Predictive Maintenance, or “PdM” (a component of Preventative Maintenance, or “PM”), in referring to the optimizing of the sustainment approach for a fielded asset, is attempting to facilitate and provide the means to detect and rectify failures of an equipment or system in advance of the failure(s). As such, the approach may consider the development or reliance upon a variety of specialized sensors or maintenance method(s). But determining the diagnostic or prognostic effectiveness of the sensors (BIT location, coverage, diagnostic validation, etc.) is the first step in determining the effectiveness of the prediction and sustainment methods upon the fielded asset(s).
While desiring to develop a Predictive Maintenance capability is the immediate objective, there are many costs trade-offs and factors that need to be comprehensively considered. Most of the cost and predictive capabilities may end up by constraining the sustainment alternatives and their effectiveness, which isn’t typically an initial consideration until the investment has already set the course in stone.
Often overlooked is the fact that many predictive approaches involve expertise that is costly and typically not going to be readily available when the asset is fielded – at least not available for a reasonable cost. So, unless the expertise is retained in house, and not about to be moved onto another program or possibly about to retire, then investigating predictive approaches above the low-hanging fruit may have some cost benefits to the system integrator or customer. Then there is the consideration of the limits of the expertise of the PHM or IVHM designer. Typically, this is where the preponderance of the expertise is retained at the specific piece of the design that the expert develops. which such knowledge isn’t so readily available to transfer to others. So, let’s be more careful and step back to weigh all of our options before we are persuaded to rely on a strategy that assumes that the predicting of failures is the optimum solution in every case.
With DSI’s ISDD, the assessing of the effectiveness of PdM along with any corrective sustainment approach can be performed in eXpress and also simulated in the sustainment lifecycle using “STAGE” (DSI’s Health Management and Operational Support Simulation Application). The diagnostic integrity of the system at the “system level”, or fielded product level, is where the constraints of the effectiveness of any sustainment alternative begins. Once fielded, the diagnostic or predictive maintenance capabilities will be what they minimally can be. In other words, if we aren’t certain of our diagnostic capability, then our predictive capability as determined by its presumed effectiveness, will be an uncertainty. Establishing of a “diagnostic baseline” capability provides the essential foundation required to establish where and how much should be invested into the more lavish predictive technologies or options.
ISDD, and more specifically, STAGE, provides the vetted diagnostic capability at the system level to that can provide canvas to “balance” the sustainment alternatives or approaches with their associated costs to observe their effectiveness in the sustainment lifecycle(s). In this manner, a much more holistic assessment can be performed to discover the value and diagnostic effectiveness of deploying Predictive or “Preventative” Maintenance in comparison to Corrective Maintenance, often referred to as “Run-to-Failure” maintenance, or any mix therein.
Predictive Maintenance must examine the current condition of the equipment and determine if the expected Remaining Useful Life (RUL) of any “critical” components of the system is sufficiently long enough (“Failure Horizon”) for the equipment to be used “adequately” in the next operation or mission. If so, then the equipment is able to be relied upon to complete the task, or operation, which yields a perception that this benefit of Predictive Maintenance appears to be a most desired method to ensure the operational availability objective of that equipment or complex system(s).
That said, however, do we know if this Preventative Maintenance corrective action resulted in the actual increased “availability”? Did this corrective action enable the continued use of the equipment or system while increasing the risk of safety? Did it also cause the possibility of any additional cost of a more intrusive repair action resulting from the “cascading” of the failure(s)?
While we truly don’t “know” if our data regarding the execution of the Predictive Maintenance resulted from any uncertain or wrongful indication of the existence of a failure (caused from the failure to exhaustively validate the diagnostic capability), our decision-making is based upon our presumption that our reporting of a failure regardless.
The primary goal of Predictive or Preventative Maintenance is to provide an opportunity to evade the experience of a failure by the performing of a corrective action upon a schedule repair activity, or the result of an early indication that a failure is beginning to occur, or otherwise, the discovery of an “insipient failure”.
So, the core objective of Preventative Maintenance is to repair or replace the correctly isolated “presumed to be failing” component(s) during a planned or unplanned maintenance event. In the case of the occurrence of an “unplanned” Predictive Maintenance activity, the objective would be to negotiate the “presumed to be failing” component(s) after the first signs of degradation, but before breakdown. In order to do this, signs of degradation must be detected as early and as clearly as possible.
The approaches and methods for engaging in the ideals of Predictive Maintenance practices has received a great deal of attention over the past half century. By monitoring the mechanical condition of the critical equipment using parameters and indicators such as heat distribution, vibration patterns and acoustic characteristics continuously by the help of different sensors and measurement systems, maintenance can be scheduled when needed. Over the past 10-15 years, a significant focus on the studying the “Physics of Failures” has led to a hope that, one day, most any failure can be prevented or predicted by carefully analyzing the “physics of the failure” (PoF) patterns, and creating the “sensors” to precisely observe and measure the progression of the “precursor” to the failure, a competency of “Prognostics”. This would enable the Predictive Maintenance events to be scheduled in advance of a failure based upon the Condition of sensed component(s), ultimately defined as “Condition-Based Maintenance”, or CBM.
