digitalisation @ kvaerner adapting to a new landscape · in the “kvaerner” menu digitalisation...

Digitalisation @ Kvaerner –

adapting to a new landscapeJan 2020

Kvaerner at

a glance

2

© Kvaerner 2020

in the “Kvaerner” menu

The Jackets yard at Verdal

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© Kvaerner 2020


Sverdrup ULQ being built at Stord

© Kvaerner 2020


Njord platform retrofit

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© Kvaerner 2020


Tow-out of the Hebron platform

© Kvaerner 2020


The new landscape

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© Kvaerner 2020


The core NCS market is changing…

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Johan Sverdrup phase 2

Johan Castberg NOAKAValhall Flank West

© Kvaerner 2020


…driving expansion in other market segments

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Modifications

Decommissioning

Marine operations

Offshore wind

© Kvaerner 2020


Technology developments afford new opportunities

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Big Data

Internet of Things

Cloud computing

Artificial Intelligence Augmented reality

Advanced Robotics

© Kvaerner 2020


Core beliefs about digital EPCI

How digital will shape EPCI Implications for Kvaerner

The digital twin will be the central assetBuild capability to interact with any Digital Twin, including

interaction with our Yard Digital Twins1

The value chain will be digitally integratedBuild solutions around industry standards for seamless

information exchange2

All physical objects will be sensorisedDevelop Yard Digital Twin, using the Cognite Data Platform,

and a underlying multi-vendor sensor architecture3

The workforce will be digital and mobileDevelop capability to deliver digital tool suite for all roles,

and make tool set available to hired-ins, suppliers, partners4

Analytics will drive efficiencyMake data available across enterprise, build data-driven

culture, with analytics capabilities5

Automation will be prevalentInvest selectively to increase productivity, and integrate data

from new assets into Yard Digital Twin6

© Kvaerner 2020


The digital twin will become a lifecycle asset

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…with Kvaerner using the twin during the EPC phase

© Kvaerner 2020


..which will also interact with the Yard Digital Twin

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Tides, water temp and seabed conditions

Dock water depth

Real-time logistics tracking

Build method simulation

Real-time progress tracking

Materials tracking

Warehouse management

Marine operations planning

Area planning & ground conditions

Lift planning

Shift and rotation management

Paint hall temperature

Quay capacity planning

Assets location and condition

Tools & equipment tracking

Vehicle tracking and maintenance

Crane collision avoidance

Perimeter security monitoring

Scaffolding inspection

High-voltage power mgmt

© Kvaerner 2020


The combination of the Product Digital Twin and the

Yard Digital Twin will afford new execution capabilities

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Real-time progress tracking

Detailed build method simulation, area and capacity planning

Digital change impact analysis

Real-time preventive HSSE monitoring

Analytics-based resource optimalisation

Real-time information available to allin 3D twin viewers on mobile devices

© Kvaerner 2020


Yard Digital Twin viewer

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Available for Stord and Verdal yards

Detailed 3D models of assets, with clickable objects with operational documentation and certificates

Layers– Area plans, coupled to schedule– Ground pressure limits– Bollards

Live sensor data– Position data for assets– Power and gas consumption– Temperatures

© Kvaerner 2020


The EPC Information Worker – a new capability

Massive computing power Algorithms Very large data sets

© Kvaerner 2020


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© Kvaerner 2020


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The process of

digitalisation

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© Kvaerner 2020


Getting the process going

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Boarddirective

Conductanalysis

Managementownership

Establishimplementation

organisation

Prioritisationimplementation,

evaluation

Landscape overview

Identify initiatives

Cost/benefit analysis

Sensitivity to

project pipeline

Responsible EVP

Steering group

with executive mgmt

Programme manager

Business owners

IT organisation

Reference groups

DevOps development process

Frequent releases

Monthly steering group meetings

Annual funding cycle

Project funding when appropriate

© Kvaerner 2020


Digitalisation roadmap, version 1.8

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DigitalProcurement

Digital Project Management

Digital Yard

Robotics

Automated Engineering

Digital Lifecycle Information

AutomatedProject Setup

Jackets

model

integration

Jackets

auto report

generation

Automated

jackets design

Auto fabrication

engineering

Auto

scaffolding

design

B2B

collaboration

platform

Next-generation

MIPS

Project

execution

control

Supplier

portal

Remote

inspections

Yard

digital twin

Connected

yard (IoT)

