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INDUSTRIAL MAINTENANCE: PREDICTIVE MAINTENANCE OF AIRCRAFT

INDUSTRIAL MAINTENANCE: PREDICTIVE MAINTENANCE OF AIRCRAFT

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Predictive Aircraft Maintenance

The chances of a plane to stop working, experience failures, or incur repair costs are relatively low. It, however, may experience failure at the least expected time and situation. It, therefore, follows that planes only operate adequately with a valid inspection. There is also the need for regular maintenance to enhance its reliability. Furthermore, the factors that affect a plane are weakening of its structural elements due to age and mechanical and technical failures such as tire burst. Still, the development of new technology has led to the transformation of airplane maintenance systems. The inventions of more complex systems such as the planes’ data systems have led to the need for more cost-effective maintenance methods limited to the aircraft industry.

Additionally, it is difficult to quantify the value of maintenance to an aircraft in the short-run. Therefore, a more complementary strategy would help in keeping valuable flight data for a long-term application (Lundgren et al., 2018). This paper explores the aspects which allude to Predictive Maintenance of Aircraft and the need to adapt its strategies in the maintenance of planes.

The History of Maintenance of Aircraft

Ren et al. (2017) define aircraft maintenance as “all actions taken to retain material to restore it to a specified condition or serviceability” (p. 19 ) The concept began in the 1960s by the Federal Aviation Agency (FAA) on Boeing 747, DC10 and L1011 which were the first generation wide-body planes. The Hard Time principal (HT), which was using the theory of preventive maintenance in replacement and repairing of aircraft components, was the first aircraft maintenance organization. The Maintenance Steering Group (MSG) reasoning, which is the basis of the current aircraft maintenance, was later developed by the Air Transport Association (ATA). HT was one of the maintenance actions for the process-oriented perspective to maintenance alongside condition monitoring and on-condition. This perspective applied 6 different Industry Working Groups, which included physical structures, auxiliary power units, mechanical systems, flight control, and hydraulics, and regional. These groups were used to develop a suitable preliminary maintenance program (Ren et al., 2017).

The MSG has developed over time. The first one focused on coming up with a logical way of conducting the process of developing effective maintenance practices. MSG-2 was later designed to improve on the original method, which waited for a breakdown to occur to determine the appropriate actions. Then later in 1980, MSG-2 was modified by the ATA into MSG-3, adjusting the decision reasoning into a more straightforward logic. Furthermore, MSG-3 focused on the consequences of aircraft deterioration and how it affects its performance. It, therefore, forms the basis of the current aircraft maintenance program applied by operators of the new plane models; This process is represented in Figure 1. The program selects tasks that are published in the maintenance review board (MRB), an FAA-approved document by the airframe builder (Mrusek et al., 2018, p. 5). Every manufacturer, for example, Airbus and Boeing, publishes its maintenance planning document. It classifies maintenance as a checklist with time, sequences, and days. It must be modified to fit in with the original task provision when planning a maintenance activity by the operator.

 

 

Figure 1.

MSG-3 Logic Diagram (Ren et al., 2017).

 

Aircraft Maintenance Analysis

Aircraft maintenance is an intricate socio-technical scheme that requires constant organization and collaboration between various individuals and groups such as crew managers, aircraft maintenance engineers (AMEs), manufacturers, or airline to safeguard consistent operations. Additionally, aircraft maintenance routine requires proper record keeping. The FAA has provisions for ideal record-keeping, and the mechanics should, therefore, provide information about the services done regularly (Staff, 2019). It thus follows that aircraft maintenance is an essential process in the aircraft industry and, as such, should be given the required consideration. A proper system of conducting the maintenance on aircraft should also be adopted to ensure consistency despite the position of the plane, time, and its structural condition. This paper examines the possibility of adoption of the predictive system of maintenance to incorporate preventive and progressive maintenance.

 

Types of Aircraft Maintenance

The FAA requires every aircraft operator to conduct regular inspections and routine checks on the plane. They should, therefore, maintain a checklist containing the different components of an aircraft, for example, the transponder, engine, landing gear, and the propeller assembly, such as control systems. In addition to the inspection, the components need to be adequately serviced; this can be done through preventive and progressive maintenance (Staff, 2019). The document is covering the maintenance requirements that should be conducted on a plane to ensure its airworthiness is called the Maintenance Program (Cranfield, 2019).

Preventive Maintenance

This system includes operations that do not involve substantial repairs or complex disjointing of the components done frequently. It is usually conducted by the pilot or a mechanic to keep the plane functioning. For example, adding fluids or replacing hardware. The FAA gives a provision that a pilot should be able to perform preventive maintenance types and any minor repairs. A mechanic, on the other hand, should be able to complete both the minor and major repairs. These classifications are made depending on the complexity of the repair and the significance of critical systems (Staff, 2019). This maintenance is less costly and saves on time.

Progressive Maintenance

This maintenance practice lets the plane to be inspected by the manufacturer and FAA frequently. It is applied mostly by companies with large fleets since it ensures there are no interruptions of operation. The aircrafts are serviced deliberately, therefore, more convenient for the company. Generally, this type of maintenance is more common in passenger planes that are in continuous use. Managers to fleets are required to adopt this plan to get approval from the FAA. Moreover, the program is also applicable to new planes that need to be used for an extended period. This program, however, has additional costs as the process is regularly repeated (Cranfield, 2019).

