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Optimization Software Needed To Improve Maintenance

Electronic technical logs are becoming increasingly common but concerns persist over big data exploitation.

Once an airline has a modern maintenance-management system, fed by quality data, the next level of maintenance software to consider is optimization and simulation software, argues Fredrik Ekstrand, CEO of Cervino, a maintenance consultancy. For most maintenance-management applications are book-keeping systems focused on technical records and continuous airworthiness. Ekstrand says they do not help allocate mechanics and shifts, advise on part stocks, or choose between in-house versus outsource maintenance.

“Different more analytical software is needed . . . It’s essential that airlines start to look forward, not backwards,” the Cervino consultant says. For analytical software can improve maintenance, predict needed part stocks, advise on staggering repair tasks effectively and reduce AOG costs.

Major airlines generally have some sort of optimization tools. But these applications are less common at younger, smaller airlines. 

One recent trend is toward electronic technical logs, which are becoming more widespread and can improve communication between cockpits and hangars. Ekstrand attributes this trend to lower cost for tablets and other handheld devices, and increasing maturity of IT capabilities at most airlines. Handheld costs and immature IT had been the chief hurdles to ETLs.

Unfortunately, another hopeful trend is less advanced, exploitation of Big Data for maintenance. “Our experience is that most airlines have very low readiness when it comes to capitalizing on data coming off the electronic operations of the modern aircraft,” Ekstrand notes. First, carriers must collect data and transfer it to ground systems. “This itself is a complex task.” And the next steps, extracting value from the data and then feeding it back into the maintenance loop, “is a task that most airlines are not ready for.”

Ekstrand says the challenges in using Big Data include the complexity of collecting data from each flight and then matching this data to the actual configurations of specific aircraft at specific times. This may be easy in principle, “but it is hard to actually make happen . . . Lots of different IT systems and organizations are involved, and the timing of collecting the events is different from time to time. Airlines need to overcome these hurdles to be ready to actually exploit the value of the big data they produce.”

TAGS: Big Data
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