Mobile

construction

workforce

Visual

construction

planning

Work force

management

Yard robotisation

team

High-priority

robotics

investments

Data

warehouse

platform

EPC

Dashboards

Analytics for

decision support

Automated

project setup

HSSEQ app /

Synergi

Constructability

Management

system

1.1

2.1 2.2 2.3 2.4 2.6

3.1 3.2 3.3

4.2 4.3

5.1 5.2 5.3 5.4 5.5 5.6

6.1 6.2

7.1 7.2 7.3

2.7

7.4

R3R3

R4

R 2

R2

R 2

R3

R1 R2

R1

Machine learning

applications for EPC

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© Kvaerner 2020


Three machine learning applications

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Jacket design Scaffolding design Spool delay prediction

V3 available V2 released Prototype

© Kvaerner 2020


Bits and pieces from the toolbox

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Neural networksUsing a set of training inputs and their known

desired outputs, adjust the coefficients in a

network of equations to maximise hit rate, and

then apply the network on new data sets.

Genetic algorithmsModel the problem as a vector of values, and

create a population of individs with semi-random

parameter values. Create new generation of

individs with better parameter values through

cross-breding and mutation

min ∑𝑊𝑥𝑢𝑛𝑑𝑒𝑟 𝐴𝑥 ≤ 𝑏

Linear optimalisationDefine a quantity to be minimised or maximised,

modelled as a sum of linear equations with

constraints. For non-linear contraints, apply

allowable transformations

Rules engineDefine how to extract relevant information from the

data to be processes. Define rules using an

appropriate syntax, and use rules engine to apply

rules to identify if and how to change the data.

Cloud-based computeAzure Batch – based architecture for

asynchrounous job execution, running

appropriately sized VMs. Containerisation next.

Data warehouseContains data from Kvaerner’s ERP system,

currently at ~108 lines

© Kvaerner 2020


Jackets design optimalisation

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Technologies

Capabilities

Benefits

• Static and dynamic analyses

• Elevation and section optimalisation

• Brace addition and deletion

• Constructability rules taken into account

• User-tunable optimisation criteria

• Input parameter validation, report generation

• Rapid concept development

• Weight and construction optimisation

© Kvaerner 2020


Designs vary, but have patterns

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© Kvaerner 2020


How to design and build a Jacket

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Input

Water depth

Soil conditions

Wave model

Topsides weight & CG envelope

Topsides interface

Seabed interface

Standards & regulations

Detailed3D model

AutoCAD3rd party sw + add-ons

Analysis

Sesam3rd party software

In-place

Fatigue

Seabed

Ship collision

Transport

Launch/lift

Method and materials

MIPSCustom application

Materials

Logistics

Work packages

Completion

Commissioning

Output

Analyses results

Reports & docs

Detailed3D model

Material lists

Workpackages

Build method

CNC files

© Kvaerner 2020


Jacket design topics

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Brace placement Elevation location Elevation brace pattern

Joint optimalisation Row bracing patterns Global optimalisation

© Kvaerner 2020


The claim

Use Algorithms and Massive Computing Power

to

Generate and Analyse various Designs,

to

arrive at a Viable Solution quickly,

optimised for Weight and/or Cost and/or Build time

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© Kvaerner 2020


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D(i)

T(i)

H1 H2 H3 D1 D2 D3 D4 D5 D6 D7 D8 D9 D10 D11 D12 D13 D14 T1 T2 T3 T4 T5 T6 T7 T8 T9 T10 T11 T12 T13 T14

Height 1

Height 2

Height 3

Diameter 2

Horizontal distance

W

Diameter 1

...

Model the problem

The complete model will have several thousand parameters

© Kvaerner 2020


Add constraints and rules

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All utilisation factors must be < 1, and ideally around 0.85

All angles must be > 40 degrees

Force on piles must lie between 35 and 80 MN

Member diameter must be > 16 * wall thickness

Brace diameter must be < 0.95 * leg diameter

Braces coming into a leg should be separated by 100 mm

Leg diameters increase in 100mm steps

Bracing diameters increase in 10 mm steps

Wal thickness increase in 5 mm steps

Cones must be placed beneath elevations

Leg can diameter must equal diameter of leg above

Inside diameter for cans on braces must match inside diameter of braces

Bottom leg sections must widen to increase buoyancy

Legs should be splayed to allow pile insertion

Find a quantitative fitness measure of any given design

© Kvaerner 2020


Run and tune a suitable algorithm

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Run analysis and evaluate results

Rank the results and select winners

Establish the initial population

Adjust the parameters in a smart way

Breed the next generation

© Kvaerner 2020


Generatevariations

Evaluate/guide/refine

Target solution architecture

Water depth

Soil conditions

Wave model

Topsides weight & CG envelope

Topsides interface

Seabed interface

Input

Standards & regulations

Analysis

Sesam3rd party software

Method and materials

MIPSCustom application

Detailed3D model

AutoCAD3rd party sw + add-ons

Knowledge base Templates Method generator

Analyses results

Reports & docs

Detailed3D model

Material lists

Work packages

Build method

Output

CNC files

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© Kvaerner 2020


Does it work?

