Integrated vehicle health management

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Integrated vehicle health management (IVHM) or integrated system health management (ISHM) is the unified capability of systems to assess the current or future state of the member system health and integrate that picture of system health within a framework of available resources and operational demand. [1]

Contents

Aims of IVHM

The aims of IVHM are to enable better management of vehicle and vehicle fleet health.

This is achieved through correct use of reliable sensing and prognosis systems to monitor part health and also using usage data to assist in understanding the load experienced and likely future vehicle load.

History

Origins

It has been suggested that IVHM as a named concept has been around since the 1970s. [2] However, there does not seem to be much in the way of written evidence of this. IVHM as a concept grew out of popular aviation maintenance methods. It was a natural next step from condition based maintenance. As sensors improved and our understanding of the systems concerned grew, it became possible to not just detect failure but also to predict it. The high unit cost & high maintenance cost of aircraft & spacecraft made any advance in maintenance methods very attractive. NASA [3] was one of the first organisations to use the name IVHM to describe how they wanted to approach maintenance of spacecraft in the future. They created NASA-CR-192656, [4] in 1992 with the assistance of the General Research Corporation and the Orbital Technologies Corporation. [5] This was a goals & objectives document in which they discussed the technology and maintenance concepts that they believed would be necessary to enhance safety while reducing maintenance costs in their next generation vehicles. Many companies since then have become interested in IVHM and body of literature has increased substantially. There are now IVHM solutions for many different types of vehicle from the JSF to commercial haulage vehicles.

First space prognostics

The first published history of predicting spacecraft equipment failures occurred on the 12 Rockwell/U.S. Air Force Global Positioning System Block I (Phase 1) satellites using non-repeatable transient events (NRTE) and GPS Kalman filter data from the GPS Master Control Station, between 1978 and 1984 by the GPS Space and Ground Segment Manager. NRTEs were isolated to the GPS satellites after mission operations support personnel replayed the real-time satellite telemetry ruling out RF and land-line noise caused from poor Eb/No or S/N and data acquisition and display system processing problems. The GPS satellite's subsystem equipment vendors diagnosed the NRTEs as systemic noise that preceded the equipment failures because at the time, it was believed that all equipment failures occurred instantaneously and randomly and so equipment failures could not be predicted (e.g. equipment failures exhibited memoryless behavior). Rockwell International GPS Systems Engineering Manager ordered a stop to predicting GPS satellite equipment failures in 1983 claiming it wasn't possible and the company was not on contract to do so. The prognostic analysis that was completed on the GPS satellite telemetry was published quarterly contractually as a CDRL to the GPS Program Office personnel and a wide variety of Air Force subcontractors working on the GPS program.

Further development

One of the key milestones in the creation of IVHM for aircraft was the series of ARINC standards that enabled different manufacturers to create equipment that would work together and be able to send diagnostic data from the aircraft to the maintenance organisation on the ground. [6] ACARS is frequently used to communicate maintenance and operational data between the flight crew and the ground crew. This has led to concepts which have been adopted in IVHM.

Another milestone was the creation of health and usage monitoring systems(HUMS) for helicopters operating in support of the Oil rigs in the North Sea. This is key concept that usage data can be used to assist maintenance planning. FOQA or Flight Data systems are similar to HUMS as they monitor the vehicle usage. They are useful for IVHM in the same way as they allow the usage of the vehicle to be thoroughly understood which aids in the design of future vehicles. It also allows excessive loads and usage to be identified and corrected. For example, if an aircraft was experiencing frequent heavy landings the maintenance schedule for the undercarriage could be changed to ensure that they are not wearing too fast under the increased load. The load carried by the aircraft could be lessened in future or operators could be given additional training to improve the quality of the landings.

The growing nature of this field led Boeing [7] to set up an IVHM centre with Cranfield University in 2008 to act as a world leading research hub. [8] The IVHM centre has since then offered the world's first IVHM Msc course and hosts several PhD students researching the application of IVHM to different fields.

