TOWARDS THE ZERO ACCIDENT GOAL: ASSISTING THE FIRST OFFICER MONITOR AND CHALLENGE CAPTAIN ERRORS



sample. These were errors in which the non-flying crew-member (the first officer in 81-
87% of the cases) did not properly monitor and challenge the flying crew-member when
errors were committed. Usually the errors that should have been monitored or
challenged were listed as causal or contributing to the accident.

Using this data we can calculate how many accidents are related to inadequate
monitoring and challenging. According to the NTSB in 19 of the 37 accidents a
monitoring/challenging error followed a causal error. Since the initial pool consisted of
75 accidents, approximately 25% of all accidents could have been prevented by better
monitoring and challenging. Keeping in mind that in 81-87% of all the accidents the
captain was the flying pilot, about 20% of all accidents could have been prevented if the
first officer had better monitored and challenged the captain.

4. OPTIMIZATION MONITORING AND CHALLENGING

The NTSB’s discussion of human errors included the need for practicing
monitoring/challenging behavior in LOFT scenarios and emphasizing monitoring and
challenging (M&C) errors in the LOFT debriefings. In particular, the NTSB felt that an
important avenue would be the “intentional introduction of a procedural or decisional
error by the flying pilot in the LOFT scenario. This technique would make certain that
the non-flying pilot is confronted with the opportunity to detect and challenge the error
made by the flying pilot.” This leads us, next, to propose M&C optimization as a
technique.

It is evident for the sake of error correction, that the degree of M&C is a
parameter that should be modified to some best value between 0 and 100%. The

13



More intriguing information

1. The name is absent
2. The name is absent
3. The Triangular Relationship between the Commission, NRAs and National Courts Revisited
4. The name is absent
5. Computational Batik Motif Generation Innovation of Traditi onal Heritage by Fracta l Computation
6. Demand Potential for Goat Meat in Southern States: Empirical Evidence from a Multi-State Goat Meat Consumer Survey
7. Temporary Work in Turbulent Times: The Swedish Experience
8. The name is absent
9. Confusion and Reinforcement Learning in Experimental Public Goods Games
10. The Response of Ethiopian Grain Markets to Liberalization