In the video What is Condition Based Maintenance (CBM)?, John introduced a simple definition of CBM. Let's recap this definition and looks at some main objectives and specific examples of CBM in different industries below. Alternately, you can find this information on p5 -p7 of the CBM Guide ebook.
2.1 An Introduction to Condition-Based Maintenance (CBM)
Condition Based Maintenance (CBM) is a set of maintenance processes driven by real-time asset information to ensure maintenance is performed only when evidence of need exists. CBM can also be useful in fault prevention by recognizing equipment degradation before catastrophic failure occurs. There are other more specific examples, and we discuss those in depth in the remainder of this section.
Most CMMS (Computerized Maintenance Management System) applications support integration of OT (Operational Technology) time-series data via the concept of a meter (or counter). A meter is either quantitative or qualitative. Quantitative meters are used for numerical quantities such as run hours, temperature, rate of change, material processed, fouling factor in percent, and time (in seconds) to transition. The CMMS can generate prescriptive maintenance (such as a PM task, or a repair and replace order) when specific numbers are exceeded. Most CMMS systems can also forecast when a trigger point will occur based on the pattern of change sent to the CMMS by the PI System. This is useful in generating orders in time to plan and schedule them appropriately.
Qualitative meters are those that are setup to maintain states, such as “good” and “bad”, or the street light example of “red”, “yellow” and “green”. For one or more of the states, the CMMS can also generate a prescriptive order or work notification.
The integration of OT data with CMMS via meters is intended to drive preventive maintenance (more effectively than on calendar basis alone), and corrective maintenance when CBM detects an incipient failure or some abnormal condition exists.
In addition to the above, we often hear operational, reliability and maintenance personnel say they want to know “when the system is not operating as it normally does”. This is also known as “anomaly detection”, and is the most prevalent and valuable “advanced analytic” applied in condition monitoring scenarios. The technique used to detect anomalies is Advanced Pattern Recognition (APR). There are a few statistical algorithms well suited to APR and a number of OSIsoft partners that offer solutions with the PI System for APR.
The goal of a CBM implementation is to move from a calendar-based preventive maintenance program to a condition-based preventive maintenance program.
The main objectives of CBM are to:
- Reduce maintenance costs (stretch maintenance cycles)
- Reduce adverse impacts of maintenance activities (if it works, don’t fix it)
- Improve asset reliability (ensure assets are functional and capable)
- Improve asset availability (minimize asset downtime)
- Enable value realization from condition information (e.g. lifecycle extension, decision support, better capital expenditures, etc.)
2.1.3 Role of CBM in CMMS
Maintenance processes normally are, and in the case of this document are assumed to be, managed in a work management system as pre-described maintenance tasks (preventive or planned). Work management systems are typically called a computerized maintenance management system (CMMS) and maybe a complete and dedicated piece of software or a module of a more comprehensive enterprise asset management (EAM) or enterprise resource planning (ERP) system.
Maintenance processes have been historically based on, calendar (time-based) schedules due to a lack of asset-specific condition information. Calendar-based schedules are more conservative and recommend more frequent maintenance in order to avoid running an asset to failure. Because calendar-based schedules can generate unneeded maintenance, they can increase costs as well as damage to assets during unnecessary repairs and decrease overall asset availability. When asset information is integrated into CBM-enabled work systems, maintenance processes are generated by asset-specific condition indicators that predict when an asset needs maintenance. These indicators are often supplemented by a calendar schedule as well to ensure maintenance is performed even when the asset is little used. A familiar example to the most casual reader may be the oil maintenance of a vehicle, which is typically stated in terms of a condition (7,500 miles driven) or a calendar event (12 months duration) whichever comes first.
EXAMPLE: Modern vehicles can detect the condition of the lubricating oil (expressed in %) and recommend replacement when it is losing its effectiveness.
EXAMPLE: A compressor needs maintenance after a certain number of start/stop cycles. If start/stop cycles cannot be counted, conservative factors would be used to estimate a time interval after which maintenance should be scheduled. The factors could be based on predictive information or vendor recommendations to ensure maintenance would be done before exceeding the recommended number of cycles. In contrast, CBM ensures maintenance is done only when there’s a need. CBM gives the advantage of setting maintenance cycles for longer periods than would have been done using conservatively based on time schedules, saving money and increasing equipment availability.
Real-time asset information enables users to define asset-specific condition indicators either from raw sensor data or through data calculations. Condition indicators derived from asset data initiate maintenance tasks based on real-time conditions and are asset-specific. Real-time asset data may come from on-line monitoring (temperatures, delta pressures, start/stop sequences, etc.), off-line diagnostic tests (eddy current, corrosion inspection, oil analysis, etc.) or portable test equipment (thermography, Doble electrical test set, etc.) The PI System can manage and historize, aggregate and perform analysis on all of these data types with information from other sources. Condition indicators derived from these analyses and calculations can be provided to the CMMS. We’ll cover much more on access methods later.
The benefits of well-implemented CBM programs extend outside of protecting corporate investment in asset portfolios. When real-time asset data provide visibility into asset condition, maintenance schedules and costs can be planned. (Will that compressor make it until the next outage?) Common failures or issues that occur across units or within fleets can be identified. (Why is maintenance more expensive on a specific vendor’s equipment compared to other vendors?) Just by creating visibility into asset condition indicators, data can help prevent catastrophic failures. It only takes a few big saves to typically pay for a complete CBM implementation.