ATEX (explosive atmosphere) risk assessment is required when any equipment or protective systems are intended for use in potentially explosive atmospheres. However, when reviewing the whole ATEX risk assessment procedures and their results, despite many operations on plant and equipment containing dangerous substances are performed by operators, the human and organizational influences are neglected. With the growing complexity, increased automation and functional sophistication high-technology systems, apart from some events caused by an unusual or unforeseeable manifestation, such as an earthquake, in the majority of cases, human became the main or sometimes even the only cause. The practical need for Human Reliability Analysis (HRA) has grown as part of the requirement to calculate more precisely the probability of an accident and to improve the understanding of human action as a part of system design. This study aims to propose an ATEX Human-Machine-Interaction (HMI) Integrated Safety Assessment (ISA) methodology with integration of the Human Reliability Analysis into the Probabilistic Safety Assessment (PSA), in order to be able to analyse the HOFs influences on ATEX hazards.

Figures - uploaded by Jie Geng

Author content

All figure content in this area was uploaded by Jie Geng

Content may be subject to copyright.

ResearchGate Logo

Discover the world's research

  • 20+ million members
  • 135+ million publications
  • 700k+ research projects

Join for free

7th European Meeting on Chemical Industry and Environment EMChIE 2015

Tarragona, 10-12 June 2015

ATEX (Explosive Atmosphere) Human-Machine-Interaction Integrated Safety

Assessment Methodology

Jie Geng1,2, Salvina Murè1, Gianfranco Camuncoli1, Micaela Demichela2

1 ARIA s.r.l. – Corso Mediterraneo 140 -10129 Torino, Italia

2 SAfeR, Dipartimento di Scienza Applicata e Tecnologia, Politecnico di Torino, Corso Duca degli

Abruzzi, 24 – 10129 Torino, Italia

e-mail: jie.geng@aria.to.it

Abstract

ATEX (explosive atmosphere) risk assessment is required when any equipment or protective systems

are intended for use in potentially explosive atmospheres. However, when reviewing the whole ATEX

risk assessment procedures and their results, despite many operations on plant and equipment

containing dangerous substances are performed by operators, the human and organizational influences

are neglected. With the growing complexity, increased automation and functional sophistication high-

technology systems, apart from some events caused by an unusual or unforeseeable manifestation,

such as an earthquake, in the majority of cases, human became the main or sometimes even the only

cause. The practical need for Human Reliability Analysis (HRA) has grown as part of the requirement to

calculate more precisely the probability of an accident and to improve the understanding of human

action as a part of system design. This study aims to propose an ATEX Human-Machine-Interaction

(HMI) Integrated Safety Assessment (ISA) methodology with integration of the Human Reliability

Analysis into the Probabilistic Safety Assessment (PSA), in order to be able to analyse the HOFs

influences on ATEX hazards.

Keywords: ATEX Risk Assessment, Human-Machine Interaction (HMI), Integrated Safety Assessment

(ISA)

INTRODUCTION

ATEX (explosive atmosphere) risk assessment is required when any equipment or protective

systems are intended for use in potentially explosive atmospheres. The standard ATEX risk evaluation

result relies on a semi-quantitative approach which is based on the following indexes: probability of an

explosive atmosphere formation, probability of the presence of an effective ignition source,

consequences. However, when reviewing the whole ATEX risk assessment procedures and their

results, although many operations are performed by operators, influences from human and

organizational factors (HOFs) are mostly neglected. (e.g. maintenance activity, as in Demichela et al.,

2014, that could even bring to major accidents, as in Piccinini & Demichela, 2012). The ATEX-HMI

(Human-Machine Interaction)-ISA (Integrated Safety Assessment) methodology is proposed in this

paper, in order to be able to analyse the HOFs influences on ATEX hazards.

The ATEX-HMI-ISA methodology needs to face to two challenges: 1) identification of the HOFs

influence on the ATEX risk assessment under the Human-Machine Interaction (HMI) system; 2)

quantification of the HOFs influence with the Integrated Safety Assessment (ISA). To deal with

challenge 1 & 2, the ATEX-HMI-ISA methodology is developed from the standard ATEX risk

assessment methodology (see Figure 1), which consists of four steps: 1) Area Classification, 2)

Ignition Source Identification, 3) Consequence Analysis, and 4) ATEX Risk Evaluation.

