic Analysis
Oil Analysis
Electrical Analysis
Pressure Analysis
Motion Amplification
Pros & Cons of Condition Monitoring
One of the major benefits of condition monitoring is that the technologies offer the organization a plethora of information about the nature of the defect and, to a large extent, information about the physical cause of the defect.
This enables the organization to significantly enhance the effectiveness of the root cause analysis process and eliminate the possibility of this same defect occurring in the future. Condition monitoring is famous for helping the organization prevent unexpected failures. By finding the defects early, the organization can plan and schedule the outage and, therefore, not experience the surprise of machinery failure when least expected.
Another benefit of condition monitoring is the amount of specific information that the collected data from the technologies can provide to the maintenance teams about the nature of the problem. By using some of these technologies, specific defects are identified, such as ‘inner race defects found on both pump bearing’ instead of the general indication of ‘pump making strange noise’. By and large, this reduces the troubleshooting time and costs associated with ‘parts swapping until the problem is solved.’ This also reduces the total amount of downtime for a repair, thus increasing availability and often productivity.
Condition-based monitoring enables the planning and scheduling process in three ways. First, condition monitoring identifies the defects early enough to allow the planning and scheduling process to take its natural flow. Nothing must be expedited or rushed, and production schedules do not have to be changed at the last minute.
Second, it gives the planner something specific to plan. Because of how precise the problem can be pinpointed; the planner can kit a specific collection of parts and have confidence that the required parts are there, and the maintenance technicians will not have to stop the job to go find what they need.
Third, the early detection of the fault means that more parts can be ordered, and fewer parts must be kept in stock. While there are several case studies
and success stories published in industry trade magazines, the specific list of benefits is almost universal.
A typical list includes:
Steps to Establish a Condition-Based Maintenance Program
Based on our success with condition-based maintenance (CBM) programs in multiple industries and countries, we have defined the following proper elements of a complete CBM program:
An accurate equipment walkdown assessment is required.
The condition-based maintenance program is based on asset/component failure modes.
The condition-based maintenance program should include all monitoring equipment as needed, including vibration, ultrasonics, infrared, lubrication and oil analysis, motor current analysis, and electronic signature analysis.
A schedule maintenance strategy that allows you to collect data and spot defects.
One condition-based maintenance execution model does not fit all companies. Therefore, Allied provides various flexible condition-based maintenance
program execution models including:
A single cloud-based enterprise CBM software platform that can support data analysis, visualization, and timely decision-making.
The extensibility of the CBM platform enabling integration with your enterprise asset management (EAM) solution is defined, implemented, and tested.
All the above capabilities work together, providing a complete CBM program that enables organizations to be more proactive and increase available time to plan and schedule work, as shown in the P-F Curve diagram below.
Case Study: Digital Transformation with Condition Monitoring
One-stop-shop for equipment reliability services and products
Industry-leading practitioners
All equipment gives off early warning signals – such as changes in temperature, vibration, or high-frequency sound – before it fails. These warning signals, or failure modes, can be detected with certain Condition Monitoring (CM) equipment.
The problem is that one or two technologies alone cannot detect most of the warning signals in your plant. As a result, a single-technology CBM program will miss far more faults than it catches. The key to a successful CBM program is to ensure it is highly sensitive to the failure modes of your equipment. That is why you need to apply multiple technologies so you can detect most failure modes in your plant.
Ultimately, your equipment’s failure modes and criticality determine which technologies you apply.
Allied Reliability has over 30 years of experience identifying critical assets and failure modes on equipment in various industries. We use that knowledge to help our clients understand what is most likely to cause a failure in their process and how best to proactively detect that failure (i.e., what technology to use to detect it).
Over our 30-year history, Allied has developed and implemented our complete condition-based maintenance work process for many successful customers. Any customer can leverage the process regardless of their condition-monitoring maintenance strategy and regardless of the number of condition-monitoring technologies in use (vibration, infrared, oil analysis, etc...).
Allied Reliability provides asset management consulting and predictive maintenance solutions across the lifecycle of your production assets to deliver required throughput at lowest operating cost while managing asset risk. We do this by partnering with our clients, applying our proven asset management methodology, and leveraging decades of practitioner experience across more verticals than any other provider. Our asset management solutions include Consulting & Training, Condition-based Maintenance, Industrial Staffing, Electrical Services, and Machine Reliability.
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