Digital Transformation Of Process And Functional Safety

Digital Transformation of Process andFunctional SafetyDavid Hansen, CFSE – ISA Houston– SIS SILverstonedhansen@sissilverstone.com281-701-6476

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DefinitionsDigitization Convert analog information into digital. E.g. scanningpaper documentsDigitalization 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 Oriented - ShoppingInternal DataOther purchasesReviewsReturnsDataModel numberViewsObject Class:Defense Attack RobotMark I (DAR)PriceNumber soldObject Class:shopperPurchased DataPurchasersPoliticsReviewsFriends and familyProfile of likely customersOccupationPetsPurchaseObject:DAR 18709ReviewObject:BillLikes and dislikesDAR is great! Took over asmall country with its help!PurchaseObject:DAR 18710ReviewObject:JillDAR is terrible! It killed mycat!Machine Learning Data Analytics Recommendation: Market to dictators, avoid cat owners.

Object Oriented – Functional SafetyObject Class:HAZOP/LOPA riskscenariosObject Class:IndependentProtection LayerObject Class:DeviceKey PerformanceIndicators (KPIs)Event bject:Process UnitsObject:Process EquipmentObject:Tower Overflow tocompressorScenarioObject:Tower flood nction SIF-101Compressor onsObject:XS-145Object:SIF-129Tower feed S/DOther Data ConnectionsFinancial et Management SystemsProcess SimulatorsMaintenance SystemsObject:PSV-134Data Analytics Recommendation: ACME Model 146 level transmitters are causing significant elevated enterprise risks.Analytics Systems

Data Analytics/Machine Learning Digitalization data overload. Need automated functionality to fully benefit. Machine Learning looks for patterns.Theoretical CasesProcessSafety1. Analytics discovers that elevated risks from seeminglyrandom failures from different types of transmittersare not random. Analytics from users and vendorsdetermine that a specific capacitor type is failing in hotweather conditions.2. Analytics automatically discover outlier risk rankingsfor similar scenarios across the organization. Either toomany resources are being allocated or risks are tooelevated.PersonnelLocation andWeatherDevicesData LakeMaintenanceAssetManagement

Digital Transformation is here! How we make money Video game industryPublishing (Youtube)InvestingOnlyfans 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 GodsOne portal to access all your information from any deviceanywhere.

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 variousinitiatives. Perception that they are already safe. Ignorance is bliss. Hidden risks can be revealed bysoftware platforms. Have already invested in existing isolated tools.

Digital Transformation is Coming Most major operating companies doing something: From voicing interest toTiny budgets toSignificant budgets and software evaluations toAmbitious 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 economicchallenges. More centralized government focused approachedinternationally. Germany’s Industry 4.0China 2030 agendaData Lake

Cloud Software Microsoft Azure and Amazon Web Services (AWS) bigplayers. Software on cloud called Software as a Service (SaaS). Major shift in the last 4 years from user managedsoftware to SaaS. IT department reductions. Data backed up on servers around the globe. No local event canlose 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. (Successfultransformations 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 downservers.

Why do digital transformations fail? Software does not actually work. Vaporware. (Easiest toovercome). Software does work but users think it doesn’t. Inadequate funding. Those executing the transformation projects do notunderstand the data. Software too difficult to use and users are not trained orsupported adequately. Give up before benefits are realized. Benefits are notrealized right away. Might be less efficient at first. Softwaresystems require use to get benefit. Software licensingcontracts limit access to too few. Benefits not realized. Usestops. Stop at digitalization. Fail to transform systems. E.g. stillrequire paper reports printed from databases. Users not incentivized to use the new platform. Workprocesses not transformed. End users demand customization. End up with an orphanedsystem. Enterprise software decisions can be very political (internalrivalries). 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 throughorganization. Cloning/copying/auto generation and templates acrossorganization. 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 forautomated 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 andpeace of mind for executives. Good for careers. Enterprise software ensures best practice consistency across theorganization improves performance. Efficient data manipulation allows for better predictions and decisionmaking. Align financial and risk information access to make better spendingdecisions. Reduced cost and improved software performance. Less softwarelicenses to manage with greater accessibility and performance. Highly compensated personnel improve risk, plant performance andfinancial 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 informationbetween financial and risk. Retain and attract key personnel. Work brings greater value andrecognition and satisfaction. Increase asset value of facilities.

Where will we be in 20 years?a) Like most other businesses that useintegrated data platforms?a) Still using online documents and isolatedmini-tools.It is good, it is necessary, and it is coming.

Object Class: Independent Protection Layer Object: Safety Instrumented Function SIF-101 Compressor S/D Object: SIF-129 Tower feed S/D Event Data Diagnostics Bypasses Failures Incidences Activations Object Oriented - Functional Safety Object: PSV-134 Tower Object: LT-101 Object Class: Device Object: XS-145 Object: XV-137 Object: PSV-134 Object .