Human-Machine Interaction (HMI): Apart from the step 3 (Consequence Analysis) - that is highly

relied on the results from the area classification (step 1), and the step 4 (ATEX Risk Evaluation) - that

needs to integrate step 1-3, the step 1 (Area Classification) and the step 2 (Ignition Source

Identification) are the main considerations of the HOFs integration in the ATEX-HMI-ISA methodology.

Integrated Safety Assessment (ISA): Once HOFs influence in each step is identified, ISA aims to

provide the method for "how to quantify the HOFs influence". Probabilistic Safety Assessment (PSA) is

introduced to be able to quantify the risk with two parts: 1) transferred probability from initial results of

each step in the standard ATEX risk assessment; and 2) Human Error Probability (HEP) from the

Human reliability analysis (HRA). HRA, as one of the important categories of the human factor

techniques, aims to identify and quantify human error. However, in this paper, we are not aiming to

explain how HRA works, but focusing on how to integrate HRA into the developed methodology. Since

the previous works of the HRA integration were based on the Area Classification (Geng et al., 2014;

Geng et al., 2015), in this paper, the step 2 (Ignition Source Identification) are explained in more

details than the step 1 (Area Classification) as an example.

Further, the final ATEX risk evaluation remains in the ATEX-HMI-ISA methodology, which is still

using semi-quantitative values to calculate (RHOF =PHOF*CHOF*D'HOF ). However, those semi-quantitative

values (PHOF, CHOF, and D'HOF) derived from each step are determined by the PSA. In the end, the final

7th European Meeting on Chemical Industry and Environment EMChIE 2015

Tarragona, 10-12 June 2015

ATEX risk evaluation result (RHOF) is influenced by the modified values of PHOF, CHOF and D'HOF. As

mentioned above, two situations coming from the HOFs influence may occur:

1) In case of the plant with the sufficient management,

Result (ATEX-HMI-ISA) = Result (Standard ATEX Risk Assessment)

2) In case of the plant with the insufficient management,

Result (ATEX-HMI-ISA) = Result (Standard ATEX Risk Assessment + HOFs Influence)

Figure 1. The framework of ATEX-HMI-ISA methodology (Geng, et al., 2014)

STEP 1 OF THE ATEX-HMI-ISA METHODOLOGY: AREA CLASSIFICATION

The standard ATEX Area Classification analysis is referred to IEC 60079-10 (for gas) and IEC

61241-10 (for dust). For the specific application in countries, some guidelines provide the detailed

procedures, such as CEI 31-35 and CEI 31-56. It generally includes: 1) the identification of release

sources - each item of the process equipment which contains a flammable material is considered as a

potential release source; 2) assessment of the internal and external zones of the identified emission

sources, on the basis of the degree of release, the release rate, concentration, velocity, ventilation

and other factors (such as prevention measures). In the previous study (Geng et al., 2014; Geng et al.,

2015), the HOFs was identified as a type of prevention measures or barriers in the external zone

prediction part. The barriers can be technical barriers or HOFs barriers. In Area Classification of the

ATEX-HMI-ISA methodology, these barriers were concerned with potential probability of failure (for

example, the probability of the technical barrier failure Ptbf , and/or the HEP). In the end, the Probability

of Barrier Failure (PBF) was integrated into the final PSA, in order to see the difference of the zone

prediction with and without barriers' consideration (see Table 1).

Table 1. ATEX-HMI-ISA area classification zone identification

Emission

Source

Emission

Degree

Generated

Zone Barriers PSA Modified

Zone

E.S. 1

Continuous/

Primary/

Secondary

Internal &

External:

Zone 0/20,

Zone 1/21,

Zone 2/22,

Zone NE

Technical

Barriers/

HOFs Barriers

Integration of :

1) transferred probability

from the standard ATEX

area classification; and

2) Prob. of Barrier Failure

(e.g. HEP, Ptbf)

Internal &

External:

Zone 0/20,

Zone 1/21,

Zone 2/22,

Zone NE

Classification

1. ATEX Area

Classification

Analysis

Considering

Functional Failure

Only (P)

1a. ATEX Area

Classification

Analysis

Considering the

Failure of HOFs

(PHOF )

Sources

2. ATEX Ignition

Sources Analysis

Considering

Functional

Failure Only (C)

2a. ATEX Ignition

Sources Analysis

Considering the

Failure of HOFs

(CHOF )

4. ATEX Risk Level

Analysis RHOF=

PHOF *CHOF*D'HOF

Mitigation of Risks

5. Is this risk

tolerable?

