What is Integrated Vehicle Health Management?

Integrated Vehicle Health Management (IVHM) is a natural next step from Condition Based Maintenance (CBM), where parts are replaced when they fail or once certain threshold is passed; to predictive maintenance, where parts are repaired or replaced before it fails or/and at an optimum time.

IVHM capability encompasses set of activities to identify, mitigate and resolve faults in a vehicle (Automotive, Aeroplane, Heavy Equipment, Wind Turbine, and Power Plant et al) or structure (Bridges, Railway Lines etc). It is not a challenge to do these manually but, IVHM objective is to do these activities using an automated system to increase reliability. In a recent survey human error in maintenance task has been estimated as the contributing factor for 15% of the aircraft incidents. IVHM will definitely reduce such human errors to almost nil.

IVHM comprises various technologies that can be used across a number of technologies for business benefit. It aims to equip the vehicle or structure with on-board (embedded) and off-board (at Service Bay) smart sensors and algorithms to enable diagnosis, fault isolation and prognosis, and then disseminate the results on demand for appropriate use in a timely manner. The development of such systems can improve vehicle or structural safety, reduce maintenance costs, and improve vehicle readiness by identifying potential faults and failures (diagnosis), predicting the onset of faults (prognosis), taking the proper corrective actions, and alerting the relevant stakeholders. 

Fig 1: Effect of IVHM

Benefits of IVHM
IVHM benefits are many. In fact IVHM will be the de facto standard in future. The main aim of IVHM is to implement better vehicle management and fleet health. Some of the major benefits derived out of IVHM:

• Higher safety and increased reliability due to use of real-time diagnostics and prognostics to fix faults before they creates an issue.

• Improving vehicle availability through reduced scheduled and unscheduled downtime resulting in increased operational efficiency. This is critical for expensive vehicles or equipment (e.g. aircraft, power generating turbine etc) whose downtime costs high for the owner.

• Decision support for fleet maintenance and operational management.

• Increasing component life by not disposing it off before its end of life.

• Reduced inspection time

Simplistic Architecture of IVHM
While IVHM technology has a wide use across all vehicles, equipment and structures, its use in commercial aircraft is comparatively recent and still evolving. The following diagram will provide a typical high level architecture of IVHM.

Fig 2: Information flow in IVHM

Typical Workflow of IVHM

Open System Architecture for Condition-Based Maintenance (OSA-CBM) specification is a standard architecture for moving information in a condition-based maintenance system. It is an implementation of the ISO-13374 functional specification which adds data structures and defines interface methods for the functionality blocks defined by the ISO standard.

ISO 13374 guides information flow in the following hierarchical order for any IVHM system.

a) Application specific low-level functions:

• Data Acquisition: Converting Sensor output to a digital data.

•  Data Manipulation: Implement low-level signal processing  of  the raw measurements

•  State Detection: Detects abnormalities and supports modeling of normal operations.

b) Decision support related to system health management:

• Health Assessment: Provides Diagnostics of fault and /or health condition

•  Prognostics Assessment: Forecast fault and/or health condition based on current data and projected usage loads and computes remaining useful life.

•  Advisory Generation: Provides actionable information related to health management.

Aerospace IVHM Services

Typically aircraft OEMs or their associates offer three levels of IVHM services to the operators:

Real-time monitoring: Monitoring service provides real-time Aircraft status (Engine, structure, Cabin data, avionics etc) via wireless connectivity links like ACARS (Aircraft Communications Addressing and Reporting System) or Inmarsat’s SwiftBroadband communication to the Ground Services Network (GSN). Real-time monitoring service can alert users and exports data for Analysis and assessment.

Data Management: Uploading and downloading of Aircraft Data. Delivering decrypted, decompressed and converted data to users. A well architected data warehousing solution is required for this.

Data Analytics: Involves both Data Mining and Data Analytics services to support investigative analysis, performance monitoring, data processing to detect predefined aircraft behavior, prognostics, data trending, usage base monitoring, statistical analysis, alert users etc. It should also compare own aircraft / fleet data with same aircraft type fleet wide data.

The last two involves intense IT and data analytics work.

Aerospace IVHM Development and Big DataAs

per my understanding the success of IVHM depends on ability to detect anomalies, diagnose problems, make prognostic and mitigation decision based on huge heterogeneous data from various systems, sub-systems and components. This is where I see a big opportunity for the data scientists.

