Moving To Condition-Based Maintenance (CBM)

The Evolution of Maintenance

One of the major tenants of Reliability Centered Maintenance (RCM) is that enterprises should apply maintenance strategies to assets depending on the asset’s importance to the enterprise’s mission and its inherent reliability. Maintenance strategies have evolved over time as organizations have sought to assure high asset reliability and availability with a reasonable maintenance investment. A major challenge for any maintenance organization is to apply the appropriate maintenance strategy to each individual asset so that the organization’s overall goals and objectives can be attained at minimal cost.

First -- “Run-to-failure”. The most basic maintenance strategy available is “run to failure” in which an asset is operated until it fails or breaks. Then it is repaired with reactive or corrective maintenance which may involve repair or replacement. This is still an appropriate maintenance strategy for many non-critical assets.

Second -- “Preventive”. However, some asset failures have expensive and far-reaching consequences. These failures can shut down entire production lines, make buildings unusable, or even cause injuries or fatalities. Organizations place an imperative on avoiding these types of failures. Thus, a different maintenance strategy evolved to accomplish the objective of avoiding asset failures – preventive maintenance. The idea of preventive maintenance is look at the failure history of an asset, and to conduct maintenance to “fix” it before there is a meaningful probability of its failing in the first place. In this manner, a preventive maintenance strategy prevents an asset from failing.

Because the preventive maintenance program for each asset is different and all preventive maintenance needs to be performed on an exact schedule to be effective, Computerized Maintenance Management Systems (CMMS) were developed to help manage this complexity. Preventive maintenance is a core activity of many maintenance organizations today, and it does keep assets operating reliability and performing well.

Preventive maintenance works because it delivers high asset availability and minimizes unscheduled downtime. For those assets critical to operations, preventive maintenance avoids the severe consequences that asset failure can cause.

Unfortunately, the benefits of preventive maintenance come at a price. By its very nature, preventive maintenance means that maintenance is being performed more often than is necessary. Since maintenance consumes both labor and parts, this strategy has a measureable cost of “over-maintenance.” Additionally, preventive maintenance often requires that assets be taken off-line during servicing, incurring a cost to the organization for this downtime and lost capacity. Finally, more frequent maintenance involves more frequent intrusions into the equipment, which itself increases the chance of asset or system failures.

Finally, “Condition-based Maintenance”. Because preventive maintenance is expensive, and because enterprises are increasingly pressured to reduce their costs, organizations are developing a new type of maintenance strategy. Under this strategy, the condition of the asset is monitored regularly until it begins to give evidence of deteriorating performance or incipient failure. Maintenance is then performed “just-in-time” to prevent asset failure.
The promise of this new strategy – predictive maintenance or condition-based maintenance – is that the overall costs of maintenance can be reduced while providing the high asset availability and performance that preventive maintenance delivers. The current wave of innovation in asset maintenance today is developing predictive or condition-based maintenance strategies.

Condition-Based Maintenance Is Growing

Condition-based or predictive maintenance can help lower maintenance costs even compared to a sophisticated preventive maintenance approach. Condition-based maintenance uses real-time information on asset conditions to identify when maintenance is necessary, allowing maintenance to be deferred until needed. Savings comes not just from consuming less labor and parts in maintenance, but also from incurring less downtime and creating less frequent infant mortality.

There is an important but poorly defined difference between predictive maintenance and condition-based maintenance. Predictive maintenance is generally triggered by analysis of equipment condition data that is gathered periodically and manually. Most equipment vibration analysis and lubrication analysis, for example, is conducted on a scheduled basis to identify deteriorating conditions that require maintenance. This contrasts with condition-based maintenance in which equipment condition data is collected continuously and analyzed in real-time. Condition-based maintenance is still a relatively new approach, but is used more frequently on critical equipment in process industries such as refineries and power plants.

There are a number of factors that have limited the adoption of condition-based maintenance besides the fact that it is a relatively new strategy. Most of the equipment that could be subject to condition-based maintenance is not currently instrumented. Data on equipment condition cannot be collected without installing sensors on the equipment along with a means of collecting the sensor data. Even when equipment is properly instrumented to track operating parameters that could identify incipient failure, the sensors are not connected into a data collection network that allows real-time monitoring. These instruments or sensors usually provide local displays or store readings in data loggers, and data is collected from them by technicians that visit the equipment periodically. Such manual data collection is expensive, subject to error, and not always timely.