Risk Evaluation

Analysis

3. ATEX

Consequence

Analysis

Considering

Functional

Failure Only (D')

3a. ATEX

Consequence

Analysis

Considering the

Failure of HOFs

(D'HOF )

7th European Meeting on Chemical Industry and Environment EMChIE 2015

Tarragona, 10-12 June 2015

STEP 2 OF THE ATEX-HMI-ISA METHODOLOGY: IGNITION SOURCE IDENTIFICATION

Ignition source identification is the second step to go through if the zone classification is not

determined as zone NE. Different from the step 1 (Area Classification) that only concerns the

equipment end-users, the step 2 (Ignition Source Identification) concerns both of the equipment end-

users and builders. Since the equipment builders were not required to conduct ATEX risk assessment

of the year before 2003, the equipment end-users were the major users to do the ATEX risk

assessment in their whole plants. After the year 2003, because the equipment builders were required

to do the ATEX risk assessment for their products, the standard ATEX ignition source identification

conducted in two ways: 1) for the equipment end-users after the year 2003, the ATEX marking on the

equipment can help analysts to identify the risk combined with the classification zones. 2) for the end-

users of the year before 2003 and the equipment builders, they should follow the procedures

according to EN 1127-1 (2011) and EN 13463-1 (2009). Basically, four definitions of ignition sources

clarified by EN 13463-1 (2009) can be concerned as the guidance of procedures (see Figure 2).

Figure 2. Relationship of possible ignition sources, equipment related ignition sources,

potential ignition sources, and effective ignition sources (EN 13463-1, 2009)

Equipment Related Ignition Sources Identification

EN 1127-1 lists 13 possible ignition sources (see in Table 2). According to the listed possible

ignition sources, the equipment (the targeted emission source) related ignition sources are identified.

During the 13 ignition sources, electrical apparatus, mechanical sparks, and static electricity are the

most frequently identified ignition sources. For some major ignition sources, other standards give more

detailed information. For example, IEC 50404 is especially for the electrostatic source analysis.

Table 2. 13 Possible ignition source list (EN 1127-1, 2011)

- Hot surfaces - Electromagnetic waves

- Flames, hot gases - Ionizing radiations

- Mechanical sparks - High-frequency radiation

- Sparks from electrical equipment - Ultrasounds

- Static electricity - Adiabatic compression

- Catholic protection and corrosion protection - Chemical reactions

- Lightning

Potential Ignition Sources Identification

In terms of EN 13463-1 (2009), Table 3 is used to record the identified potential ignition sources

from the procedure of the equipment related ignition source identification. The column 1 records the

identified potential ignition sources (1a) and basic concerning causes (1b). The column 2 is the

frequency of the occurrence without applying any additional prevention measure or barrier (2a-2d).

Effective Ignition Sources Identification

The final effectiveness of identified potential ignition source should consider with applied barriers.

In Table 4, applied barriers are mentioned in column (3a) with the support of relevant standards (3b)

and received technical documentations (3c). As the result, the frequency of occurrence including

applied barriers (4a-4d) are assessed. In the ATEX-HMI-ISA methodology, the PSA (column e ) and

modified results of the effectiveness (column f ) are introduced, in order to record the final

effectiveness of the identified potential ignition source with the barrier failure consideration.

Possible Ignition Sources

(Identified ignition source listed in EN1127-1)

Equipment Related Ignition Sources

(Ignition source caused by the considered equipment)

Potential Ignition Sources

(Any potential equipment related ignition source that is capable to ignite an explosive

atmosphere)

Effective Ignition Sources

(Any potential ignition source that can ignite an explosive

atmosphere in normal operation, expected malfunction or rare

malfunction)

7th European Meeting on Chemical Industry and Environment EMChIE 2015

Tarragona, 10-12 June 2015

Table 3. Potential Ignition Source Identification (EN 13463-1, 2009)

No.

