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飛航安全與人為因素 行政院飛航安全委員會 報告人 王興中. Flight Safety 飛航安全. U.S. General Aviation. Scheduled Air Carrier. 50. 40. 30. Accidents/100,000 flight hours. 20. 10. 0. 1960. 1970. 1980. 1990. Source: Boeing. Source: NTSB. U.S. Navy/Marine Corps. U.S. Air Force. Accidents/100,000 flight hours. - PowerPoint PPT Presentation

Text of 飛舮‰…¨èˆ‡ç‚› ç´ ...

Accidents/100,000 flight hours
U.S. Navy/Marine Corps
Source: U.S. Naval Safety Center
Improvements in aviation safety, however, are not unique to commercial carriers. General aviation deaths and fatal accident rates in the U.S. declined to a 15-year low in 1996, with only 1.51 accidents occurring per 100,000 flight hours (NTSB, 1997). Aviation accidents within the U.S. military (i.e., Army1, Navy, Air Force, and Marine Corps) have also decreased steadily over the past 2 decades. The rate of major accidents in the U.S. military, calculated as the number of accidents per 100,000 flying hours, declined from about 4.3 in 1975 to 1.5 in 1995.
In fact, if one were to examine any Service organization or even the civilian sector they would all look essentially the same (USN/USMC - upper right; USAF - upper left; commercial airlines - bottom). Specifically, they all reveal the same downward trend throughout the 50s, 60s and into the early 70s. Many have attributed this stark decline in the overall mishap rate to improved design, materials, training, and the implementation of standardized training programs. Notably, however, all the graphs show the same “flattening” of that positive downward trend in the mishap rate over the last couple decades.
1 The U.S. Army rates between 1950 and 1972 were unavailable at the time of publication.


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The red (bottom) line in this graph shows worldwide trends in aviation accident rates, as well as projected accident rates through the year 2010. The green (middle) line depicts the traffic growth which is expected to increase dramatically over the next 10 years. The blue (top) line shows the predicted increase in accident frequency due to the rapid industry expansion. Note that this predicted increase is based on the current accident rate; therefore, even if the accident rate stays the same over the next decade, the raw number of accidents will increase markedly. Furthermore, as can be seen from the graph, there may be as many as 52 accidents a year worldwide during the first decade of the new century. This translates into an astonishing one accident a week.
Note. Graph adapted from Flight Safety Foundation (1997). Values plotted in the graph are estimates based on industry statistics.


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2 Based on industry estimates
3 Based on current accident rate
Number of Commercial Jet Accidents, Accident Rate
and Traffic Growth - Past, Present and Future
The red (bottom) line in this graph shows worldwide trends in aviation accident rates, as well as projected accident rates through the year 2010. The green (middle) line depicts the traffic growth which is expected to increase dramatically over the next 10 years. The blue (top) line shows the predicted increase in accident frequency due to the rapid industry expansion. Note that this predicted increase is based on the current accident rate; therefore, even if the accident rate stays the same over the next decade, the raw number of accidents will increase markedly. Furthermore, as can be seen from the graph, there may be as many as 52 accidents a year worldwide during the first decade of the new century. This translates into an astonishing one accident a week.
Note. Graph adapted from Flight Safety Foundation (1997). Values plotted in the graph are estimates based on industry statistics.

2002
02/12 Iran Air Tours Tupolev TU-145M Khorramabad, Iran (12/107)-(0/0)-(12/107)
02/15 Tiramavia Antonov 12BP Monrovia-Roberts (1/0)-(0/0)-(8/0)
03/15 Aerotaxi (Cuba) Antonov AN-2 Baez, Cuba (2/14)-(0/0)-(2/14)
03/17 Djibouti Airlines Let 410 Djibouti, Africa (4/0)-(0/0)-(4/0)
04/12 Tadair Swearingen 226 Palma de Mallorca, Spain (2/0)-(0/0)-(2/0)
04/15 Air China Boeing 767-2J6ER Pusan, South Korea (11/117)-(0/0)-(11/166)
04/19 SELVA Colombia Antonov AN-32A Popayan, Colombia (0/3)-(0/0)-(3/5)
05/04 EAS Airlines BAC One-Eleven Kanos, Nigeria (7/64)-(0/0)-(8/69)
05/07 EgyptAir Boeing 737-566 Tunis, Tunisia (3/11)-(0/0)-(6/56)
05/07 China Northern McDonnell Doulgas Yellow Sea – Dalian, China (9/103)-(0/0)-(9/103)
05/21 Sky Executive Airlines Let 410UVP Calabar, Nigeria (5/0)-(0/0)-(5/0)
05/25 Trigana Air Service De Havilland Nabire, Indonesia (6/0)-(0/0)-(6/0)
The red (bottom) line in this graph shows worldwide trends in aviation accident rates, as well as projected accident rates through the year 2010. The green (middle) line depicts the traffic growth which is expected to increase dramatically over the next 10 years. The blue (top) line shows the predicted increase in accident frequency due to the rapid industry expansion. Note that this predicted increase is based on the current accident rate; therefore, even if the accident rate stays the same over the next decade, the raw number of accidents will increase markedly. Furthermore, as can be seen from the graph, there may be as many as 52 accidents a year worldwide during the first decade of the new century. This translates into an astonishing one accident a week.
Note. Graph adapted from Flight Safety Foundation (1997). Values plotted in the graph are estimates based on industry statistics.

