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Safety Management System Performance Based on Organizational
Factors of “Seveso” sites
Papadakis Georgios A., Kokkinos Konstantinos G. & Machaira Paschalia P. Industrial Risk ManagementDept. of Production Engineering and ManagementTechnical University of Crete (TUC), Chania, Greece
TUC PAPADAKIS, KOKKINOS & MACHAIRA SRA-E 11-13 SEPTEMBER 2006 LJUBLJANA, SLOVENIA
Purpose Of the Study
• Development and analysis of an integrated model of Safety Management Systems (SMS) in “Seveso” sites for the control of major-accident hazards involving dangerous substances.
• Linkage of the events of a Fault Tree to SMS and quantification of SMS performance through measuring reliability and performance of system elements and safety related procedures.
TUC PAPADAKIS, KOKKINOS & MACHAIRA SRA-E 11-13 SEPTEMBER 2006 LJUBLJANA, SLOVENIA
The SMS elements
Management&
Leadership
Risk Assessment
Emergency Planning
GPPolicy/Goals
Available Resources
RR
PS
F
TK
GP
RAL
RR
PS
TK
TK
Accident Scenarios/Consequence Zones/Risk Evaluation
GP
RR
PS
Overall Performance
Problem Identification
Training Needs
PS
TK
Training NeedsTraining Needs
Training Needs
OK Yes
No
Preventive, Control and Mitigation Measures
PCMM
RAC
RAL
RAL
RAL
Goal Prioritization
Resource Alloc.
Roles-Respons.
Personnel Selection
Formalization
Monitoring Performance
Audit
QA-Perf. Evaluation
Problem Identification
Problem Identification
Problem Identification
QA-Perf.Evaluation
Problem Identification
Training(Management &
Personnel)
GP
RR
PS TK
Training Needs
RAL
Operations
GP
RR
PS
TK
Training Needs
RAL
Problem Identification
QA-Perf.Evaluation
Maintenance
TK
GP
RAL
RR
PS
Training Needs
Problem Identification
Prev. Maintenance/Test
Corrective Maintenance
Eq.&Struct. Monitoring
AS/CZ/RE
Planned Eq.&Pr.Changes
Systems Perf. Data
Systems Performance Data
Rel.Data/Systems Perf.Data
RR
ORK
ORKORKORK
ORK
QA-Perf.Evaluation
QA-Perf. Evaluation
CORCoordination
F COR
F COR
Equipment Performance
Plant Data/Systems Perf.
Equipment Performance
Overall Performance
COM
CEN
TU
COMCEN
F CORCOMCEN
CEN COM TU
F COR
COM
CEN
TU
F COR
COM
CEN
TU
F COR
COM
CEN
TU
OWN
OWN
OWN OWN
OWN
OWN
OWN
OL
OL
OL
OL
OL
OL
OL
ORK ORK
TUC PAPADAKIS, KOKKINOS & MACHAIRA SRA-E 11-13 SEPTEMBER 2006 LJUBLJANA, SLOVENIA
The SMS factors
• 30 principal organizational and management factors related
to the safety management.
• 16 organizational factors proposed in nuclear safety research and catalogued in five general categories:
1. decision making2. communications3. human resource allocation4. administrative knowledge5. Culture
• 14 management & other organizational factors not in taxonomy on the basis of the most important activities in operations with dangerous substances.
TUC PAPADAKIS, KOKKINOS & MACHAIRA SRA-E 11-13 SEPTEMBER 2006 LJUBLJANA, SLOVENIA
The SMS factors
TUC PAPADAKIS, KOKKINOS & MACHAIRA SRA-E 11-13 SEPTEMBER 2006 LJUBLJANA, SLOVENIA
Organizational factors
Decision Making: Centralization (CEN), Goal Prioritization (GP), Problem Identification (PI), Organizational Learning (OL), Resource Allocation (RAL)Communications: Communication (COM) (External, Inter/Intra-departmental) Human Resource Allocation: Quality Assessment (QA)/Perf. Evaluation, Personnel Selection (PS), Technical Knowledge (TK), Training Needs (TN)Administrative Knowledge: Coordination of Work (COR), Formalization (F), Organizational Knowledge (ORK), Roles-Responsibilities (RR)Culture: Ownership (OWN), Time Urgency (TU)
The SMS factors
TUC PAPADAKIS, KOKKINOS & MACHAIRA SRA-E 11-13 SEPTEMBER 2006 LJUBLJANA, SLOVENIA
Management & other organizational factors (not in taxonomy)
Policy/GoalsAvailable ResourcesOverall PerformancePlanned Equipment and Procedure ChangesPlant Data/Systems PerformanceSystems Performance DataEquipment and Structures Monitoring Equipment Performance Corrective Maintenance Preventive Maintenance/TestRisk Assessment Criteria (RAC) Accident Scenarios/Consequences Zones/Risk Evaluation (AS/CZ/RE) Preventive, Control & Mitigation Measures (PCMM) Reliability Data/Systems Performance Data
The model action-flow diagram
• Representation of SMS elements and factors in a model action-flow diagram using the Structured Analysis and Design Technique (SADT).