Even when equipment is instrumented and connected to a central monitoring point, this is often not sufficient for adopting condition-based maintenance. Usually equipment is monitored in this manner as part of a production, process or building control system. These automation systems track equipment and process parameters that are needed to monitor and control the equipment. These parameters are usually not the ones that monitor potential equipment failure modes and that identify a need for maintenance. For a pump driven by an electric motor, for instance, an automation system will usually track flow rates, upstream and downstream pressures, and motor RPMs. Condition-based maintenance would instead require monitoring bearing temperatures, vibration signatures, and motor current draw. Most automation systems do not track the necessary parameters for implementing condition-based maintenance.

Enabling Condition-Based Maintenance

The prospects for condition-based maintenance are improving rapidly, however. Condition-based maintenance is being enabled by several advances, but especially by advances in networking technology. Many business processes and employees have become much more productive and efficient over the last decade as they have become connected to information resources and each other by the spread of the Internet and related networking technologies. While people have become connected, machines and other assets have not yet been brought into networks.

But that is changing as the pervasive Internet is branching out to connect a wide range of equipment and devices. Because the cost of retrofitting wire to connect these devices is prohibitively expensive, wireless technologies are the growing method for making these connections. In particular, wireless sensor networks are a new technology that is connecting machines and other devices in a broad range of applications. This phenomenon is becoming a significant enabler of condition-based maintenance.

Wireless sensor networking is a relatively new technology that is designed to connect machines through the Internet the same way that WiFi has been broadly adopted to connect laptops and other computing devices. Aleier’s sister company, Cirronet, makes a wide range of wireless sensor networking equipment that differs in communication range, sensor connections, battery life and prices to address the requirements of many applications. This capability is becoming more broadly available as Cirronet and the other companies that provide wireless sensor networking solutions continue to refine and reduce the costs of their products.

Implementing Condition-Based Maintenance

Computerized Maintenance Management Systems, or CMMS’s, are the well-established application tool that has been used to plan and manage the maintenance function in organizations of all sizes. Over the past decade, Enterprise Asset Management (EAM) systems have been built on this maintenance foundation to help organizations manage all of the operational activities of managing assets over their complete life cycle, from their design, procurement and commissioning all the way through their retirement and disposal.

Enterprise Asset Management applications deliver a number of benefits to an organization when they are fully utilized. Of course, they help lower maintenance costs by making maintenance personnel and the parts inventory more productive. But they also help enterprises to improve the availability and performance of those assets, and to better achieve the primary mission those assets are intended to perform.

An Enterprise Asset Management application also helps reduce the need for asset investment in the long run. One of the ways that an EAM helps minimize long-term asset investment and improve maintenance productivity is by enabling enterprises to implement the correct maintenance strategy for each asset. The EAM system assists organizations in deciding which assets deserve the investment in condition-based maintenance; require the attention of preventive maintenance, and those that should be operated as “run to failure.” The EAM then implements and manages the appropriate strategy for each asset, including condition-based maintenance.

The Aleier FM1j Enterprise Asset Management application includes condition-based maintenance capabilities. FM1j collects and stores equipment condition data, regardless of how that data is captured. The system then analyzes the data as it is received, using an appropriate predictive algorithm or rule, to identify when the equipment requires maintenance. Finally FM1j creates an appropriate response, which usually means creating a workorder to perform the desired maintenance activity on the equipment.

A rule, or a set of rules, defines the triggers that determine a need for condition-based maintenance. Rules can be simple or complex, depending on the failure modes of the equipment. They can include exceeding a threshold value, exceeding that threshold for an extended time, exhibiting an excessive rate of change in a reading, reaching an excessive difference between the readings of two sensors, and so on. FM1j also allows a range of responses to be pre-defined, including sending alerts or automatically turning off equipment in addition to generating a traditional maintenance workorder. Aleier’s EAM has a rich set of capabilities to help organizations implement condition-based maintenance strategies across a broad spectrum of equipment.

The Future of Asset Management

Enterprises now have more options to assure the availability and continued performance of their assets while minimizing the costs to keep them in service. These organizations can choose the appropriate maintenance strategy for each asset, depending on how critical it is to operations, how frequently it fails, and its ability to be automatically and continuously monitored. New technologies are enabling enterprises to improve the management of their assets, including the ability to employ condition-based maintenance on more of their equipment. New technologies are a primary enabler of condition-based maintenance, which is the latest major innovation in the area of asset management.