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APATS Bangkok 17.09.2013 1
Evidence for change in flight crew training
developed by Thomas LeoffIAAPS chairman
APATS Bangkok 17.09.2013 2
Follow Me….
APATS Bangkok 17.09.2013 3
Evolution in Aviation
Where do we come from?
• Today s training system is based on the seventies
• ICAO s SARPs on training stem from that time with the exception of the MPL
• The operation philosophies of aircraft like the B707 which where a core part of that huge progress in aviation at that time are still a cornerstone in today s training
APATS Bangkok 17.09.2013 4
APATS Bangkok 17.09.2013 5
The seventies….
APATS Bangkok 17.09.2013 6
… are the scenario for today's legal requirements for training programs
They are:• Based on traditional developments• Engineering driven• Knowledge based• Based on numbers like requirements of
flight hours of instruction or landings, legs etc.
APATS Bangkok 17.09.2013 7
The major deficiencies are:
• Syllabus structures from the 70ies and 80ies
• No feedback from the real world OPS• Human Factors training outdated and not
related to actual needs • No feedback system to control the
efficiency of the training in place
APATS Bangkok 17.09.2013 8
International activities by IATA, ICAO and EASA
There are 3 international activities which are relevant for the corrective action:• IATA´s ITQI initiative• ICAO´s developments regarding EBT• EASA´s planned Rulemaking Activity for
Evidence Based Training
IATA´s Data Report on EBT (soon to be published)
APATS Bangkok 17.09.2013 9
APATS Bangkok 17.09.2013 10
The 4 Ws of change in training:• What – training, testing & legal requirements
therefore• Why? – number of new pilots in the next 20
years, introduction of SMS for ATOs, pilot qualification as key factor for safety improvements and the frequent technical improvements in the system
• Who? – ICAO, EASA, NAAs &Stakeholders• When? – ASAP!
APATS Bangkok 17.09.2013 11
The „What?“
• The legal requirements• The scenarios for the training• The Training Programs and their
supervised effectiveness• The form of examination• The qualification of instructors and
examiners
APATS Bangkok 17.09.2013 12
The „Why?“• Pilot Demand forecasted for the next 20
years• The new concept of Competency- &
Evidence Based Training• Introduction of SMS in ATOs and other
sources of operational data and the new opportunities from that
• Current “flat” trend lines of accident rates
APATS Bangkok 17.09.2013 13
Pilot Demand Forecast
APATS Bangkok 17.09.2013 14
The actual accident trend lines
Two practical samples for human deficiencies
They stem from a Research Project in which several German Universities from Bremen, Berlin and Munich cooperate with Lufthansa.The goal is, to develop valid Safety Performance Indicators for the SMS
APATS Bangkok 17.09.2013 15
FINISHED FILES ARE THE RESULT OF YEARS OF
SCIENTIFIC STUDY COMBINED WITH THE
EXPERIENCE OF YEARS
FINISHED FILES ARE THE RESULT OF YEARS OF
SCIENTIFIC STUDY COMBINED WITH THE
EXPERIENCE OF YEARS
Kategorie Fehler MTBF
Task Related Probability Of Errors MTBFs
Prof. Bubb TU-Munich
Simple and regularely performed tasks at a low stress level.
1 . 10-3
Complex tasks in unusual situations at a high stress level and / or time pressure.
Complex , regularely performed tasks in a well known working environment at a low stress level.
1 · 10-1
1 · 10-2
~30 min
~5 min
~30 sec
Category Error probability MTBF
APATS Bangkok 17.09.2013 20
Today we fly…
APATS Bangkok 17.09.2013 21
… and that´s today´s A380!
APATS Bangkok 17.09.2013 22
… and here the new B787
APATS Bangkok 17.09.2013 23
What shall we update?
• A simple update of the actual set of Training Programs is not enough!
• We must initiate a more sophisticated approach!
• How could we achieve that?• We should start with the newly defined
Pilot Core Competencies and Behavioral Indicators….
APATS Bangkok 17.09.2013 24
The new set of Pilot Competenciesas defined by IATA/ICAO/IFALPA February 2012
APATS Bangkok 17.09.2013 25
How can we adapt the training to that new approach?