1 2

Ignition Hazard Assessment of the frequency of occurrence

without application of an additional measure

a b a b c d e

Potential

Ignition

Sources

Description/

Basic Cause

During normal

operation

During

foreseeable

malfunction

During rare

malfunction

Not relevant

Reasons for

Assessment

Table 4. Effective Ignition Source Identification (developed from EN 13463-1, 2009)

3 4

Measures applied to prevent the ignition source becoming

effective Frequency of occurrence incl. measures applied

a b c a b c d

Description

of the

measure

applied

Basis (citation of

standards, technical

rules, experimental

results

Technical

documentation

During normal

operation

During

foreseeable

During rare

malfunction

Not relevant

PSA

Effectiveness

PSA event tree for the Integrated Safety Assessment (ISA)

To quantify the effectiveness of the identified potential ignition source, the PSA event tree is

introduced, which aims to show the relationship between: 1) the initial probability transferred from the

potential ignition sources identification without applying any barrier (PIG), and 2) the potential

probability of barrier failures (PBF). The PBF can be result from the technical barrier failure (Prtbf)

and/or the HOFs barrier failure (HEP).

In Figure 3, the PSA event tree is a simplified representation of the accident sequence by using

Boolean logic (Ioannis, 1998). In the Ignition Source Identification of the ATEX-HMI-ISA methodology,

the initial event of the PSA event tree is the initial result from the potential ignition source identification

without applying any barriers (see Table 3). A series of possible paths are constructed by each applied

barriers (see Table 4). Each path is assigned with a probability of occurrence. As the final

effectiveness of the identified potential ignition source is calculated in case of only when all the

prevention measures are failed, the equation is expressed as:

PSA = PrIG × PrBF1 × PrBF2 × … × Pr BFN = Pr IG × ∏ (PrBFi), i = 1, 2, … , N Eq. (1)

where, PSA is the probability of the effectiveness of the identified potential ignition source. PrIG is the

initial probability transferred from the potential ignition sources identification without applying any

barrier. PrBSi is the probability of the ith barrier succeeding to be active as a prevention measure. PrBFi

is the probability of the ith barrier failure.

Initial Result without

Prevention Measures

Technical

Prevention

Technical

Prevention

…

…

Barrier N: e.g.

HOFs Prevention Consequence

Figure 3. PSA Event Tree

The initial probability

from the potential

ignition sources

identification without

applying any prevention

measure (PIG)

Pr (Barrier 1, Succeed)

Pr (Barrier 1, Failure)

Pr (Barrier 2, Succeed)

Pr (Barrier 2,

Failure)

Pr (Barrier N, Succeed)

Pr (Barrier N, Failure)

…

PrIG × PrBS1

PrIG × PrBF1 × PrBS2

PrIG × PrBF1 × PrBF2

× … × PrBSN

PrIG × PrBF1 × PrBF2

× … × PrBFN

7th European Meeting on Chemical Industry and Environment EMChIE 2015

Tarragona, 10-12 June 2015

Transferring qualitative results into quantitative numbers

Since the initial result from the potential ignition sources identification (see in Table 3) is a

quantitative value, it cannot be calculated directly in the PSA event tree. Different from Area

Classification (Geng, et al., 2014) that can take advantage of probability indexes from the Italian

Guidelines CEI 31-35 (2012) and CEI 31-56 (2007), the Ignition Source Identification of the ATEX-

HMI-ISA methodology is trying to link the uniform probability ranges from the Area Classification by

taking into account the same frequency of occurrence descriptors (see in Table 5).

Table 5. Linking probability ranges with the frequency of occurrence

Effectiveness

Frequency of Occurrence

Assessment for Ignition

Sources (EN 13463-1, 2009)

Probability of Explosive Atmosphere

Formation in 365 days

(CEI 31-56, 2007; CEI 31-35, 2012)

Area

Classification

Frequently During normal operation P>10 -1 Zone 0/20

Occasionally During foreseeable malfunction 10 -1 ≥P>10 -3 Zone 1/21

Rarely During rare malfunction 10 -3 ≥P>10 -5 Zone 2/22

Neglectable Not relevant 10 -5 >P Zone NE

STEP 3 AND STEP 4: CONSEQUENCE ANALYSIS AND ATEX RISK EVALUATION

Consequence Analysis in the standard ATEX risk assessment is relied on the area classification.

Given to the guide of application for the ATEX risk assessment from Cavaliere and Scardamaglia

(2005) and Cavaliere (2011), the following formulas and indexes (see in Table 6) support the

calculation of the semi-quantitative D value that is used for the ATEX Risk Evaluation (step 4). If the

zone prediction changes in the step 1 (Area Classification), the D value is also changed as DHOF .