Discussion

Predictive Maintenance

The traditional methods of equipment maintenance comprise of procedures defined during the designing of the aircraft. These methods include preventive maintenance which is planned in prior and performed occasionally. Predictive maintenance, on the other hand, conducts continuous observation of the aircraft. The manufacture, which usually offers this service, alerts the operator in advance whenever there is any form of risk, such as mechanical failure. It, therefore, gives adequate time between the alert and failure for the planning and conducting of maintenance (Korvesis, 2017, p. 2). Furthermore, the status of the plane is usually reflected in the information of its operation; this may make it challenging to analyze the data, thereby leading to the need for the application of Big Data types to compress the information and attain the best outcome.

Predictive maintenance enables the mechanical engineer to know the accurate information at the appropriate moment to plan and perform the required maintenance. On top of the precise data, it requires the engineer to have a combination of field knowledge and skills in data science to be able to analyze and comprehend the information from the aircraft (Moro, 2019). The skills are also:

  1. Vital to the prediction of the chances of failure and the possible time of occurrence.
  2. Crucial in stopping the failure from occurring by arranging for maintenance promptly and carrying out inspections where necessary.

Additionally, sharing of data is a necessary procedure of refining the forecasts and improve precision. Predictive maintenance involves the application of Big Data technologies, as had been mentioned. These data types include reference data, which shows the regular performance of the aircraft’s system and the operating data, which gives the ideal condition of the plane and is conveyed either in real flight time or when the aircraft is grounded. Similarly, it applies software that uses the Flight Data Recorder (FDR) technique and sensors to show the possibility of system failure. With this data, the engineer can identify the possible failures that might need maintenance and act accordingly.

Moreover, real-time data from the aircraft is saved in FDR and downloaded onto a computer software that detects irregularities and sends the information to prompt inspection by the mechanical engineer (Moro, 2019). This process is known as the Maintenance, Repair, and Operation (MRO) technique; it assists in reducing the average time and expenses.

It is important to note that the victory of predictive maintenance is dependable on the achievement of three goals. Firstly, finding the right aircraft information. This objective is crucial since the whole maintenance process is data-driven; it is, therefore, necessary to obtain the correct data from the onset to ensure the proper diagnosis. Secondly, the problem should be addressed adequately to ensure the achievement of the expected outcome. And lastly, there should be an appropriate evaluation of the result from the data analysis (Moro, 2019).

Airbus Predictive Maintenance Case Study

Airbus aircraft manufacturer and EasyJet airline company adapted a five-year contract in which Airbus agreed to provide predictive maintenance to its A320 category plane fleet. The technology uses the Skywise data system, which enables the airline’s engineers to intercede in time to replace parts of the aircraft before system failure, thereby preventing the possibilities of any downtime. It was the first trial of preventive maintenance by Airbus. The process is enhanced by the installation of flight operations maintenance exchanger (FOMAX) on easyJet’s fleet. This technology was launched in 2017 at the Paris Air Show, in conjunction with Palantir Technologies, who are the inventors of incorporation of Big data into advanced analytics. This system has since helped in ensuring the timely and safe travel of customers and the eradication of downtime in the airline (Dubon & Frendt, 2018).

Conclusion

Every airline has different aircraft, which in turn display exceptional characteristics that can lead to failure. These failures can lead to delays in flights or cancellations in some cases. Predictive maintenance, as opposed to the preventive and progressive maintenance, averts any instances of downtime in airlines. It adapts a data-oriented system that involves the application of Big-data technology, which includes reference and operating data in analyzing the flight information data. This approach is more effective since it incorporates the Maintenance, Repair, and Operation technique, which saves on time and overall costs. Also, the application of software programs using sensors and FDR to show possible faults in advance enhances the safety of the entire crew and passengers and saves on time. From this discussion, predictive maintenance is the best approach to aircraft maintenance currently and in the future. Though, its accomplishment will depend on the acceptance of the big-data technology in aircraft data analytics.

 

 

 

 

 

 

References

Cranfield, U. (2019). Airworthiness: Maintenance Programme. Flight Safety Foundation. Retrieved from: https://www.skybrary.aero/index.php/Maintenance_Programme

Dubon, J., and Frendt, M. (2018). easyJet signs Skywise Predictive Maintenance agreement with Airbus for its entire fleet. Airbus. Retrieved from: https://www.airbus.com/newsroom/press-releases/en/2018/03/easyjet-signs-skywise-predictive-maintenance-agreement-with-airb.html

Korvesis, P. (2017). Machine Learning for Predictive Maintenance in Aviation. Artificial Intelligence [cs.AI]. Université Paris-Saclay. English. ffNNT: 2017SACLX093

Lundgren, C., Skoogh, A., & Bokrantz, J. (2018). Quantifying the effects of maintenance–a literature review of maintenance models. Procedia CIRP72, 1305-1310.

Moro, L. (2019). Predictive Maintenance: How necessary are aircraft checks? Data Science. Retrieved from: https://datascience.aero/predictive-maintenance-aircraft-checks/

Mrusek, B. M., Kiernan, K. W., & Clark, P. J. (2018). UAS Maintenance: A Critical Component in Maintaining Airworthiness. International Journal of Aviation, Aeronautics, and Aerospace5(5), 2.

Ren, H., Chen, X., and Chen, Y. (2017). Reliability-Based Aircraft Maintenance Optimization and Applications: Basic Concepts. Science Direct. 1-36.

Staff, J. T. (2019). Aircraft Maintenance and Inspection: Types of Aircraft Maintenance. JETechnology Solutions, Inc. Retrieved from: https://www.aircraftmaintenancestands.com/blog/article/aircraft-maintenance-and-inspections/

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