2002
06/17 Hawkins and Powers Lockheed Walker, California – U.S.A. (3/0)-(0/0)-(3/0)
07/01 DHL Express Boeing 757 Freighter Ueberlingen, Germany (2/0)-(0/0)-(2/0)
07/04 New Gomair Boeing 707 Bangui, Central African (16/7)-(1/1)-(17/8)
07/16 Britten-Norman BN-2B Borneo Jungles, (2/7)-(0/1)-(2/8)
07/17 Skyline Airways DeHavilland Surkhet, Nepal (2/2)-(0/0)-(2/2)
07/26 FedEx Boeing 727 Tallahassee, Florida, (0/0)-(3/0)-(3/0)
07/27 Ukraine Air Force Sukhoi SU-27 Lviv, Ukraine (0/0)-(2/0)-(2/0)
07/28 Pulkovo Airlines IL-86 Moscow, Russia (14/0)-(2/0)-(16/0)
08/22 Shangri La Air DHC-6-300 Pokhara, Nepal (3/15)-(0/0)-(3/15)
08/29 Vostok Aviakompania Antonov AN-28 Ayan, Russia (2/14)-(0/0)-(2/14)
08/30 Rico Linhas Aereas Embraer 120ER Rico Branco, Brazil (3/20)-(0/0)-(3/28)
09/14 TOTAL Linhas Aereas ATR-42-312 Paranapanema, Brazil (2/0)-(0/0)-(2/0)
10/01 India Military - Navy Ilyushin IL-38/ Vasco, India (12/0)-(0/0)-(12/0)
10/23 Tretyakovo Air Ilyushin IL-62M Bishkek, Kyrgyzstan (0/0)-(0/0)-(11/0)
10/25 Private Charter Beech King Air A100 Eveleth, Minnesota (2/6)-(0/0)-(2/6)
11/06 Lux Air Fokker 50 Luxembourgh (2/18)-(2/0)-(3/19)
The red (bottom) line in this graph shows worldwide trends in aviation accident rates, as well as projected accident rates through the year 2010. The green (middle) line depicts the traffic growth which is expected to increase dramatically over the next 10 years. The blue (top) line shows the predicted increase in accident frequency due to the rapid industry expansion. Note that this predicted increase is based on the current accident rate; therefore, even if the accident rate stays the same over the next decade, the raw number of accidents will increase markedly. Furthermore, as can be seen from the graph, there may be as many as 52 accidents a year worldwide during the first decade of the new century. This translates into an astonishing one accident a week.
Note. Graph adapted from Flight Safety Foundation (1997). Values plotted in the graph are estimates based on industry statistics.