D'HOF = DHOF + PL + KST + VZ + SS + CN (for dust)

D'HOF = DHOF + PL + KG + VZ + CN (for gas)

Table 6. Indexes for the D value estimation (Cavaliere, 2011)

Factors Unit of

Factors

Indexes

0 0.2 0.4 0.6

Zone NE Zone 2 or Zone 22 Zone 1 or Zone 21 Zone 0 or Zone

20

Personnel

presence (PL) -- Absent of Work Occasional Work Intermittent

Work

Continuous

Work

Dust explosion

index (Kst) (bar x m/s) < 10 10 to 50 51 to 100 > 100

Gas explosion

index (KG) (bar x m/s) < 10 10 to 50 51 to 100 > 100

Cloud volume (VZ) (dm3) 0 ≤ 1 1 ≤ 10 > 10

Layer thickness

(SS) (mm) Absent ≤ 5 5 ≤ 50 > 50

Confined Dust

Cloud (CN) Not Expected Not Confined Partly Confined Completed

Confined

According to the obtained PSA from the step 1 (Area Classification) and step 2 (Ignition Source

Identification), the semi-quantitative values of PHOF and CHOF are determined (see Table 7). With the D

value calculated from the formula mentioned in the step 3 (Consequence Analysis), the ATEX-HMI

risk (RHOF) is the multiplication of PHOF, CHOF, and D'HOF (R HOF = PHOF *CHOF*D'HOF ). The final risk level

refers to Table 8.

Table 7. The semi-quantitative ranking system for the ATEX risk evaluation

Area

Classification

Zone

Probability of Explosive

Atmosphere Formation in 365

days (CEI 31-56, 2007)

Semi-Quantitative Ranking System

Degree P or PHOF C or CHOF D or DHOF

Zone 0/20 P>10-1 Frequently 3 3 0.6

Zone 1/21 10

≥P>10

Occasionaly 2 2 0.4

Zone 2/22 10

≥P>10

Rarely 1 1 0.2

Zone NE 10-5>P Neglectable 0 0 0

Note:

- The D value showed in the table is based on the area classification zones and is only the part of the D' value calculation;

- The D' value is the sum of D value and other factors showed in Table 5; the maximum value of D' for gas is 3, and the

maximum value of D' for dust is 3.6.

7th European Meeting on Chemical Industry and Environment EMChIE 2015

Tarragona, 10-12 June 2015

Table 8: ATEX-HMI risk evaluation criteria

Risk Level Risk Value

High R ≥ 18

Medium 9 ≤ R < 18

Low 1 < R <9

Negligible R ≤ 1

CONCLUSION

This study aims to provide the advanced methodology that is able to analyse the HOFs influences on

ATEX hazards. Two challenges are addressed in the developed ATEX-HMI-ISA methodology: 1) in

order to identify the HOFs influence under the Human-Machine Interaction (HMI) system, each step of

the standard ATEX risk assessment was analyzed. Finally, the HOFs is identified as a barrier for the

further quantification. 2) PSA event tree was proposed for the Integrated Safety Assessment (ISA)

which enable to integrate the transferred initial quantitative results of each step from the standard

ATEX risk assessment and the potential barrier failures.

Acknowledgements

This research is supported in part by the INNHF project ---- "Innovation through Human Factors in risk analysis

and management". The project is financed under EU FP7 Marie Curie Actions Initial Training Networks-FP7-

PEOPLE-2011-ITN: Project ID 289837.

References

Cavaliere A., and Scardamaglia P., 2005, Guida all'applicazione delle direttive ATEX, EPC S.R.L., Italy (in Italian).

Cavaliere A., 2011, Manual for the ATEX application---- Area Classification, Risk Assessment and Management of Explosive

Atmospheres, EPC S.R.L., Italy: Rome, pp.331-333 (in Italian).

CEI EN 60079-10-1, 2010, Explosive atmospheres - Classification of areas - Explosive gas atmospheres, Italian

Electrotechnical Committee.

CEI 31-35, 2012, Equipment for use in the presence of combustible gas – Guide for classification of hazardous area, Italian

Electrotechnical Committee (in Italian).

CEI 31-56, 2007, Equipment for use in the presence of combustible dust – Guide for classification of hazardous area, Italian

Electrotechnical Committee (in Italian).

CEI CLC/TR 50404, 2003, Electrostatics - Code of practice for the avoidance of hazards due to static electricity.

Demichela, M., Pirani, R., Leva, M.C., 2014, Human factor analysis embedded in risk assessment of industrial machines:

Effects on the safety integrity level. International Journal of Performability Engineering, 10 (5), 487-496.