• Integration of the SMS of operators and the ATOs
• Defined feedback loops based on data from the SMS, incident reports & analysis
• This feedback loop must cover the entire system from initial to recurrent training
• Research to support the SMS utilization
An Example from our Research Project
Simulator study measuring manual flying skills regarding Performance Shaping Factors
APATS Bangkok 17.09.2013 26
Technische Universität MünchenLehrstuhl für Ergonomie
Simulatorstudie zu manuallen Flugfertigkeiten
Simulator study measuring manual flying skills regarding Performance Shaping Factors
Dipl.-Ing. Andreas Haslbeck
Dipl.-Ing. Ekkehart Schubert, Cpt. Manfred Müller
Technische Universität MünchenLehrstuhl für Ergonomie
Simulatorstudie zu manuallen Flugfertigkeiten
Technische Universität MünchenLehrstuhl für Ergonomie
Simulatorstudie zu manuallen Flugfertigkeiten
Captains A346 FOs A320
Age MW 50,0 SD 4,1 MW 30,4 SD 3,1
2. Demographic Data
2.5622.093
14.851
3.374
0
2.000
4.000
6.000
8.000
10.000
12.000
14.000
16.000
18.000
20.000
A346 A320
Flugerfahrung in Flugstunden
Flugstunden Typ Flugstunden gesamt
3
17
0
5
10
15
20
A346 A320
Landungen als PF in 30 Tagen
Simulator Study: manual flying skills
Flight hours Landings as PF within last 30 days
on type Total hours
„Quality nine
three kilo“
„Continental
one ooh six“„Whitestar
one eight“
„Lufthansa
one seven eight niner“
„Singapore
three two eight“
„Eurotrans
zero seven“
„Lufthansa
seven three one“
„Lufthansa
seven two seven“
Traffic Scenarios
Technische Universität MünchenLehrstuhl für Ergonomie
Simulatorstudie zu manuallen Flugfertigkeiten
Scenario 1 (summary)
EDDMILS APP 08L with >15Kts tailwind (WX: VIS >3.000m OVC 800ft)
G/A Standard Missed APP
Raw Data ILS APP 26R (WX >non-precision: VIS 2.000m OVC 350ft)
Simulator study manual flying skills
Technische Universität MünchenLehrstuhl für Ergonomie
Simulatorstudie zu manuallen FlugfertigkeitenSimulatorstudie zu manuallen Flugfertigkeiten
Measuring basic (manual) flying performance
The Simulator crew measures deviations:•from Localizer•altitude and sinkrate (Glideslope)•approach speed•touchdown point
A Computer program integrates all measured deviations.
In addition pilot performance assessment by an experienced training pilot.
Technische Universität Berlin
VP Level Loc GS speed visual landing average grade
1 6 1 1 2 1 1 2 2
2 5 3 2 2 2 4 3 3 weiblich
3 2 1 1 1 2 1 1,33333 1
4 1 1 1 1 1 1 1 1
5 2 1 1 2 2 1 1,5 2
6 2 1 1 1 2 1 1,33333 1
7 3 1 1 1 2 2 1,66667 2
8 1 1 1 1 1 1 1 1
9 1 1 1 2 2 1 1,33333 1
10 5 1 2 2 1 1 2 2
11 1 1 1 1 2 2 1,33333 1
12 1 1 1 1 1 2 1,16667 1
13 2 1 1 1 3 3 1,83333 2
14 3 2 2 2 2 2 2,16667 2
15 3 1 1 2 2 1 1,66667 2
16 1 1 3 2 4 2 2,16667 2
17 1 2 2 2 3 3 2,16667 2 weiblich
18 2 1 1 1 2 2 1,5 2
19 4 1 1 2 2 1 1,83333 2
20 2 1 1 2 2 1 1,5 2
21 1 1 1 1 2 1 1,16667 1
22 2 1 1 2 2 1 1,5 2
23 3 1 2 2 2 2 2 2
24 3 1 1 2 1 1 1,5 2
25 2 1 1 1 2 2 1,5 2
26 1 1 1 1 1 1 1 1
27 3 1 1 1 2 1 1,5 2
28 6 6 6 4 6 3 5,16667 5 weiblich
29 3 1 1 1 1 1 1,33333 1
30 2 1 1 2 2 1 1,5 2
A320-Pilots Grading
Technische Universität Berlin
-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2
x 105
-5
0
5
10
15
20x 10
4
X [ft]
Y [
ft]
Topansicht
EDDM 26R
MIQ
DM431
DM429
GUDEGMAGAT
WLD
BURAM
XERUM
A320A340-600
34
Datarecording(A340 & A320 FFS)
eye tracking camera
FMA-Checks
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
4 8 9
10
12
13
14
15
16
17
18
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
49
50
51
52
53
54
55
56
58
60
Ø C
PT
Ø F
O
An
teil
ge
täti
gte
rF
MA
-Ch
eck
s
CPT FO
Performance variability (all kinds of FMA-Checks)
Speed-ChecksSpeed/vert.Speed-Checks unter 100ft
19,0%
9,5%
64,0%60,0%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Speed überprüft zwischen 100ft und TD vert. Speed überprüft zwischen 100ft und TD
An
teil
de
r P
ilo
ten
CPT FO
F/O A320
CPT A346
F/O A320
CPT A346
Speed / Vertical Speed Checks below 100ft RA
Speed checked below 100ft and TD V/S checked below 100ft and TD
19.05.2014Seite 38
Bitte diesen Text mit dem Präsentationstitel überschreibenDeutsche Lufthansa AG
SaMSys Simulator Experiments
Measuring…
Economical Flight Performance
FMS Mode Awareness / Automation
Handling unclear situations (Warsawa)
Redundancy and team-interaction
Go-Around-decision and -performance
Basic Flying Skills (AI and Boeing)
Predictability of pilot performance (DLR-test)
Simulator Study: Manual Pilot Skills
Test Scenario 2
• The tower reported wind is within limits. However the actual surface wind is beyond the limit (18Kts instead of max. 10Kts)
• A Go-Around should be performed!