The data generated from various aviation systems (aircraft, associated systems and people) have all the characteristics (Volume, Variety, Velocity, Variability, Veracity and Complexity) of Big Data. It is a mix of structured, unstructured and semi-structured type data (both numeric and textual data) which may include:

• Real-time sensor data from Aircraft

• Test report or narratives describing any safety incident during flight

• Aircraft maintenance logs

• Operational manuals

• Weather condition

• Passenger information

• Market information

• Airline information

• Airport operation data

• Aircraft data

• Flight tracking data etc.

As per my understanding the greatest challenge is to transform these huge heterogeneous data sets into actionable knowledge (revealing data patterns frequently occurring before these events) and establish interdependence / relationship that will help in detection, diagnosis, prognosis and mitigation at various levels (Aircraft Level, Fleet Level, Country Level etc). Non-uniform and non-standard data due to various legacy and disparate infrastructure across aviation data sources adds to the difficulty in integrating and analysing the data.

Nevertheless, this broad data set is essential to measure aerospace performance, safety and operational efficiency. Isolated /uniform information sets (viz weather report, radar tracking data) only provides a fraction of relevant information, but do not provide the required context, perspective and details to create actionable knowledge.

The industry is still looking for a good Data Mining technique in place to integrate all (weather, radar, crew, IVHM, aircraft, airline, flight etc) in an organised uniform way so that queries can be automated by aviation system at any level (Flight, airline fleet and same aircraft type fleet wide).

Fig 4: Data Flow between the Ground Stations and Aircraft

IVHM Market
In a recent survey the global commercial aircraft health monitoring system market was estimated to be approximately $2.3 billion in 2014 and is expected to be around $3.5 billion by 2020, growing at 7% CAGR. Boeing and Airbus enjoy duopoly over this market, capturing more than 60% of the market share. The market size includes revenues from both line fit and retro-fit market.

Airbus, Boeing and GE Aviation are the top three IVHM players in the market. Bombardier, world’s third largest commercial aircraft manufacturer is in the process of developing and deploying it for its ‘C’ Series commercial and Gobal 7000/8000 business jet programs. Other key players include United Technologies (Pratt & Whitney), Rolls Royce, Meggitt and Honeywell International.

IVHM is also widely used in military application. The U.S. Air Force uses system from Integrated Defense Systems (IDS) of Boeing for F-15, C-130, and T-38 programs. A system is also being developed by IDS for AH-64D Apache Longbow and C/MH-47F/G helicopters.

According to the analysts growth in IVHM will be driven mainly by:

• Single aisle aircraft segment (A320, B737, Bombardier C Series etc) with the rise of production.

• Wide body aircrafts like B777, B787and A330 for engine health monitoring systems for the retro-fit market.

• Very Large Aircrafts (A380 & Boeing 747) for structural health monitoring system, aero-propulsion, and ancillary systems for the line fit market.

• China, Japan, India, Middle East, Asia-Pacific and Brazil are projected to be the key growth regions.

IDIS is also working with the U.S. Army and suppliers to develop a condition based maintenance approach for the Advancements in IVHM technologies are expected to fuel the growth of this market. Key players such as Boeing, Airbus and GE Aviation are expected to implement artificial intelligence based technology that can extract relevant intelligence from the data, enabling increased fault detection and prognostics. The recent technological advancements in artificial intelligence based detection technology through a secure web service has brought one of the most significant improvements in rotorcraft safety management, halving the number of undetected faults compared to the existing systems.

Generally, an IVHM unit includes an on-board health management unit that communicates to a ground services network for storage, further analysis, and alert management by providing configurable acquisition, configurable algorithms, wireless communication links, maintenance data servers, embedded web-servers, real-time parameter displays, and data bus interfaces.

By developing a comprehensive web-based aircraft health management service that provides a high fidelity interpretation of all data, key players in this market have made it possible for operators to monitor fleet trends and detect and predict anomalies with greater confidence. An advanced data transmission software enables a quick, smart, and automatically updated 24/7 web connection between the customer base and the central data repository.

Customer interest in the IVHM technology is driven by the need for improved operational availability, lower costs, longer service life, and the increasing complexity of the aircraft. Typically, the sensors and the data bus on-board an aircraft, can predict the condition of an aircraft and the readiness for future missions. The challenge is to convert this data into information that is specific, pertinent, and accurate.