EN 13463, 2009, Non-electrical equipment for use in potentially explosive atmospheres.

EN 61241-14, 2004, Electrical apparatus for use in the presence of combustible dust – Part 14: Selection and installation.

Geng J., Mure S., Camuncoli G., & Demichela M., 2014, Integration of HOFs into ATEX risk assessment methodology,

Chemical Engineering Transactions, 36, 583-588. DOI: 10.3303/CET1436098

Geng J., Mure S., Baldissone G., Camuncoli G., & Demichela M., 2015, Human Error Probability Estimation in ATEX-HMI

Area Classification: from THERP to FUZZY CREAM, Chemical Engineering Transactions, 43.

Hollnagel E., 1998, Cognitive Reliability and Error Analysis Method: CREAM, Oxford: Elsevier Ltd.

Ioannis A. P., 1998, Mathematical foundations of event trees. Reliability Engineering and System Safety, 61(3), 169-183.

Piccinini N., Demichela, M., 2012, Five dead and five injured in a dimethyl terephthalate plant accident: Serious errors in the

plant design coupled with incorrect maintenance management. Industrial and Engineering Chemistry Research, 51 (22),

7619-7627.

Swain A.D., Guttmann H.E., 1983, Handbook of Human Reliability Analysis with emphasis on Nuclear Power Plant Applications,

NUREG/CE-1278. Washington, DC: US Nuclear Regulatory Commission.

UNI EN 1127-1, 2011, Explosive atmospheres - explosion prevention and protection - Part 1: Basic concepts and

methodology.

... maintenance activity). The ATEX-HOF methodology was proposed, with the aim of providing an advanced methodology to analyze HOF influences on ATEX hazards (Figure 1, Geng et al., 2015a). (Geng, et al., 2015a) The original ATEX Risk assessment relies on a semi-quantitative approach as Eq. ...

... The ATEX-HOF methodology was proposed, with the aim of providing an advanced methodology to analyze HOF influences on ATEX hazards (Figure 1, Geng et al., 2015a). (Geng, et al., 2015a) The original ATEX Risk assessment relies on a semi-quantitative approach as Eq. (1). ...

ATEX (explosive atmosphere) risk assessment is required when any equipment or system potentially cause explosive atmospheres. The integrated methodology here is proposed, in order to analyze influences of human and organizational factor (HOF) on ATEX hazards. The on-site application is here discussed showing the advantages: The ATEX-HOF methodology provides a quantitative analysis for the Area classification and Ignition source assessment, and the semi-quantitative approach for the Damage analysis. As a result, the ATEX-HOF risk evaluation becomes more accurate. An event tree based probabilistic assessment has been introduced, which is taking into account both the technical barrier failure (Prtbf) and the human intervention in terms of Human Error Probability (HEP). The on-site applications shown how taking into account HOFs is particular important in companies where the usual hypothesis of the correctness of operator intervention could bring to not conservative results.

... Cavaliere and Scardamaglia (2005) (Geng, et al., 2015a) On the other hand, two representative HRA techniques (THERP and FUZZY CREAM) were applied and compared. The application of FUZZY CREAM provided a simpler, rapid, but effective way to support the Human Reliability Analysis (HRA). ...

... The ATEX-HOF risk evaluation is still using the semiquantitative approach as in Eq. The framework of the ATEX-HOF methodology(Geng, et al., 2015a) 4.1.1 Step 1: ATEX-HOF Area ClassificationThe area classification has been carried out when the initial process and instrumentation line diagrams and initial layout plans were available and confirmed before plant start-up. ...