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© Kvaerner 2020


• Provably optimal design

• Build around general exclusion volumes

• Reach specified work points

• Code compliant design

• Provides precise quantities and weights

• Integrated with 3D CAD application

Scaffolding design optimalisation

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Technologies

Capabilities

Benefits • Optimal design, with precise quantities

• Design permanent and dynamic portions

• Scaffolding as direct discipline

min ∑𝑊𝑥𝑢𝑛𝑑𝑒𝑟 𝐴𝑥 ≤ 𝑏

© Kvaerner 2020


Njord scaffolding

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© Kvaerner 2020


User interface integrated in 3D CAD application

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© Kvaerner 2020


Efficiency impact

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Significantly reduces the time required to

model scaffolding

Improved material management and

resource planning

Work process modified to include permanent

scaffolding, reducing tear-down and rebuild

effort

Fewer modifications reduces risk

© Kvaerner 2020


• Predict prefab delay for individual

spools and pipe supports

• Timeline analysis

• Data available through dashboard

Spool delay prediction

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Technologies

Capabilities

Benefits • Prioritise effort to maximise flow

• Generate data for root-cause analysis

• Include impact in tendering & design

© Kvaerner 2020


It’s about applied statistics

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Regression measures

Actual vs. predicted delay Underlying drivers

Joint probability distributions

© Kvaerner 2020


Demonstration

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Mobile Construction Workforce

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© Kvaerner 2020


Mobile Construction Workforce – initial steps

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Initial design ideas established though global innovation contest in Cognizant

Kvaerner awarded Cognizant 9 week study to develop a design concept for operators and foremen using mobile devices

Initial yard walks and workshop conducted at Stord and Verdal Yards over a two week period

Extensive involvement from selected foremen and operators from structural, piping and EIT disciplines

© Kvaerner 2020


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© Kvaerner 2020


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© Kvaerner 2020


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© Kvaerner 2020


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© Kvaerner 2020


Clickable wireframe prototype

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Wireframes for 20 use cases

approved by Kvaerner

stakeholders, including foremen

& operators at Stord and Verdal

Shown extensively throughout

organisation

Deliverables for 14 use cases

selected for initial

implementation

© Kvaerner 2020


Implementation effort

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9 week analysis effort

27 week implementation for 14

use cases

Multi-location implementation

team On-site team for product

development, requirements

definition and user interaction

Near-shore software factory

© Kvaerner 2020


The result – the WeBuild app

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App in production for 300+ users, to be

rolled out to entire blue-collar work force Includes support for hired-ins

Multi-language support

Foreman role: Work order management,

material management, team management

and collaboration

Operator role: Presence, fully fledged

object/operations lists, procedures, weld

reporting, time capture, collaboration

features

Constructability

engine

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© Kvaerner 2020


The transition from design to fabrication is key

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FEEDFabricationengineering

Designengineering

Verify completeness and data quality

Add objects and data needed for construction

Check constructability

Prepare fabrication data

Create job cards

Prefab Installation ...

Turn system design into physical design

Determine overall geometry

Ensure compliance to operational and safety requirements

Specify materials, welds, etc.

© Kvaerner 2020


Minimum distance from weld to obstruction

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Minimum distance from weld

to obstruction is 300mm

Model shows DN700mm pipe

with 188mm distance from

weld to pipe support

© Kvaerner 2020


Minimum stub lengths

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Stubs must have a

minimum length as a

function of pipe diamter

Model shows a drain box

stub which is shorter

than prescribed

© Kvaerner 2020


Venting of high points, drain for low points

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All line high points must

have venting, to enable

gas escape for testing

Similarly, all low points

must have drains

Model shows line with

no venting at high point

S.E.Solberg 23.01.2020

© Kvaerner 2020


Equal test pressure for welded lines

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Lines welded together must

have equal test pressures

Model shows to lines with

45 bar and 78 bar test

pressures, respectively

S.E.Solberg 23.01.2020

Additional slides

70

© Kvaerner 2020


Required platform capabilities in the digital landscape

Landscape characteristica Implications for Kvaerner

The set of business partners, i.e. digital actors will vary across projects, markets, and over time

