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M. Rodriguez / Risk Management in the Process Industry / 3 27 2014 Risk Management in the process industry M. Rodríguez, I. Díaz Autonomous Systems Laboratory Technical University of Madrid 2014 STAMP Conference

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Page 1: Risk Management in the process industrypsas.scripts.mit.edu/home/wp-content/uploads/2014/... · M. Rodriguez / Risk Management in the Process Industry / 3 27 2014 Risk Management

M. Rodriguez / Risk Management in the Process Industry / 3 27 2014

Risk Management in the process industry

M. Rodríguez, I. Díaz

Autonomous Systems Laboratory

Technical University of Madrid

2014 STAMP Conference

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1. Today: Safety in the process industry

2. Tomorrow: STPA for the process industry? A simple example. Open Questions

3. Functional modeling & STPA

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1. Today: Safety in the process industry

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Hey listen… I sell STPAs It’s good for your business

Sorry!, We’ve already got HAZOPs…

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I know…. But look!

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I would say you’ve still got a problem!!

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Ok let’s talk. Let me tell you HOW WE DO THINGS HERE..

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(Commissioning & Startup)

EPC Engineering (detailed) Procurement Construction

FEED ( Front End Engineering Design)

Basic Engineering

Conceptual Stage

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Risk Reduction

Reduce likelihood/consequences Transfer full / part Avoid Risk

Risk analysis & assessment

Analysis methods Likelihood & Consequences

Identify Hazards

Risk Classes

Establish context & Process Info

Stakeholders

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Standards

Regulations

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IEC 61511 / ISA S84.01 (IEC 61508 )

Seveso I, II, III --- Europe

OSHA 29 CFR1910.119 --- USA

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IEC 61511 Safety Lifecycle

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Safety Lifecycle Closed Loop

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Hazards studies

1. Hazards types identification

2. Preliminar Hazard Analysis

3. Analysis Methods & Evaluation

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Hazards studies

1. Hazards types identification

2. Preliminar Hazard Analysis

3. Analysis Methods & Evaluation

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DESIGN INTENTION

DEVIATION = ELEMENT + GUIDEWORD (PARAMETER/ CHARACTERISTIC)

MIXING PHASE LEVEL TEMP. PRESSURE COMPOSITION FLOW REACTION COMM

NO / NONE MORE LESS AS WELL AS PART OF REVERSE OTHER THAN ------------------ WHERE ELSE BEFORE / AFTER EARLY / LATE FASTER / SLOWER [NOT ALL DEVIATIONS FEASIBLE]

DIRECT CAUSALITY

CAUSES CONSEQUENCES

SAFEGUARDS

RECOMMENDATIONS /ACTIONS ALARMS/SIS

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Emergency Plans

Fire & gas

Flare & Scrubber

SIS

Alarm

BPCS

Process

19

mitigatio

n

pre

ven

tio

n

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Nice!. Let me show you something….

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2. Tomorrow: STPA for the process industry?

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What I do (and HAZOP doesn’t) • Include socio-technical

analysis (human factor) • Include systemic factors • Include all the hierarchy (from

regulations to the process): Safety culture

• Fill the design operation gap: avoid higher risk states

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What I do not do (vs. traditional safety) • Put the blame on you • Consider only reliability and

probability • Work only in the design stage Basically I don’t follow chains of events!

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1. ESTABLISH SYSTEM ENGINEERING FOUNDATION

FUNCTIONAL CONTROL STRUCTURE

2. IDENTIFY UNSAFE CONTROL ACTIONS (UCAs)

3. USE UCAs TO CREATE SAFETY REQUIREMENTS / CONSTRAINTS

4. DETERMINE HOW EACH HAZARDOUS CONTROL ACTION COULD OCCURR

PROVIDED NOT PROVIDED EARLY / LATE TOO SOON / TOO LONG NOT FOLLOWED THE CA

HAZARDS TYPES

HAZID

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A simple example

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STPA for the process industry

Preventive actions can be obtained from the analysis!!