• In 70ft a Go-Around is triggered by the PM
• Runway change after the Go-Around.
Technische Universität Berlin
39% of all pilots discussed the tailwind situation during the approach briefing.
89% of all pilots talked about the strong tailwind during approach above 1000ft AGL.
50% of all pilots checked the wind indication during final approach below 1000ft AGL.
64% of all pilots would have landed without the wind information given by the PM (TW of 18 Kts).
14% of all pilots decided to land, knowing the tail wind was 18Kts.
44% of all A340 pilots performed the Go-Around only after the PM gave the command in ~70ft AGL.
Go-Around Anslysis(MSc of Alexander Schmidt)
40
19.05.2014Seite 41
Bitte diesen Text mit dem Präsentationstitel überschreibenDeutsche Lufthansa AG
SaMSys Simulator Experiments
Measuring…
Economical Flight Performance
FMS Mode Awareness / Automation
Handling unclear situations (Warsawa)
Redundancy and team-interaction
Handling the Go-Around
Basic Flying Skills (AI and Boeing)
Predictability of pilot performance (DLR-test)
Technische Universität Berlin
Go-Around Analysis(MSc of Alexander Schmidt)
a) 1 A340-600 captain (3,7%) performs the Go-Around correctly.10 A320-F/O (33%) perform the Go-Around correctly.
b) In general more than one SOP-violation per Go-Around Average: A340-600 Cpt.: 2 , A320 F/O: 1,3.
c) Common SOP violations:• „Missed Appr. Proc.“ not correct („NAV-Mode“ not activated).• Flaps not operated according SOP.• Thrust Reduction to late and/or MCT is selected instead of CLB thrust.• Vertical speed is not reduced during the last 1000ft before reaching
Go-Aroud Altitude.
42
Masterarbeit Alexander Schmidt
Technische Universität Berlin
Vertical Speed within the last 1.000ft before reach ing the
level off altitude
0,0%
12,9%
35,5%
51,6%
3,2%
67,7%
16,1% 12,9%
0,0
10,0
20,0
30,0
40,0
50,0
60,0
70,0
80,0
< 1000 1000-1500 1500-2000 >2000
rela
tive H
äufig
keit
[%]
Steiggeschwindigkeit [ft/min]
A340
A320
Go-Around Analysis
v/s in ft/min
Go Around CampaignFRA CF, Annina Müller23. Februar 2010Page 44
Fligth Recorder Data Analysis
�Only 5% of all Go-Arounds are flown correctly.
� In average 2,7 SOP-violations can be observed per Go-Around.
� Analysis of 150 Go-Arounds showed 415 SOP-violations .
�Maximum number of violations per Go-Around: 10.
But a word of BIG CAUTION• Research is necessary but must be
performed by competent researchers• Human monitoring of data acquisition is a
must • Computerized data analysis of OPS data
has risks of misleading results• Identification of root causes is paramount
but difficult
APATS Bangkok 17.09.2013 46
What are the next steps?
• A Process for data driven revision and update of training programs must be implemented – the “Inner Loop”
• Control the effectiveness of the training in an “Outer Loop” by measuring the performance in the real OPS through valid Safety Performance Indicators (SPIs)
• Develop such valid SPIs for the Airline Operations and the related training
APATS Bangkok 17.09.2013 47
Main topics for improvement
• Full application of all available training media backed up by a regular training transfer control process
• Global harmonization and joint efforts in the development of the new Evidence Based Training System
• Safety shall be the globally agreed driving factor for this new training system
APATS Bangkok 17.09.2013 48
Conclusion• Initiate a human centered approach to
training, teaching and learning by using all available means of training know-how & technology and validate the efficiency
• Design the testing of knowledge, capabilities and the resulting performance as close as possible to the requirements of the aviation system
• Ensure regular updates driven by data
APATS Bangkok 17.09.2013 49
Thank you for your attention!
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