Philosophy

This graphic depicts the information flow within the IVHM concept as described by Professor Ian Jennions et al. of the IVHM Centre, Cranfield University. This graphic also appears in a similar form in the 2011 IVHM book. IVHM Graphic.pdf
This graphic depicts the information flow within the IVHM concept as described by Professor Ian Jennions et al. of the IVHM Centre, Cranfield University. This graphic also appears in a similar form in the 2011 IVHM book.

IVHM is concerned not just with the current condition of the vehicle but also with health across its whole life cycle. IVHM examines the vehicle health against the vehicle usage data and within the context of similar information for other vehicles within the fleet. In use vehicles display unique usage characteristics and also some characteristics common across the fleet. Where usage data and system health data is available these can be analysed to identify these characteristics. This is useful in the Identification of problems unique to one vehicle as well as identifying trends in vehicle degradation across the entire fleet.

IVHM is a concept for the complete maintenance life cycle of a vehicle (or machine plant installation). It makes extensive use of embedded sensors and self-monitoring equipment combined with prognostics and diagnostic reasoning. In the case of vehicles it is typical for there to be a data acquisition module on-board and a diagnostic unit. Some vehicles can transfer selected data back to base while in use through various rf systems. Whenever the vehicle is at base the data is also transferred to a set of maintenance computers that also process that data for a deeper understanding of the true health of the vehicle. The usage of the vehicle can also be matched to the degradation of parts and improve the prognostics prediction accuracy.

The remaining useful life is used to plan replacement or repair of the part at some convenient time prior to failure. The inconvenience of taking the vehicle out of service is balanced against the cost of unscheduled maintenance to ensure that the part is replaced at the optimum point prior to failure. This process has been compared to the process of choosing when to buy financial options as the cost of scheduled maintenance must be balanced against the risk of failure and the cost of unscheduled maintenance. [10]

This differs from Condition-based maintenance(CBM) where the part is replaced once it has failed or once a threshold is passed. [11] This often involves taking the vehicle out of service with at an inconvenient time when it could be generating revenue. It is preferable to use an IVHM approach to replace it at the most convenient time. This allows the reduction in waste component life caused by replacing the part too early and also reducing cost incurred by unscheduled maintenance. This is possible due to the increased prognostic distance provided by an IVHM solution. There are many technologies that are used in IVHM. The field itself is still growing and many techniques are still being added to the body of knowledge.

Architecture

Health monitoring sensors are designed into the vehicle and report to a data processing unit. Some of the data may be manipulated on board for immediate system diagnosis and prognosis. Less time critical data is processed off board. All the historical data for the vehicle can be compared with current performance to identify degradation trends at a more detailed level than could be done on board the vehicle. This is all used to improve reliability and availability and the data is also fed back to the manufacturer for them to improve their product. [12]

A standard architecture for IVHM has been proposed as the OSA-CBM [13] standard which gives a structure for data gathering, analysis and action. This is intended to facilitate interoperability between IVHM systems of different suppliers. The key parts within OSA-CBM are

These are laid out within ISO 13374 [14]

The system is not intended to replace safety critical warnings such as an aircraft's flight management system but instead to complement them and perhaps also leverage existing sensors for assistance with system health monitoring. Ideal systems to monitor are those systems, subsystems & structural elements which are likely to show graceful degradation so that they can be repaired or replaced at a convenient time prior to failure. This gives a saving over condition based maintenance as once a part has failed often a vehicle cannot be used until repaired. This often results in scheduling difficulties if the vehicle fails when it was needed for revenue generation and cannot be used. In contrast IVHM can be used to replace the part during vehicle downtime prior to failure. This ensures that it can continue to generate revenue as scheduled.