Predictive Maintenance includes Condition-based Maintenance (CBM) when investing into designing for deploying prognostics capabilities. If prognostics include the designing of a health management system and specialized sensors to identify the physics of failure characteristics of critical components onboard a vehicle or system, then we would categorize such prognostics a capability as encompassing a PHM objective (there is much to discuss later regarding the ability to adequately perform the reconfiguration or remediation aspects of the HM). Regardless, this approach would be to provide “just in time” awareness to an impending failure and attempts to allow sufficient advance notice to remediate a failure in advance of the experiencing of a failure.
Predictive Maintenance also includes Scheduled Maintenance or Reliability-Centered Maintenance (RCM), which results from a more reliability discipline bias. As such, components are expected to fail individually, and in accordance with their specific individual reliability engineering “predicted” failure characteristics. This approach to maintenance would lead to more “scheduled” maintenance activities. Again, the objective of RCM would be to address likely failures in advance of the component failure.
Predictive Maintenance may also include “Opportunistic” Maintenance, which would target the advance replacement of components based upon the aspect of “convenience” when performing a related maintenance activity. Again, this would be performed to address system availability, operational success and safety while maybe reducing or increasing cost of ownership. Regardless, this activity is still a predictive activity that is based upon aspects of both an RCM and CBM events.
Opportunistic Maintenance is an “a la carte” sort of methodology that enables the decision-making to consider the interdependencies of the components, structures and variable costs associated with any replacement or repair activity. With ISDD, the interrelationships of any on the components, structures or designs are already established and can be fully vetted. So the building of a complex Opportunistic maintenance strategy can be levied upon any design or “integrated” systems of designs where the interdependent functional and failure properties exist. This will avail an advantage of assessing the impact of this form of preventative maintenance strategy along with any mixture of designs, processes, structures or economic parameters. Opportunistic Maintenance strategies can be effectively applied in design development for any (balance or “mixture”) of maintenance paradigms, including manufacturing, production, and field-based sustainment decision-making. With DSI Workbench, the maintenance or lab technician is fully armed with all of the diagnostic, testing, repairing or guided troubleshooting knowledge captured throughout the design development and sustainment lifecycles.
Corrective Maintenance is based upon the repair of a failed item, or “run to failure”. This is an approach that may be cost effective and is based upon the system integrator being sharp enough to actually realize how to maximize the benefit of CM along with CBM, RCM and OM. This “balancing” of implementing the optimized mix of either of these approaches to sustainment is a DESIGN INFLUENCE event.
There are a few programs out there that have fully institutionalized this Integrated Systems Diagnostics Design (ISDD) influence activity and these organizations are far ahead of any of those that fall prey to cornering themselves into producing designs that fall unchecked into one specific approach or another, rendering their approaches to be “out of balance”, inadvertently or otherwise. This is why any of the sustainment approaches need to be examined in design development (and ongoing) to determine the best “balance” or “mix’” of using any or all of these Predictive and/or Corrective Maintenance strategies.
The initial impediment to any reliability-centric approach is that it has been traditionally segregated from the deeper diagnostic engineering activities, which in turn, are typically not performed in time provide valuable input for the selecting of components and validating test coverage for the purposes of the final intended usage of the design. ISDD enables a much more robust and holistic methodology of using the validated diagnostic capability inherent to the design, and based upon any integrated interdependencies of the individual designs or components contained therein, to explore the optimal balancing of maintenance activities. ISDD goes another step further and incorporates the “maintenance philosophy” along with the design’s diagnostic capability to determine seed Operational Maintenance Simulations that also include the impact of maintenance events.
The ability to combine and assess the maintenance philosophy as required by the customer or asset owner(s) along with the captured diagnostic design knowledgebase of the asset (fielded equipment, product or “integrated system) and then directly bring that optimal balance of predictive versus corrective maintenance to the field is unique to ISDD. Furthermore, and coupled with the operational use of “DSI Workbench” (portable maintenance application), the maintenance or lab technician is fully armed with all of the diagnostic, testing, repairing or guided troubleshooting knowledge ever captured, or updated with empirical data throughout the design development and sustainment lifecycles.
Without the ability to determine the diagnostic baseline, capability and effectiveness of the design, in other approach to the use of predictive maintenance is putting the cart in front of the horse and a recipe for undeterminable diagnostic ambiguity.
A sound diagnostics engineering approach (or ISDD) performed early in the design development phase should produce invaluable information and detail to the effectiveness of any sustainment approach.