They can be ranked following some criteria, for example less deviation from current hazardous state

States considered: • Desired (D) • More (+) • Less (-) • No / none (N)

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Source Controller: Cooling Water Supply. Type Not provided

Process Variables: Context System state

Fmonomer Finitiator Reaction Rate Temperature Hazard

D D + + Yes

+ D + + Yes

+ N N D No

N + N D No

D + + + Yes

… … … … …

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Accident Hazard SafetyConstraint

Explosion H1:Temperaturetoohigh Temperaturemustnever

violatemaximumvalue

H2:Pressuretoohigh Pressuremustneverviolate

maximumvalue

Leakage H3:Leveltoohigh Levelmustneverviolatemaximumvalue

STPA for the process industry

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Source Controller: Open level control valve. Type: Not Provided

ID Fcw Fgas F1 F2 Hazard

1 + + + + H1, H2, H3

2 + + + - H2, H3

3 + + + N H2

4 + + + D H2, H3

5 + + - + H3

6 + + - - H3

7 + + - N --

8 + + - D H3

9 + + N + H3

10 + + N - H3

11 + + N N --

12 + + N D H3

252 D D N D H3

253 D D D + H3

254 D D D - H3

255 D D D N --

256 D D D D H3

… … … … … …

… … … … … …

… … … … … …

States considered: • Desired (D) • More (+) • Less (-) • No / none (N)

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Open Questions

• STPA explicit step? Be sure that there is at least one control action for every hazard identified

• A chemical plant has thousands of variables and controllers: How to define the system limits for the analysis? Physical equipment? Functionally?

• How many states must be considered for the Process Variables (discretize)?

• How many variables have to be considered (pressure, flow, composition, temperature, etc.)?

• Can STPA cope with hazards like pipe leaks, dust accumulation, static electricity, HTHA cracking, alarms problems, etc.?

• How to filter relevant contexts to hazards to avoid unneccessary scenarios?

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3. Functional modeling & STPA

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But there’s more, if you buy STPA you get ….. A functional modeling tool FOR FREE!

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Functional Modeling Methodology used to model any man made system by identifying the overall goal and the functions needed to achieve it. It uses qualitative reasoning.

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Why Functional Modeling?

Integrated Process Design & Operation & Automation

Provide a systematic framework for formalizing inter subjective common sense knowledge which is shared among participants in design and operation of complex systems i.e. engineers and operators. Functional modeling is a systematic approach to applying different perspectives and degree of abstraction in the description of a system and to represent shifts in contexts of purpose. This aspect of FM is crucial for its use in handling complexity in systems design and operation.

Support integrated process and control system design by providing abstractions by which high level decision opportunities and constraints in process and control system design can be made explicit. FM can be used to reason about control strategies, diagnosis and planning problems.

M. Lind.Nuclear Safety and Simulation, Vol. 4, Number 3, September 2013

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Orthogonal :

means-ends / part-whole

Alltogether:

Function / structure

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Higraphs / statecharts

A digital watch

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Higraphs • Blobs: states

• Edges: transitions

• Exclusion: OR

• Orthogonality: AND

Required conditions • Blobs: functions

• Edges: states

• Exclusion: AND

• Orthogonality: OR

function 1 state 1 state 2

(function) state 1

transition state 2

dualization

D-higraphs: The origin

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Structural description: variables that

characterize the system. Flow(F),

temperature (T), Level (L),etc.

Used by D-higraphs

Behavioral description: Potential

behavior of the system as a network.

Functional description: Purpose of a

structural component of connections.

Provided by the D-higraph layout.

Systems’ view Description

D-higraphs: Elements & Properties

Properties: Inclusion, exclusion and cartesian product

material energy

info

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D-higraphs: Qualitative simulation

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D-higraphs & STPA

Controllers x UCAs x statesContextVars

STPA generates huge tables:

D-higraphs exploits the model to reduce the analysis

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1. Associate every hazard with a variable Hi(var_x)

1. See var_x dependencies in D-higraphs var_x(var_i++,var_j-+,var_k++)

3. Identify which of the variables is a CA ( var_j)

4. Apply UCAs scenarios CA: var_j Context var_i, var_k

5. Identify non hazardous contexts potential solutions

6. Rank safe contexts

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D-higraphs & STPA STEPS:

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D-higraphs can also help in STPA step 4: Determine how each hazardous control action

could occurr. D-higraphs allows for

root cause & consequence analysis.

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D-higraphs & STPA

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Remarks

• Presentation focused on the low level of the architecture Upper levels are similar to other domains

Functional modeling can represent the architecture (abstraction & hierarchy)

• STPA for the process industry needs knowledge to avoid huge

tables • D-higraphs (easy) extension to include humans (as controllers)

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OPERATION & MANAGEMENT

DESIGN & OPERATION ST

PA

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Conclusion You have a very promising future… But you’re still young. Come back in a few years

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aslab.org

[email protected]