Digital Transformation of Process and Functional Safety

David Hansen, CFSE – ISA Houston– SIS SILverstone

dhansen@sissilverstone.com

281-701-6476

Announcements

• Happy 75th Birthday ISA New Orleans Section!

• New “Diamond Sponsor” program - $75/year• Petrotech, Denison Technologies, ArtZat Consulting, Crescent Power Systems

• Check out ISAConnect

• Young Professionals – ISA Connect Live Meet Up• April 28th – 9AM CST

• New Orleans Section Executive Committee Meeting• April 29th – 5PM CST

Presentation Sponsors

DefinitionsDigitization

• Convert analog information into digital. E.g. scanning paper documents

Digitalization

• Process of moving to a digital business.

• Projects.

• Unclear and used in different ways.

Digital Transformation

• Includes Digitalization projects

• Reorganization of the business around data platforms.

Digital Twins

• Computer models.

• Used to predict based on real or theoretical data.

• You probably have a digital twin.

Psychodigital Tranformulization

• I made this up

Object Class:Defense Attack Robot

Mark I (DAR)

Object:DAR 18709

Object:DAR 18710

Object Class:shopper

Object:Bill

Object:Jill

Data

Model number

Price

Number sold

Purchasers

Reviews

Profile of likely customers

Internal Data

Other purchases

Reviews

Returns

Views

Purchase

Review

Purchase

Review

Purchased Data

Politics

Friends and family

Occupation

Pets

Likes and dislikes

DAR is great! Took over a small country with its help!

DAR is terrible! It killed my cat!

Machine Learning Data Analytics Recommendation: Market to dictators, avoid cat owners.

Object Oriented - Shopping

Object Class:HAZOP/LOPA risk

scenarios

Object:Tower Overflow to

compressor Scenario

Object:Tower flood and

overpressure scenario

Object Class:Independent

Protection Layer

Object:Safety

Instrumented Function SIF-101Compressor S/D

Object:SIF-129

Tower feed S/D

Event Data

Diagnostics

Bypasses

Failures

Incidences

Activations

Object Oriented – Functional Safety

Object:PSV-134Tower

Object:LT-101

Object Class:Device

Object:XS-145

Object:XV-137

Object:PSV-134

Object:Process Equipment

Object:Process Units

Object:Facilities

Object:Enterprise

Key Performance Indicators (KPIs)

Other Data Connections

Financial Systems

Projects

Asset Management Systems

Process Simulators

Maintenance Systems

Analytics Systems

Data Analytics Recommendation: ACME Model 146 level transmitters are causing significant elevated enterprise risks.

Data Analytics/Machine Learning

Data Lake

Process Safety

Personnel

Devices

Maintenance

Asset Management

Location and Weather

• Digitalization= data overload.

• Need automated functionality to fully benefit.

• Machine Learning looks for patterns.

Theoretical Cases

1. Analytics discovers that elevated risks from seemingly random failures from different types of transmitters are not random. Analytics from users and vendors determine that a specific capacitor type is failing in hot weather conditions.

2. Analytics automatically discover outlier risk rankings for similar scenarios across the organization. Either too many resources are being allocated or risks are too elevated.

Digital Transformation is here!

• How we make money• Video game industry• Publishing (Youtube)• Investing• Onlyfans

• How we manage our money • How we manage money• Money itself (crypto currency)

• How we spend our money• Shopping from home• AI telling us what we want

• How we interact with each other• Social Media• Dating

• How we govern• Climate Change• COVID response• AI Gods

One portal to access all your information from any device anywhere.

Digital Transformation is not Here!

Process Industries Functional and Process Safety

• Online documents (PDF, Word, Excel)

• Disconnected tools

• PHA/LOPA database tool

• Word

• Excel

• SIL Calculation tool

• SRS Database

• Action Tracking software

• MOC software

• Document management software

• CMMS

• Paper test results

• Control system event logs

• All isolated from each other.

• Difficult to access.

Why the slow transformation?