Communications between the vehicle and the maintenance organisation are crucial to fixing faults in a timely manner. The balance of how much data should be sent to the maintainer during use and how much should be downloaded while in maintenance is a one that must be judged carefully. One example of this is what is known as fault forwarding. When an aircraft experiences a fault the flight management system reports it to the flight crew but also sends a message through ACARS to the maintenance team so that they can start their maintenance planning before the aircraft has landed. This yields a time advantage as they know some of the parts and personnel required to fix the fault before the aircraft has landed. However the communication link does cost money and has a limited bandwidth so the worth of this health & usage data must be judged carefully with consideration given as to whether it should be transmitted or merely downloaded during the next maintenance or as part of the operator shutdown process.

Related Research Articles

<span class="mw-page-title-main">Telemetry</span> Data and measurements transferred from a remote location to receiving equipment for monitoring

Telemetry is the in situ collection of measurements or other data at remote points and their automatic transmission to receiving equipment (telecommunication) for monitoring. The word is derived from the Greek roots tele, 'remote', and metron, 'measure'. Systems that need external instructions and data to operate require the counterpart of telemetry: telecommand.

<span class="mw-page-title-main">Maintenance</span> Maintaining a device in working condition

The technical meaning of maintenance involves functional checks, servicing, repairing or replacing of necessary devices, equipment, machinery, building infrastructure, and supporting utilities in industrial, business, and residential installations. Over time, this has come to include multiple wordings that describe various cost-effective practices to keep equipment operational; these activities occur either before or after a failure.

<span class="mw-page-title-main">Safety-critical system</span> System whose failure would be serious

A safety-critical system or life-critical system is a system whose failure or malfunction may result in one of the following outcomes:

<span class="mw-page-title-main">Telematics</span> Interdisciplinary field that encompasses telecommunications

Telematics is an interdisciplinary field encompassing telecommunications, vehicular technologies, electrical engineering, and computer science. Telematics can involve any of the following:

Prognostics is an engineering discipline focused on predicting the time at which a system or a component will no longer perform its intended function. This lack of performance is most often a failure beyond which the system can no longer be used to meet desired performance. The predicted time then becomes the remaining useful life (RUL), which is an important concept in decision making for contingency mitigation. Prognostics predicts the future performance of a component by assessing the extent of deviation or degradation of a system from its expected normal operating conditions. The science of prognostics is based on the analysis of failure modes, detection of early signs of wear and aging, and fault conditions. An effective prognostics solution is implemented when there is sound knowledge of the failure mechanisms that are likely to cause the degradations leading to eventual failures in the system. It is therefore necessary to have initial information on the possible failures in a product. Such knowledge is important to identify the system parameters that are to be monitored. Potential uses for prognostics is in condition-based maintenance. The discipline that links studies of failure mechanisms to system lifecycle management is often referred to as prognostics and health management (PHM), sometimes also system health management (SHM) or—in transportation applications—vehicle health management (VHM) or engine health management (EHM). Technical approaches to building models in prognostics can be categorized broadly into data-driven approaches, model-based approaches, and hybrid approaches.

Condition monitoring is the process of monitoring a parameter of condition in machinery, in order to identify a significant change which is indicative of a developing fault. It is a major component of predictive maintenance. The use of condition monitoring allows maintenance to be scheduled, or other actions to be taken to prevent consequential damages and avoid its consequences. Condition monitoring has a unique benefit in that conditions that would shorten normal lifespan can be addressed before they develop into a major failure. Condition monitoring techniques are normally used on rotating equipment, auxiliary systems and other machinery like belt-driven equipment,, while periodic inspection using non-destructive testing (NDT) techniques and fit for service (FFS) evaluation are used for static plant equipment such as steam boilers, piping and heat exchangers.

Fleet management is the management of:

<span class="mw-page-title-main">Predictive maintenance</span> Method to predict when equipment should be maintained

Predictive maintenance techniques are designed to help determine the condition of in-service equipment in order to estimate when maintenance should be performed. This approach promises cost savings over routine or time-based preventive maintenance, because tasks are performed only when warranted. Thus, it is regarded as condition-based maintenance carried out as suggested by estimations of the degradation state of an item.

