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Toru Nakata
National Institute of Advanced Industrial Science
and Technology, Japan.
Human Factors and Functinal Safety
1
Depending on Humans too much
 Do you feel unmanned systems safe?
 Elevators, automatic train, etc.
 Full-automatic airplane?
 Why do we think manned systems safer?
 Some machines are less reliable than humans.
 Humans can behave as hero under emergency?
 Humans can violate safety rules slightly to maintain
efficiency and convenience of the jobs?
 Human can undertake responsibility?
 Or, designers of systems abandon to improve their
design draft and leave residual risks to human
operators?2
Four Aspects of Human
1. Human as a Supervisor
 Humans decide the goal of operation.
 In case of dangerous situation, humans can decides the
abandonment of the operation for safety.
2. Human as a Controller
 Humans can regulate the system and reduce error.
3. Human as a EUC (equipment under control)
 Human body can be a part of the system.
4. Human as a Disturbance Source
 Human commits mistakes.
3
Humans should be …
Aspect Desirable Undesirable
Supervisor
Decision with consideration Hasty decision
Pre-determined safety
strategy.
Difficult choice over dilemma
Well informed Lack of information
Controller
Dexterity not required. Dependency on personal skill
Discrete control task Continuous control task
Safety rules are protected Rules can be violated by human
EUC
Human can taka a rest. Human must work stable.
Only human can do the task. Machines are suitable for task.
Disturbance
Humans are isolated to
system
Human has access to the
system.
4
Those 9 points should accord to SIL (safety integration level).
Probability of Human Error
 HEP: Human Error Probability
 HR: Human Reliability, HEP = 1 - HR
 It is very hard to forecast HEP.
 So we should
1. Use deterministic evaluation of safety in proper
cases.
2. Use tree-diagram analysis when we need
quantitative evaluation
3. Create consensus on risk evaluation. This is the most
important point.
5
Deterministic? Probabilistic?
 Deterministic: Phenomenon has high reproducibility
 Some human errors are deterministic, and they can be
reproduced under a certain condition.
 Students tends to commit same error like
23-17 = 27-13 = 14.
 Probabilistic: Less reproducibility. (High entropy.)
 Uncertainty on skill task
6
Deterministic Error Estimation
 Find the letter “O” in 3 seconds.
7
O
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
Q
P
S
Q
S
A
Q
C
O
S
D
D
D
Q
DV
A
P
T
D
S
C
D
D
V
B
QB
W
R
D
S
C
R
D
D
C
A
L
D
S
E
T
P
T
I
Q
F
Q
D
B
Y
R
V
X
T
Z
T
M
H
J
G
S
O
W
T
K
T
U
N
B
D
100% successful Almost 100% failProbabilistic
We know the reasons of success:
“on the coner, aligned, shape differences of O and T.”
We can conclude 100% success for this case.
Thresholds of deterministic area
8
Probabilistic Error Evaluation
 Many techniques already exist
 Technique for Human Error Rate Prediction (THERP)
 Anyway, we do not know presice HEP. So we should
 Conduct experiments to measure HEP,
 Find some typical and prousible value of HEP from
papers and books,
 Or calculate the HEP value with tree-diagram analysis.
9
Fault Tree Analysis (FTA)
10
To calculate a certain failure probability
Event Tree Analysis (ETA)
11
Evaluate risk hidden in a certain situation
Strictness of Evaluation
More strict Less strict
Evidence of value
Proven in practice,
measured in exprmnt
Designer’s opinion
Number of subject Many Less than 4.
Subject
Various. General
comsumers.
Homogeneous. Colleagues
of the designer.
Exprmt Scenario Walkthrough. Partial.
Exprmt Environment Realistic with variety. In-room experiment
Feedback of failure info
from users
Exists. Not exists.
Method
Quantitative. Structural
(ETA, FTA, or HAZOP, etc.)
Qualitative. Less structural.
12
Consensus is the most important
 Consensus of choice of risk evaluation scheme
 Degree of consensus must accord to required SIL.