  • Jie Geng Jie Geng

ATEX (explosive atmosphere) risk assessment is required when any equipment or system potentially causes explosive atmospheres. Despite many operations on plant and equipment containing dangerous substances are performed by operators, influences of human and organizational factor (HOF) are mostly neglected. This research work, according to the overview of the general risk assessment and human factor integration techniques, focuses on the HOF influence on a specific application domain: the ATEX (explosive atmosphere) risk assessment domain. The integrated ATEX risk assessment methodology with HOF is proposed. The ATEX-HOF methodology provides a quantitative risk analysis approach with taking into account of HOF. Inside each phase, clearly assessment goals are identified which are enable to conduct the ATEX risk assessment with simplified 'step-by-step'. An event tree based probabilistic assessment has been introduced, which is taking into account both the technical barrier failure (Prtbf) and the human intervention (e.g. operational failure, and/or operational barrier failure) in terms of Human Error Probability (HEP). Hence, the ATEX-HOF risk assessment becomes more complete than the traditional approach. Two on-site applications shown how taking into account HOFs is particular important in companies where the safety culture is lower and consequently the usual hypothesis of the correctness of operator intervention (in maintenance, normal operations, and emergency) could bring to not conservative results. The applied operational (HOF) barriers explicated in the analysis can be used to support for defining a more detailed set of operational procedures, which is able to maintain the risk level evaluated. In addition, since several accident investigations have found that 80% correspond to human error, in nowadays, the change in safety has focused on developing good safety cultures that positively influence human behaviour at work to reduce errors and violations. HOF as the major consideration within the safety culture plays an important role in the Safety Management System (SMS). Safety culture is not a difficult idea, but it is generally considered as "trust", "values" and "attitudes", which is difficult to clarify the meaning in practise. The Event tree based probabilistic assessment method has been introduced to quantify the HOF influence. This research, hence, can be concerned as an attempt to handle safety cultures in practice via the integration of the risk assessment.

ATEX (explosive atmosphere) risk assessment is required when any equipment or system can potentially cause explosive atmospheres. Although many operations are performed by operators, influences from human and organizational factors (HOFs) are mostly neglected. In order to address HOFs influence, the ATEX-HMI (Human-Machine Interaction) methodology is proposed: it aims at integrating HOFs into each step of the standard ATEX risk assessment. The first step faced is Area classification: the ATEX-HMI methodology introduces the Human Error Probability (HEP) into the zone calculation procedure. Human Reliability Analysis (HRA) is the main method for the HEP assessment, thus two HRA methods were applied for the ATEX-HMI methodology. The first one, THERP, demonstrated an efficient quantitative precision, but it was not easily applicable to real industries. Then, the Cognitive Reliability and Error Analysis Method (CREAM) was adopted, together with a complementary FUZZY application for quantitative analysis. The present paper introduces the FUZZY CREAM application, also showing a comparative analysis of THERP and FUZZY CREAM, on the basis of a food plant case study.

The study consists in devising a method to account qualitatively and quantitatively for the human factor in verifying the Safety Integrity Level (SIL) assigned to machinery. Two crucial aspects have to be taken into account modelling man-machine interaction in Quantitative Risk Analysis (QRA): 1. the need to include the human interaction in the logical model of QRAs techniques; 2. the quantification of the effect of human factors. The efforts were thus aimed at defining an improved methodological framework encompassing the integration of Human and Organisational Factors (H&OF) into safety analysis by means of quantitative risk assessment schemes. In the end, the Integrated Dynamic Decision Analysis (IDDA) was adopted, integrated to Task Analysis. This tool allows modelling the logic of a complex system; it provides a representation of all the possible alternative states into which the system could evolve as a real logical and temporal sequence of events. The proposed model is designed with the aim of transferring the IDDA philosophy to the in-depth study of the deviations that may occur during human implementation of operational procedures and to analyse their effects on system reliability.

The current ATEX (Explosive Atmosphere) risk assessment methodology relies on a semi-quantitative approach based on the following indexes: probability of an explosive atmosphere formation, probability of the presence of an effective ignition source and consequences. The whole risk assessment procedure can be separated into four steps ---- area classification, ignition sources identification, consequence analysis, and risk evaluation. However, when reviewing the whole ATEX risk assessment procedures and their results, despite many operations on plant and equipment containing dangerous substances are performed by operators, the human and organizational influences are neglected. The study proposed in this paper is to develop an ATEX risk assessment methodology with the integration of human and organizational factors (HOFs), in order to provide an advanced methodology able to analyse the HOFs influences on ATEX hazards. The developed ATEX risk assessment methodology introduces in the procedure the Technique for Human Error Rate Prediction (THERP) to identify human and organizational weaknesses, and also provides a tool for calculating the human error probability (HEP) in the first two risk steps ---- area classification and ignition sources identification. During the risk evaluation procedure, human risk level, based on the results of HEP, has been introduced into the original ATEX risk assessment methodology.

