Predictive maintenance (PdM) is maintenance that monitors the performance and condition of equipment during normal operation to reduce the likelihood of failures. Also known as condition-based maintenance, predictive maintenance has been utilized in the industrial world since the 1990s.
Yet, in reality, predictive maintenance is much older, although its history is not formally documented. According to Control Engineering, “The start of predictive maintenance (PdM) may have been when a mechanic first put his ear to the handle of a screwdriver, touched the other end to a machine, and pronounced that it sounded like a bearing was going bad.”
The goal of predictive maintenance is the ability to first predict when equipment failure could occur (based on certain factors), followed by preventing the failure through regularly scheduled and corrective maintenance.
Predictive maintenance cannot exist without condition monitoring, which is defined as the continuous monitoring of machines during process conditions to ensure the optimal use of machines. There are three facets of condition monitoring: online, periodic and remote. Online condition monitoring is defined as the continuous monitoring of machines or production processes, with data collected on critical speeds and changing spindle positions (“Condition Monitoring of Rotating Machines,” Istec International).
Periodic condition monitoring, which is achieved through vibration analysis, “gives insight into changing vibration behavior of installations” with a trend analysis (“Condition Monitoring of Rotating Machines,” Istec International). Lastly, remote condition monitoring, as its name suggests, allows equipment to be monitored from a remote location, with data transmitted for analysis.
Before establishing a predictive maintenance program, an organization must take several steps, which include:
- Analyzing the need and equipment history
- Reviewing any and all available records on downtime, equipment defects, losses (yield and energy), potential regulation fines and workplace safety
- Establishing definitions and concepts as well as building a case for PdM
- Educating major stakeholders and getting buy-in
- Completing an equipment inventory and appraising the current equipment conditions
- Selecting equipment for the program’s initial implementation
- Developing system details based on individual systems and/or components
- Evaluating any existing preventive or predictive maintenance
- Deciding which systems to include and what to inspect for
- Defining the program’s criticality and establishing PdM frequency and schedule type
- Evaluating the anticipated resources and assigning personnel roles and responsibilities
- Organizing the program and integrating it into the scheduling system
- Educating and obtaining buy-in from operations and maintenance
- Upgrading equipment and conducting training
- Creating a computerized maintenance management systems (CMMS)
Advantages and Disadvantages of Predictive Maintenance
As mentioned, the advantages of predictive maintenance are tremendous from a cost-savings perspective and include minimizing planned downtime, maximizing equipment lifespan, optimizing employee productivity and increasing revenue (Immerman, “The Impact of Predictive Maintenance on Manufacturing”). Another advantage of predictive maintenance is its ability to transform both a maintenance team and an organization, as implementing PdM allows asset managers to improve outcomes and better balance priorities such as profitability and reliability.
One of the main disadvantages of predictive maintenance is the amount of time it takes to assess and implement a PdM schedule. With predictive maintenance being a complex initiative, plant personnel must be trained on how to not only use the equipment but also how to interpret the analytics (or data).
While many organizations choose to train existing employees on predictive maintenance, there are condition-monitoring contractors who specialize in performing the required labor and analyzing the results for a facility. In addition to the training costs, predictive maintenance involves an investment in maintenance tools and systems. This cost has decreased over time with the introduction of cloud-based technology.
Predictive Maintenance Technologies
As the name suggests, the goal of predictive maintenance is to predict when maintenance is needed. While there is no Magic 8-Ball, there are several condition-monitoring devices and techniques that can be employed for effectively predicting failure, as well as providing advanced warning for maintenance on the horizon.
Known as a nondestructive or nonintrusive testing technology, infrared (IR) thermography in predictive maintenance is widely used. With IR cameras, personnel are able to detect high temperatures (aka, hotspots) in equipment. Worn components, including malfunctioning electrical circuits, typically emit heat that will display as a hotspot on a thermal image (“Predictive Maintenance,” Lean Manufacturing Tools).
By quickly identifying hotspots, infrared inspections can pinpoint problems and help avoid costly repairs and downtime. Infrared technology is considered “one of the most versatile predictive maintenance technologies available … used to study everything from individual components of machinery to plant systems, roofs and even entire buildings,” (Control Engineering). More uses for infrared technology include detecting thermal anomalies and problems with process systems relying on heat retention and/or transfer.
With acoustic technologies, personnel can detect gas, liquid or vacuum leaks in equipment on a sonic or ultrasonic level. Considered less expensive than ultrasonic technology, sonic technology is useful on mechanical equipment but limited in its use. Ultrasonic technology has more applications and is more reliable in detecting mechanical issues.
It allows a technician to “hear friction and stress in rotating machinery, which can predict deterioration earlier than conventional techniques” (“Predictive Maintenance,” Wikipedia) by using instrumentation to convert sounds in the 20- to 100-kilohertz range into “auditory or visual signals that can be heard/seen by a technician. These high frequencies are the exact frequencies generated by worn and underlubricated bearings, faulty electrical equipment, leaky valves, etc.” (Wright, “How to Leverage Multiple Predictive Maintenance Technologies”).
While both sonic and ultrasonic testing can be expensive, there is another form of acoustic monitoring that is quite affordable: a technician’s ears. “Something as simple as detecting an oil leak or a gearbox that sounds weird could and often does lead to the prevention of a catastrophic failure, avoiding tens of thousands of dollars in losses,” (Wright, “How to Leverage Multiple Predictive Maintenance Technologies”).
Employed primarily for high-speed rotating equipment, vibration analysis allows a technician to monitor a machine’s vibrations by using a handheld analyzer or real-time sensors built into the equipment. A machine operating in peak condition exhibits a particular vibration pattern. When components like bearings and shafts begin to wear and fail, the machine will begin to generate a different vibration pattern. By proactively monitoring the equipment, a trained technician can compare the readings against known failure modes to determine where problems are occurring.
Among the issues that can be detected with vibration analysis include misalignment, bent shafts, unbalanced components, loose mechanical components and motor problems.
Ensuring technicians are trained will be vital, as it can be difficult to predict machine failure utilizing vibration analysis. Many organizations offer in-depth training to prepare individuals for certification as vibration analysts. The only downside to using vibration analysis is the cost associated in implementing it with a PdM program.
Oil analysis is an effective tool in predictive maintenance. It enables a technician to check the oil’s condition and determine if other particles and contaminants are present. Some oil analysis tests can reveal the viscosity, presence of water or wear metals, particle counts, and the acid number or base number.
One of the benefits of using oil analysis is that the initial test(s) will set a baseline for a new machine. When done properly, oil analysis can yield a myriad of results to help make predictive maintenance successful.
Along with these techniques, facilities may use other technologies such as motor condition analysis, which details the operating and running condition of motors; and eddy current analysis, which identifies changes in tube wall thickness within centrifugal chillers and boiler systems. Borescope inspections, CMMS, data integration and condition monitoring can also help facilitate predictive maintenance. While there are several different technologies to aid in your PdM efforts, it is vital to choose the right one to ensure success.
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