Machine to machine (M2M) is direct communication between devices using any communications channel, including wired and wireless. Machine to machine communication can include industrial instrumentation, enabling a sensor or meter to communicate the information it records to application software that can use it. Such communication was originally accomplished by having a remote network of machines relay information back to a central hub for analysis, which would then be rerouted into a system like a personal computer.

<span class="mw-page-title-main">Flight controller</span> Person who aids in spaceflight activities

Flight controllers are personnel who aid space flight by working in such Mission Control Centers as NASA's Mission Control Center or ESA's European Space Operations Centre. Flight controllers work at computer consoles and use telemetry to monitor various technical aspects of a space mission in real-time. Each controller is an expert in a specific area and constantly communicates with additional experts in the "back room". The flight director, who leads the flight controllers, monitors the activities of a team of flight controllers, and has overall responsibility for success and safety.

Medical equipment management is a term for the professionals who manage operations, analyze and improve utilization and safety, and support servicing healthcare technology. These healthcare technology managers are, much like other healthcare professionals referred to by various specialty or organizational hierarchy names.

<span class="mw-page-title-main">Brüel & Kjær</span> Danish multinational company

Brüel & Kjær is a Danish multinational engineering and electronics company headquartered in Nærum, near Copenhagen. It was the largest producer in the world of equipment for acoustic and vibrational measurements. Brüel & Kjær is a subsidiary of Spectris.

A vehicle tracking system combines the use of automatic vehicle location in individual vehicles with software that collects these fleet data for a comprehensive picture of vehicle locations. Modern vehicle tracking systems commonly use GPS or GLONASS technology for locating the vehicle, but other types of automatic vehicle location technology can also be used. Vehicle information can be viewed on electronic maps via the Internet or specialized software. Urban public transit authorities are an increasingly common user of vehicle tracking systems, particularly in large cities.

<span class="mw-page-title-main">Spaceworthiness</span> Measure of the quality of spacecraft

Spaceworthiness, or aerospaceworthiness, is a property, or ability of a spacecraft to perform to its design objectives and navigate successfully through both the space environment and the atmosphere as a part of a journey to or from space. The concept may less commonly be extended to other devices, such as spacesuits, which are designed to spend some amount of time exposed to space.

Health and usage monitoring systems (HUMS) is a generic term given to activities that utilize data collection and analysis techniques to help ensure availability, reliability and safety of vehicles. Activities similar to, or sometimes used interchangeably with, HUMS include condition-based maintenance (CBM) and operational data recording (ODR). This term HUMS is often used in reference to airborne craft and in particular rotor-craft – the term is cited as being introduced by the offshore oil industry after a commercial Chinook crashed in the North Sea, killing all but one passenger and one crew member in 1986.

Fault forwarding is a maintenance technique which is used to decrease the time taken to repair a vehicle. The problem is reported by the vehicle while it is in use and the maintenance team plan their repair before they have access to the vehicle. Therefore, when the vehicle is with them they will already have gathered the necessary parts and expertise. Thus minimizing the time taken to return the vehicle to service.

<span class="mw-page-title-main">Wind turbine prognostics</span>

The growing demand for renewable energy has resulted in global adoption and rapid expansion of wind turbine technology. Wind Turbines are typically designed to reach a 20-year life, however, due to the complex loading and environment in which they operate wind turbines rarely operate to that age without significant repairs and extensive maintenance during that period. In order to improve the management of wind farms there is an increasing move towards preventative maintenance as opposed to scheduled and reactive maintenance to reduce downtime and lost production. This is achieved through the use of prognostic monitoring/management systems.

An intelligent maintenance system (IMS) is a system that uses collected data from machinery in order to predict and prevent potential failures in them. The occurrence of failures in machinery can be costly and even catastrophic. In order to avoid failures, there needs to be a system which analyzes the behavior of the machine and provides alarms and instructions for preventive maintenance. Analyzing the behavior of the machines has become possible by means of advanced sensors, data collection systems, data storage/transfer capabilities and data analysis tools. These are the same set of tools developed for prognostics. The aggregation of data collection, storage, transformation, analysis and decision making for smart maintenance is called an intelligent maintenance system (IMS).