  • Micaela Demichela Micaela Demichela
  • Roberta Pirani

The study proposed in this paper consists of devising a method to account qualitatively and quantitatively for the human factor in verifying the Integrity Level of Safety system (SIL) assigned to the machinery. It is called "operational SIL", which may differ from the design SIL, due to the impact of human and organizational factors (H&OF) in the operational phase. There are two crucial aspects related to modelling man-machine interaction in Quantitative Risk Analysis (QRA) context:the need to insert human interaction in the logical model of QRAs techniques;the quantification of effect of human factors. During the study an Operability Analysis, which is usually known with the acronym HAZOP (Hazard and Operability studies) was initially used to support the assessment, but with some added features that enable one to accommodate systematically H&OF into the process called Integrated Recursive Operability Analysis framework (IROA). This first attempt to apply IROA methodology showed that this type of analysis highlights the position where in depth human factor analysis must be carried out. Once the point is identified in which the human erroneous action may occur it will be necessary to include the study of human factors and the assessment human error probability (HEP). Our efforts are aimed at defining an improved methodological framework encompassing the integration of H&OF into safety analysis by means of quantitative risk assessment schemes. In order to do that the adopted tool is the Integrated Dynamic Decision Analysis (IDDA). This tool allows modelling the logic of a complex system; it provides a representation of all the possible alternative states into which the system could evolve, as a real logical and temporal sequence of events. The proposed model is designed precisely with the aim of transferring the IDDA philosophy to the in-depth study of the deviations which may occur during human implementation of operational procedures. IDDA developed on the basis of a Task Analysis (TA) could allow to obtain a detailed quantitative analysis of human factors directly during the same risk assessment. Starting from the analysis of a technological system through IDDA it is possible to integrate in the logical model a task analysis describing where and why the operator can cheat or by-pass the safety system thus including in the assessment explicitly the human factors that allow evaluating the operational SIL.

At 2:10 in the afternoon of 25 July 1968, an explosion in a tank at the SIR (Società Italiana Resine) petrochemical industry in Porto Torres (Sassari, Sardinia) caused the death of five people and the injury of five others. This article reports the events that led to the accident and explains the analysis activities that led to the reconstruction of the dynamics of the accident. The reconstruction of the etiology of the accident has been synthesized in an Incidental Sequence Diagram, a similar logical tree to the Fault Tree, in which the serious errors in the plant design are highlighted together with the poor management of some of the maintenance works.

  • A. D. Swain
  • Henry E. Guttmann

The primary purpose of the Handbook is to present methods, models, and estimated human error probabilities (HEPs) to enable qualified analysts to make quantitative or qualitative assessments of occurrences of human errors in nuclear power plants (NPPs) that affect the availability or operational reliability of engineered safety features and components. The Handbook is intended to provide much of the modeling and information necessary for the performance of human reliability analysis (HRA) as a part of probabilistic risk assessment (PRA) of NPPs. Although not a design guide, a second purpose of the Handbook is to enable the user to recognize error-likely equipment design, plant policies and practices, written procedures, and other human factors problems so that improvements can be considered. The Handbook provides the methodology to identify and quantify the potential for human error in NPP tasks.

  • I.A. Papazoglou I.A. Papazoglou

A mathematical foundation from first principles of event trees is presented. The main objective of this formulation is to offer a formal basis for developing automated computer assisted construction techniques for event trees. The mathematical theory of event trees is based on the correspondence between the paths of the tree and the elements of the outcome space of a joint event. The concept of a basic cylinder set is introduced to describe joint event outcomes conditional on specific outcomes of basic events or unconditional on the outcome of basic events. The concept of outcome space partition is used to describe the minimum amount of information intended to be preserved by the event tree representation. These concepts form the basis for an algorithm for systematic search for and generation of the most compact (reduced) form of an event tree consistent with the minimum amount of information the tree should preserve. This mathematical foundation allows for the development of techniques for automated generation of event trees corresponding to joint events which are formally described through other types of graphical models. Such a technique has been developed for complex systems described by functional blocks and it is reported elsewhere. On the quantification issue of event trees, a formal definition of a probability space corresponding to the event tree outcomes is provided. Finally, a short discussion is offered on the relationship of the presented mathematical theory with the more general use of event trees in reliability analysis of dynamic systems.

Equipment for use in the presence of combustible dust -Guide for classification of hazardous area

CEI 31-56, 2007, Equipment for use in the presence of combustible dust -Guide for classification of hazardous area, Italian Electrotechnical Committee (in Italian).

Explosive atmospheres -Classification of areas -Explosive gas atmospheres

  • Cei En

CEI EN 60079-10-1, 2010, Explosive atmospheres -Classification of areas -Explosive gas atmospheres, Italian Electrotechnical Committee.