2002
11/08 Nepal Airways Harbin Yunshuji Y-12 Jomsom, Nepal (0/0)-(?)-(3/16)
11/09 Tymen Antonov AN-26 Antalya, Turkey (0/0)-(8)-(9/19)
11/11 Laoag International Fokker F27 Manila, Philippines (1/18)-(?)-(5/29)
11/28 Eagle Aviation Let 410 Masai Mara, Kenya (1/7)-(0/0)-(2/17)
12/03 C F F Air Learjet 36A Astoria, OR (0/0)-(0/0)-(2/2)
12/09 Raytheon Aircraft Beechcraft 1900C Eagleton, AR (2/1)-(0/0)-(2/1)
12/21 Transasia Airways ATR-72-202 Penghu Islands (2/0)-(0/0)-(2/0)
12/23 Aeromist Kharkiv Antonov 140 Baghrabad, Iran (6/38)-(0/0)-(6/38)
12/24 North Flying SA.227AC Metro III Aberdeen-Dyce Airport, UK (0/0)-(2/0)-(2/0)
The red (bottom) line in this graph shows worldwide trends in aviation accident rates, as well as projected accident rates through the year 2010. The green (middle) line depicts the traffic growth which is expected to increase dramatically over the next 10 years. The blue (top) line shows the predicted increase in accident frequency due to the rapid industry expansion. Note that this predicted increase is based on the current accident rate; therefore, even if the accident rate stays the same over the next decade, the raw number of accidents will increase markedly. Furthermore, as can be seen from the graph, there may be as many as 52 accidents a year worldwide during the first decade of the new century. This translates into an astonishing one accident a week.
Note. Graph adapted from Flight Safety Foundation (1997). Values plotted in the graph are estimates based on industry statistics.

Hull Loss Accidents – Worldwide Commercial Jet Fleet – 1992 Through 2001

Pilot Error
A comprehensive Human Factors Analysis and Classification System (HFACS) has recently been developed to meet these needs. This system, which is based upon Reason’s (1990) model of latent and active failures (Shappell & Wiegmann, 1997a), encompasses all aspects of human error, including the conditions of operators and organizational failure.

Human Factors discovers and applies information about human behavior, abilities, limitations, and other characteristics to the design of tools, machines, systems, tasks, jobs, and environments for productive, safe comfortable, and effective human use





































Echoic --











Pattern matched to elements in the mental model to achieve situation awareness
Pattern-recognition sequence can become automaticity



Helmets
Pressurization
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System failures are like dominos, with the failure of one “domino” effecting the toppling of the next. The end result is the accident or injury. When this happens, however, we often forget that the accident itself is the last “domino” in this sequence, and that many dominos fell well before the accident occurred. As a result, we tend to focus almost exclusively on the people responsible for front line operations (i.e., the aircrew). Unfortunately, this has lead accident pilots (if they survive the accident) to feel severely scrutinized, as if they are being placed under a microscope or interrogated for a crime.

8910311117
Unsafe Acts
Operating Environment
Rather than scrutinizing the failure of a single system component, we must take a step back and look at the entire sequence of events that lead to the accident. A systems perspective requires that we examine blemishes or faults throughout the entire system. After all, it is often the failure of multiple components that combined together to produce an accident.
Some people may raise the question, “Why stop at the organizational or even industry level?” Does the system’s boundary really end there? Presumably everything has a prior cause. Therefore, we could potentially trace the cause of an accident all the way back to the Big Bang. Stopping at the organizational level is just arbitrary.
Theoretically this may be true. But we need to be practical. In seeking the reasons for an accident, we should search far enough back to identify factors that, if corrected, would render the system more tolerant to, or even prevent, subsequent encounters with conditions that produced the original accident. The people most concerned and best equipped to do this are those within the organization (Reason, 1990).



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360
Total Command Hours on B747-400 2,017 hrs
CM-2 Male, age 36
Total Flying Hours 2,442 hrs
Total Command Hours on B747-400 552 hrs 
CM-3 Male, age 38
Total Flying Hours 5,508 hrs
Total Hours on B747-400 4,518 hrs
 
Aligned with centerline
Active Conditions
Organizational
Factors
Inputs
Unfamiliar With 05R
As mentioned earlier, we have incorporated Reason’s (1990) model of how humans contribute to the breakdown of safe flight operations into our HFACS model. In this model, system failures are classified as either active or latent conditions. However, the exact nature of these failures or “holes” in the cheese have yet to identified and described. In this section, we provide a framework or taxonomy for identifying, classifying, and organizing active and latent failures with in the system. As previously stated, the framework is based upon the “The Taxonomy of Unsafe Operations” (Shappell & Wiegmann, 1997) which was developed for, and has recently been adopted by, the U.S. Navy/Marine Corps and U.S. Coast Guard for use in aviation accident investigation and analysis. The taxonomy describes four levels of failure within the system which include: (a) organizational factors, (b) unsafe supervisory practices, (c) unsafe conditions of operators, and (d) the unsafe acts operators commit. Each level is described in detail, beginning with the level most closely tied to the accident itself, unsafe acts.