A digital twin is a digital model of an intended or actual real-world physical product, system, or process that serves as the effectively indistinguishable digital counterpart of it for practical purposes, such as simulation, integration, testing, monitoring, and maintenance. The digital twin is the underlying premise for Product Lifecycle Management and exists throughout the entire lifecycle of the physical entity it represents. Since information is detailed, the digital twin representation is determined by the value-based use cases it is created to implement. The digital twin can exist before the physical entity, as for example with virtual prototyping. The use of a digital twin in the creation phase allows the intended entity's entire lifecycle to be modeled and simulated. A digital twin of an existing entity may be used in real time and regularly synchronized with the corresponding physical system.

References

  1. Jennions, I.K, Integrated Vehicle Health Management: Perspectives on an Emerging Field URL:http://books.sae.org/book-r-405
  2. Aaseng, G.B. Blueprint for an integrated vehicle health management system. In proceedings of the 20th Digital Avionics Systems Conference, Daytona Beach, Florida, USA, 14–18 October, vol. 1, pp. 3.C.1-1-3.C.1-11
  3. NASA.gov
  4. National Aeronautics and Space Administration (NASA). Research and technology goals and objectives for integrated vehicle health management (IVHM). Report NASA-CR-192656, October 1992, NASA Technical Reports Server https://ntrs.nasa.gov/search.jsp?R=19930013844&hterms=192656&qs=Ntx%3Dmode%2520matchallpartial%2520%26Ntk%3DAll%26N%3D0%26Ntt%3D192656
  5. "Welcome to Orbital Technologies Corporation". Archived from the original on 2017-09-09. Retrieved 2012-04-23.
  6. Sudolsky, M; ARINC 573/717, 767 and 647A: The Logical choice for Maintenance recording and IVHM Interface Control or Frame Updates, Annual Conference of the Prognostics and Heath Management Society, 2009
  7. "Boeing in the UK: Integrated Vehicle Health Management Centre". Archived from the original on 2012-07-22. Retrieved 2012-04-23.
  8. "Integrated Vehicle Health Management Centre (IVHM)".
  9. Jennions, I.K, Integrated Vehicle Health Management: Perspectives on an Emerging Field URL:http://books.sae.org/book-r-405
  10. Haddad, G.; Sandborn, P.; Pecht, M; ," Using Real Options to Manage Condition-Based Maintenance Enabled by PHM", 2011 IEEE International Conference on Prognostics and Health Management, Denver, Colorado, 20–23 June 2011 URL: http://www.calce.umd.edu/articles/abstracts/2011/Real-Options_Manage_Condition-based_PHM_abstract.html
  11. "Condition Based Maintenance Strategy for Equipment Failure Prevention". Archived from the original on 2012-04-03. Retrieved 2012-05-25.
  12. Jennions, I.K; "The story so Far – Development of an IVHM Centre," 14th Australian International Aerospace Congress, 2 March 2011, URL:http://www.cranfield.ac.uk/ivhm/pdf/aiac14%20keynote.pdf%5B%5D
  13. Swearingen, K.; Majkowski, W.; Bruggeman, B.; Gilbertson, D.; Dunsdon, J.; Sykes, B.; , "An Open System Architecture for Condition Based Maintenance Overview," Aerospace Conference, 2007 IEEE pp. 1-8, 3–10 March 2007; doi: 10.1109/AERO.2007.352921. URL: https://ieeexplore.ieee.org/document/4161678
  14. ISO. Geneva, Switzerland, 2002, ISO 13374-1, Condition monitoring and diagnostics of machines – Data processing, communication and presentation – Part 1: General Guidelines. URL: http://www.iso.org/iso/iso_catalogue/catalogue_tc/catalogue_detail.htm?csnumber=21832

See also