Precursors: An Analysis System in Reliability Parallel with FAA Certification

The fatal crash rate for the worldwide jet scheduled carrier fleet has improved by a factor of 12 over the past 50 years. This improvement is primarily due to the FAA, NTSB, and Boeing, as most planes are Boeing. This has been achieved through the design, manufacturing, and certification process, along with thorough investigation and correction of any problems that arise. However, it is essential to note that since 1958, at least 28% of new fleet designs were certified, although later discovered to be unsafe, often after crashes, and the trend is not improving. The recent incidents involving the Boeing 737 MAX, including two crashes and a door plug blowout, highlight this longstanding but unacknowledged issue with new fleet certification. These events on the 737 MAX, avoidable with the specific data analysis methodology presented, emphasize the urgent need for this additional, independent layer of safety to supplement current certification technology and methods. This paper underscores the necessity of augmenting current conventional methods for the safety and reliability assurance of new fleet designs with this new, unrecognized data analysis methodology. Any event, instance, or happening in the arrow of time that is countable has a time interval since the last happening of the same type. The analysis technology, event interval probability (EIP), reveals a series of probability mass functions (PMF) for the event time intervals immediately upon every event. These probability distributions reside in the history of any happening and extend to future happenings. Because any change in anything can be a happening, an event, the method applies to precursors, even low-level signals of no importance, when the signal is taken in isolation. These probabilities are determined using the 737 MAX crash and crash precursor and the door plug blowout precursor. With probability analysis of the precursors, all three primary events were avoidable. The FAA conducted a 737 MAX risk assessment after the first crash, finding an uncorrected fleet life risk of 2,920.9 fatalities. The true risk was 95 times greater. This difference is 275,258 fatalities. The FAA should investigate the EIP technology and either use the method or explain why not. The reliability of any system is described as an emergent property found with EIP. The system is the set of causes producing an event. The system does not need to be known, understood, or even describable, as causal information is not used in EIP. This is difficult for anyone to understand, especially experts in the system producing the events, as the human reaction is to revert to reductionism - breaking the complex into smaller, more understandable pieces. Social and human system examples are used to understand how system reliability can be known in maximum detail as a probability distribution with no system knowledge. A single event is often all that is needed to recognize a reliability shift to a new level. Again, this is difficult for professionals to accept because they immediately think of statistics, but EIP is fundamentally a probabilistic process, not a statistical process. Child Protective Services (CPS) investigation dates are used as precursors to a child's death, and police use of force citizen complaint dates are precursors to the death of George Floyd in Minneapolis, Minnesota, in 2020. Dates for these social system precursors, as with 737 MAX precursors, identify actionable “reliability” that, if acted upon, could have easily avoided all primary events. The term “reliability” is used in this unorthodox manner and applications as no better term to describe this universal emergent system property is known.