Implement required cloud-based security features,

directory services and publicly exposed APIs to enable

collaboration with a changing set of actors1

All market-leading cloud platforms will be represented in the landscape

Base architecture on loosely coupled (micro)services, with

common authentication and authorisation architecture 2

The technical standards for information exchange will vary across actors, and evolve over time

Architect multi-channel information exchange capability,

supporting industry-standard technologies3

The information models for information exchange will evolve over time

Use versioned schemas for information exchange4

The application portfolios will evolve over time, moving to cloud-based delivery, both in-tenant and SaaS

SaaS where appropriate, buy-before-build, cloud-first,

micro-services architecture, cloud migration of on-

premise portfolio based on lifecycle considerations5

The digital landscape will create new roles and business opportunities

Use third-party SaaS to build capabilities, and identify

digital business opportunities based on own strengths6

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© Kvaerner 2020


Some notes on DevOps

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Code qualitySolution architectureTest-driven coding

CompletenessDocumentation

Test coverageTest data

App distributionCommunication

© Kvaerner 2020


Copyright

Copyright of all published material including photographs, drawings and images in this document remains vested in Kvaerner and third party contributors as appropriate.

Accordingly, neither the whole nor any part of this document shall be reproduced in any form nor used in any manner without express prior permission and applicable

acknowledgements. No trademark, copyright or other notice shall be altered or removed from any reproduction.

Disclaimer

This Presentation includes and is based, inter alia, on forward-looking information and statements that are subject to risks and uncertainties that could cause actual results to

differ. These statements and this Presentation are based on current expectations, estimates and projections about global economic conditions, the economic conditions of the

regions and industries that are major markets for Kværner ASA and Kværner ASA’s (including subsidiaries and affiliates) lines of business. These expectations, estimates and

projections are generally identifiable by statements containing words such as “expects”, “believes”, “estimates” or similar expressions. Important factors that could cause actual

results to differ materially from those expectations include, among others, economic and market conditions in the geographic areas and industries that are or will be major markets

for Kvaerner’s businesses, oil prices, market acceptance of new products and services, changes in governmental regulations, interest rates, fluctuations in currency exchange

rates and such other factors as may be discussed from time to time in the Presentation. Although Kværner ASA believes that its expectations and the Presentation are based

upon reasonable assumptions, it can give no assurance that those expectations will be achieved or that the actual results will be as set out in the Presentation. Kværner ASA is

making no representation or warranty, expressed or implied, as to the accuracy, reliability or completeness of the Presentation, and neither Kværner ASA nor any of its directors,

officers or employees will have any liability to you or any other persons resulting from your use.

Copyright and disclaimer

Copyright

Copyright of all published material including photographs, drawings and images in this document remains vested in Kvaerner and third party contributors as appropriate.

Accordingly, neither the whole nor any part of this document shall be reproduced in any form nor used in any manner without express prior permission and applicable

acknowledgements. No trademark, copyright or other notice shall be altered or removed from any reproduction.

Disclaimer

This Presentation includes and is based, inter alia, on forward-looking information and statements that are subject to risks and uncertainties that could cause actual results to

differ. These statements and this Presentation are based on current expectations, estimates and projections about global economic conditions, the economic conditions of the

regions and industries that are major markets for Kværner ASA and Kværner ASA’s (including subsidiaries and affiliates) lines of business. These expectations, estimates and

projections are generally identifiable by statements containing words such as “expects”, “believes”, “estimates” or similar expressions. Important factors that could cause actual

results to differ materially from those expectations include, among others, economic and market conditions in the geographic areas and industries that are or will be major markets

for Kvaerner’s businesses, oil prices, market acceptance of new products and services, changes in governmental regulations, interest rates, fluctuations in currency exchange

rates and such other factors as may be discussed from time to time in the Presentation. Although Kværner ASA believes that its expectations and the Presentation are based

upon reasonable assumptions, it can give no assurance that those expectations will be achieved or that the actual results will be as set out in the Presentation. Kværner ASA is

making no representation or warranty, expressed or implied, as to the accuracy, reliability or completeness of the Presentation, and neither Kværner ASA nor any of its directors,

officers or employees will have any liability to you or any other persons resulting from your use.

Copyright and disclaimer

73

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