• Interconnections between factors and elements and interrelations between elements can be defined and thus action flows can be delineated.
• Localization of problem areas, discovery of organizational and management weaknesses of a SMS and user guidance to specific actions.
TUC PAPADAKIS, KOKKINOS & MACHAIRA SRA-E 11-13 SEPTEMBER 2006 LJUBLJANA, SLOVENIA
The system work-flow loops
• Sequences of actions related to important safety operations. It is postulated that each loop: – Is closed (starts and ends at the same element) – Has a specified target and is operationally independent
from other loops– Is discrete in time with specified duration and operates
either in parallel or in series with other loops
• Under these terms, the loops are bound to consist of factors that connect system elements and to show the logical arrangement of actions that should be performed for the safe operation of the system.
TUC PAPADAKIS, KOKKINOS & MACHAIRA SRA-E 11-13 SEPTEMBER 2006 LJUBLJANA, SLOVENIA
The system work-flow loops
• Division of loops in: – “Fast response” loops (i.e. those related to safe
operations of processes with dangerous substances) – “Slow response” loops (i.e. those related to
implementation of training activities)
• In order for a loop to be meaningful for safety: – All its factors and procedures should be considered
operable and not fail on demand (reliability)– Its target should be met within predetermined period of
time (effectiveness)
• There is always one (or more) “controlling mechanisms” to which reliability and effectiveness of the loop is more sensitive.
TUC PAPADAKIS, KOKKINOS & MACHAIRA SRA-E 11-13 SEPTEMBER 2006 LJUBLJANA, SLOVENIA
Analysis of “Seveso” Sites operations in work-flow loops
• Analysis of “Seveso” sites safety operations in loops with data from an industrial site in Greece.
• Analysis of SMS operation considering 15 principal loops necessary for the prevention of accidents involving dangerous substances.
• Identification of organizational factors as underlying causes of SMS failure and contributing to SMS inefficiency.
TUC PAPADAKIS, KOKKINOS & MACHAIRA SRA-E 11-13 SEPTEMBER 2006 LJUBLJANA, SLOVENIA
Quantification of SMS performance
• Based on SAM approach (Pate-Cornel & Murphy 1996), SMS reliability is measured by linking the probability of each top event (i.e. release of dangerous substance) to work-flow loops.
• The events (technical, organizational, managerial) identified in a fault tree of an accident scenario (top event) are assumed to be linked to the SMS.
• Principal feature of the proposed approach is the use of Minimal Cut Sets (MCS = minimal set of events that lead to the undesired top event).
• The probability of a MCSk is assumed to be influenced by the actions and procedures of the SMS, found in (j) loops, Bjk.
TUC PAPADAKIS, KOKKINOS & MACHAIRA SRA-E 11-13 SEPTEMBER 2006 LJUBLJANA, SLOVENIA
Quantification of SMS performance
TUC PAPADAKIS, KOKKINOS & MACHAIRA SRA-E 11-13 SEPTEMBER 2006 LJUBLJANA, SLOVENIA
If a specific top event F is analyzed using FTA, the probability of that top event P(F) can be described by:
Each loop Bjk consists of (i) independent factors Oij in series. The conditional probability of a top event F if a factor Oij fails can be expressed by:
jkkk j
ij BMCSPOFP ||
Given the condition that each loop is operationally independent from others, the probability of a MCSk can be calculated by:
jkk j
jkk BPBMCSPFP |)(
j
jkk BPMCSP
CASE STUDY
TUC PAPADAKIS, KOKKINOS & MACHAIRA SRA-E 11-13 SEPTEMBER 2006 LJUBLJANA, SLOVENIA
In the simplest case of two loops influencing a MCSk, the probability of the MCSk can be estimated by the equation:
2221112222111121
21
111
111112
1
BBBBBBBBBBBBBBBB
jk
tttttttttttttt
Bj
BBMCS
eeeeeeee
RRtRtR
Assuming that: 11 BB te and
22 BB te
the probability of the MCSk can be expressed by:
2211 BBBB
k
tttt
MCS eetR
CASE STUDY
TUC PAPADAKIS, KOKKINOS & MACHAIRA SRA-E 11-13 SEPTEMBER 2006 LJUBLJANA, SLOVENIA
To further the analysis, the following cases are examined:
– Loop B1 is assumed to be a “fast response” loop and loop B2 a “slow response” loop. In this case the MCSk reliability was found to be determined by the reliability of the “fast response” loop when λB1 < λB2.