 Broadness of consensus
1. Only the designer
2. Inside the designer’s group.
3. Among the independent design review unit.
4. Among particular buyer and user of the system.
5. Among the governmental sections.
6. Among the general consumers.
13

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Nakata1503 jsse

  • 1. Toru Nakata National Institute of Advanced Industrial Science and Technology, Japan. Human Factors and Functinal Safety 1
  • 2. Depending on Humans too much  Do you feel unmanned systems safe?  Elevators, automatic train, etc.  Full-automatic airplane?  Why do we think manned systems safer?  Some machines are less reliable than humans.  Humans can behave as hero under emergency?  Humans can violate safety rules slightly to maintain efficiency and convenience of the jobs?  Human can undertake responsibility?  Or, designers of systems abandon to improve their design draft and leave residual risks to human operators?2
  • 3. Four Aspects of Human 1. Human as a Supervisor  Humans decide the goal of operation.  In case of dangerous situation, humans can decides the abandonment of the operation for safety. 2. Human as a Controller  Humans can regulate the system and reduce error. 3. Human as a EUC (equipment under control)  Human body can be a part of the system. 4. Human as a Disturbance Source  Human commits mistakes. 3
  • 4. Humans should be … Aspect Desirable Undesirable Supervisor Decision with consideration Hasty decision Pre-determined safety strategy. Difficult choice over dilemma Well informed Lack of information Controller Dexterity not required. Dependency on personal skill Discrete control task Continuous control task Safety rules are protected Rules can be violated by human EUC Human can taka a rest. Human must work stable. Only human can do the task. Machines are suitable for task. Disturbance Humans are isolated to system Human has access to the system. 4 Those 9 points should accord to SIL (safety integration level).
  • 5. Probability of Human Error  HEP: Human Error Probability  HR: Human Reliability, HEP = 1 - HR  It is very hard to forecast HEP.  So we should 1. Use deterministic evaluation of safety in proper cases. 2. Use tree-diagram analysis when we need quantitative evaluation 3. Create consensus on risk evaluation. This is the most important point. 5
  • 6. Deterministic? Probabilistic?  Deterministic: Phenomenon has high reproducibility  Some human errors are deterministic, and they can be reproduced under a certain condition.  Students tends to commit same error like 23-17 = 27-13 = 14.  Probabilistic: Less reproducibility. (High entropy.)  Uncertainty on skill task 6
  • 7. Deterministic Error Estimation  Find the letter “O” in 3 seconds. 7 O T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T Q P S Q S A Q C O S D D D Q DV A P T D S C D D V B QB W R D S C R D D C A L D S E T P T I Q F Q D B Y R V X T Z T M H J G S O W T K T U N B D 100% successful Almost 100% failProbabilistic We know the reasons of success: “on the coner, aligned, shape differences of O and T.” We can conclude 100% success for this case.
  • 9. Probabilistic Error Evaluation  Many techniques already exist  Technique for Human Error Rate Prediction (THERP)  Anyway, we do not know presice HEP. So we should  Conduct experiments to measure HEP,  Find some typical and prousible value of HEP from papers and books,  Or calculate the HEP value with tree-diagram analysis. 9
  • 10. Fault Tree Analysis (FTA) 10 To calculate a certain failure probability
  • 11. Event Tree Analysis (ETA) 11 Evaluate risk hidden in a certain situation
  • 12. Strictness of Evaluation More strict Less strict Evidence of value Proven in practice, measured in exprmnt Designer’s opinion Number of subject Many Less than 4. Subject Various. General comsumers. Homogeneous. Colleagues of the designer. Exprmt Scenario Walkthrough. Partial. Exprmt Environment Realistic with variety. In-room experiment Feedback of failure info from users Exists. Not exists. Method Quantitative. Structural (ETA, FTA, or HAZOP, etc.) Qualitative. Less structural. 12
  • 13. Consensus is the most important  Consensus of choice of risk evaluation scheme  Degree of consensus must accord to required SIL.  Broadness of consensus 1. Only the designer 2. Inside the designer’s group. 3. Among the independent design review unit. 4. Among particular buyer and user of the system. 5. Among the governmental sections. 6. Among the general consumers. 13