• Engineering companies typically deliver PDF format.

• Hangover from financial system digital transformations.

• Consultants make lots of money the traditional way.

• Change makes experts into amateurs.

• Very cautious operating company IT departments.

• Companies are focused on product, not software.

• Limited software budgets competing for various initiatives.

• Perception that they are already safe.

• Ignorance is bliss. Hidden risks can be revealed by software platforms.

• Have already invested in existing isolated tools.

Digital Transformation is Coming

Data Lake

• Most major operating companies doing something:• From voicing interest to

• Tiny budgets to

• Significant budgets and software evaluations to

• Ambitious Data Lakes.

• Many pilot projects ongoing.

• Some facilities are transformed.

• Major driver is for high level process safety KPIs.

• Growing desire for efficiency given current economic challenges.

• More centralized government focused approached internationally.

• Germany’s Industry 4.0

• China 2030 agenda

Cloud Software

• Microsoft Azure and Amazon Web Services (AWS) big players.

• Software on cloud called Software as a Service (SaaS).

• Major shift in the last 4 years from user managed software to SaaS.

• IT department reductions.

• Data backed up on servers around the globe. No local event can lose data.

• Software accessible by software provider and contractors.• Updates.

• Projects.

• Trouble shooting.

• Makes global enterprise software more viable.

• Data lake.

• Cost declining.

Digital Transformation Risks

• Transformation effort fails and resources are wasted.

• Failed transformation damages careers. (Successful transformations boost careers).

• Transformation can reveal overwhelming risk issues. Legal risk of gross negligence.

• Risk data reveals weaknesses that can be exploited.

• Cloud company political activism (Parler). Shut down servers.

Why do digital transformations fail?• Software does not actually work. Vaporware. (Easiest to

overcome).

• Software does work but users think it doesn’t.

• Inadequate funding.

• Those executing the transformation projects do not understand the data.

• Software too difficult to use and users are not trained or supported adequately.

• Give up before benefits are realized. Benefits are not realized right away. Might be less efficient at first. Software systems require use to get benefit. Software licensing contracts limit access to too few. Benefits not realized. Use stops.

• Stop at digitalization. Fail to transform systems. E.g. still require paper reports printed from databases.

• Users not incentivized to use the new platform. Work processes not transformed.

• End users demand customization. End up with an orphaned system.

• Enterprise software decisions can be very political (internal rivalries). Which means hidden agendas and bad decisions.

Features

• Facilitate risk studies, SIL calculations, SRS, Test Procedures, Operations and maintenance in one integrated platform.

• Single source of truth.

• Entire enterprise accessible (cloud). KPIs rolling up through organization.

• Cloning/copying/auto generation and templates across organization.

• Data importers.

• Mass data editors.

• Automated SIS configurations.

• Automated data validation.

• Efficiently find device/function/risk/event correlations.

• Efficiently evaluate MOCs, bypasses and failures.

• Integrate with control system data, CMMS, other for automated analytics.

• Data analytics.

Benefits/Business Case• Reduced risk! Truly move from I Think to I Know.

• Reduced costs!

• Improve business performance!

• Aligns responsibility with knowledge for effective decision making and peace of mind for executives.

• Good for careers.

• Enterprise software ensures best practice consistency across the organization improves performance.

• Efficient data manipulation allows for better predictions and decision making.

• Align financial and risk information access to make better spending decisions.

• Reduced cost and improved software performance. Less software licenses to manage with greater accessibility and performance.

• Highly compensated personnel improve risk, plant performance and financial performance instead of entering or looking for data.

• Accrue knowledge. The more it is used the better it becomes.

• More effective allocation of resources. Balance available information between financial and risk.

• Retain and attract key personnel. Work brings greater value and recognition and satisfaction.

• Increase asset value of facilities.

Where will we be in 20 years?

a) Like most other businesses that use integrated data platforms?

a) Still using online documents and isolated mini-tools.

It is good, it is necessary, and it is coming.