– Both two loops are assumed to be “fast response” loops (tB1, tB2→0). The MCSk reliability is then determined by the reliabilities of both loops for t > tB1, tB2:
tt
MCSBB
keetR 21
The quantitative results show that the reliability of a MCSk is mostly controlled by the “fast response” loops (tB0) and thus safety performance is expected to depend more on “fast response” loops.
CASE STUDY
• Given the condition that each loop Bj consists of (i) independent factors Oij in series the reliability of a loop can be calculated by multiplying the reliabilities for all factors. Using the reliability expressions for each factor, the reliability of a loop Bj during the time interval (0, t) can be expressed by:
TUC PAPADAKIS, KOKKINOS & MACHAIRA SRA-E 11-13 SEPTEMBER 2006 LJUBLJANA, SLOVENIA
n
i
tn
i
tt iijiij
jeetR
11
where λij = constant failure rate of factor Oij; ti = operational time of factor Oij; and n = total number of factors.
The above expression shows that the reliability of a loop is controlled by the factors with short duration (ti →0) and thus safety performance is expected to depend more on these factors.
Example of a loop for the prevention of fuel release
TUC PAPADAKIS, KOKKINOS & MACHAIRA SRA-E 11-13 SEPTEMBER 2006 LJUBLJANA, SLOVENIA
Management&
Leadership
Risk Assessment
Emergency Planning
GPPolicy/Goals
Available Resources
RR
PS
F
TK
GP
RAL
RR
PS
TK
TK
Accident Scenarios/Consequence Zones/Risk Evaluation
GP
RR
PS
Overall Performance
Problem Identification
Training Needs
PS
TK
Training NeedsTraining Needs
Training Needs
OK Yes
No
Preventive, Control and Mitigation Measures
PCMM
RAC
RAL
RAL
RAL
Goal Prioritization
Resource Alloc.
Roles-Respons.
Personnel Selection
Formalization
Monitoring Performance
Audit
QA-Perf. Evaluation
Problem Identification
Problem Identification
Problem Identification
QA-Perf.Evaluation
Problem Identification
Training(Management &
Personnel)
GP
RR
PS TK
Training Needs
RAL
Operations
GP
RR
PS
TK
Training Needs
RAL
Problem Identification
QA-Perf.Evaluation
Maintenance
TK
GP
RAL
RR
PS
Training Needs
Problem Identification
Prev. Maintenance/Test
Corrective Maintenance
Eq.&Struct. Monitoring
AS/CZ/RE
Planned Eq.&Pr.Changes
Systems Perf. Data
Systems Performance Data
Rel.Data/Systems Perf.Data
RR
ORK
ORKORKORK
ORK
QA-Perf.Evaluation
QA-Perf. Evaluation
CORCoordination
F COR
F COR
Equipment Performance
Plant Data/Systems Perf.
Equipment Performance
Overall Performance
COM
CEN
TU
COMCEN
F CORCOMCEN
CEN COM TU
F COR
COM
CEN
TU
F COR
COM
CEN
TU
F COR
COM
CEN
TU
OWN
OWN
OWN OWN
OWN
OWN
OWN
OL
OL
OL
OL
OL
OL
OL
ORK ORK
CASE STUDY RESULTS
TUC PAPADAKIS, KOKKINOS & MACHAIRA SRA-E 11-13 SEPTEMBER 2006 LJUBLJANA, SLOVENIA
200 400 600 800 1000 1200 1400 1600 1800 200010
-10
10-8
10-6
10-4
10-2
100
t
R
Ra
Rb
R
Figure presents MCSk reliability (R) with respect to the reliability of critical loops B1 (Ra) and B2 (Rb) with λB1=0.005 hr -1, tB1=4 hrs, λΒ2=0,01 hr -1 and tB2=100 hrs
Conclusions
• The model action-flow diagram can be used in its own right as a means of identifying organizational and management weaknesses of a SMS.
• The analysis of important safety operations in work-flow loops shows the applicability and usefulness of the proposed model.
• The model can be widely used as a decision support tool for safety critical actions in the SMS of any organization.
• The linkage of events of a fault tree to the SMS help to discover “controlling” organizational factors in the SMS that affect system performance.
TUC PAPADAKIS, KOKKINOS & MACHAIRA SRA-E 11-13 SEPTEMBER 2006 LJUBLJANA, SLOVENIA
Conclusions
• There are indications that fast safety actions influence more SMS performance.
• There are indications that the “controlling mechanisms” mostly contributing to SMS failure and SMS inefficiency are factors which achieve their tasks in short time.
• Proposals to future research: – Application of SMS in other activities involving
dangerous substances.– Use of quantitative data for better understanding of the
impact of organizational factors on performance and reliability of SMS.
TUC PAPADAKIS, KOKKINOS & MACHAIRA SRA-E 11-13 SEPTEMBER 2006 LJUBLJANA, SLOVENIA