digital transformation: the paperless factoryinfo.tcs.com/rs/120-ptn-868/images/paperless...

Digital Transformation: The paperless factory

Valentijn de Leeuw Vice President

ARC Advisory Group [email protected] AIOTI

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Content

ARC Advisory Group Digital Transformation: Smart Manufacturing and Industrial IoT 1. Paperless design, engineering, compliance and asset management 2. Paperless manufacturing 3. Paperless supply chains Outlook and recommendations


About ARC Advisory Group

Global Technology Strategy Consultancy § Domains: Industrial Design and Operations § Technologies: Automation, Instrumentation, IT, Industrial IoT (IIoT) § Typicals:

•  Market size and trends •  Best Practices, •  Benchmarking, Strategy •  IIoT Reports, Studies, Blogs, •  Speaking engagements


WHAT ARE WE TALKING ABOUT ???


vo•cab•u•la•ry (vō-kăbˈyə-lĕrˌē)

• Smart Manufacturing § Advanced Manufacturing: Advances in the physical and chemical processes

•  Modular production •  Additive manufacturing, advanced forming •  …

§ Smart Manufacturing Technologies: Digital Transformation •  Industrial Internet of Things (IIoT, including Cloud) •  IT and Automation based technologies, e.g analytics •  …

• Smart Manufacturing Initiatives § High Value Manufacturing Catapult §  Industrie 4.0 § Smart Manufacturing Leadership Coalition, etc.


Smart Manufacturing and Industrial IoT

A WINNING STRATEGY ?


Smart manufacturing or Industrial IoT: A strategy for growth?

• Strategy for growth? • Hype? • Miss the train?


Manufacturing growth and competitiveness

Manufacturing § Resilience § Competitiveness § Growth

Are correlated with a High degree of § Technology intensity § Technology/manufacturing

complexity § Quality

DE

Complexity index 2010 versus 1995

SE UK

FR IT

ES

Impacted by Smart Manufacturing


Smart Manufacturing and Industrial IoT

THREE DOMAINS


Digital operations, asset lifecycle and supply chain management

RemoteMonitoringConnectedServices

SmartComponents

Sales

SupplyChain

Manu-

facturing

Business

Ops

Predic=veMaintenance

SmartProduct&ProcessDesign

SmartLogis=cs

ConnectedProduc=onAssets

Status,HistoryofProducts

BusinessProcessExecu=on

ConnectedProducts

AdvancedAnaly=cs

Andmanymore…

ConnectedSCON


1. LIFE CYCLE


Model for Major ALM (or PLM) Processes

Design & Build Operate & Maintain

Portfolio Mgt.

Plan Design Procure Build Operate Maintain Re=re&RecyclePlan Design Procure Build Operate Maintain Re=re&Recycle

Project Performance Management (PPM)

Asset Performance Management (APM)

Project PerformanceManagement

(PPM)

Asset PerformanceManagement

(APM)

Asset & ProjectPortfolio

Management(APPM)

Handover

ModificationRequestsFunded

Projects

New Facility

Requests


Vision for Computer Integrated Engineering and Production

Dr. Thomas Tauchnitz, Sanofi Aventis, 2005 § Single repository for all engineering disciplines from front-end through operations and

maintenance §  Integrated compliance management § Manufacturing Operations Management and control systems synched with repository § Generic, modular designs to maximise reuse

PLM suites for discrete industries are far ahead in cross-lifecycle integration


Software is available for all functions along the life cycle

Challenges are related to synchronization among systems, applications and organizations

Owner – Operator

Operations/ Maintenance

(Registration) Qualification

Engineering/ Documentation (Construction/ Commissioning)

Process Design /

Documentation

Contractors Warranty Qualification Engineering/ (Construction) /

Engineering / Asset Management

3D Equipment / Plant design / OTS

Automation, Instrumentation, MPC, RTO

LIMS / PAT

Innovation Management / Project Management / Enterprise Asset Management / Portfolio Management / Risk & Compliance

Process Simulation

Other MOM functions, HSE

R&D

Process Simulation

Equipment Design

Process Synthesis

Control methods

Process Analytics


The reality: Asset Information Erosion

• Asset information is generally spread over applications, data bases and paper files

• Processes do not emphasize the synchronization of these sources

• Result is that information becomes inconsistent

• When external service providers are involved information becomes incomplete and more inconsistent

•  Information is rarely handed over completely and electronically

• The cost of poor asset information is over 4% of CAPEX (NIST)

EPC$

Integrated$Approach$

O&O$

FEED$

Engineering$

Construc9on$

Commissioning$

Maintenance$

Redesign$

Shutdown$

Asset$Data$Quality$

Plant$Asset$Lifecycle$

Information Handover

Legal Requirement Level

Information Losses Paper-based Handover

O&O

EPC

EPC + O&O

Asset Information Quality and Quantity During Handover


World class producers have low cost and high availability

Maintenance has an impact on reliability (McKinsey, 2009) § World class oil and gas producers have 95-98% availability § Make right decisions on savings § Execute plans and processes flawlessly § Can improve availability with several percent while reducing cost 25-30%

30 McKinsey on Oil & Gas :LQWHU��

operators, planners, and well services staff,

run frequent well reviews to analyze performance

gaps and identify ways of restoring and optimiz-

ing volume. The well services function ensures that

operators apply expert knowledge in well

interventions, use prior learnings and optimize

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Superior contractor and supplier management.

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management system in place and hold frequent

dialogues with suppliers. They know how to

set incentives so that the contractor optimizes

value for the operator. Thus a well service

provider is not rewarded according to the volume

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programs with select companies. They

develop an in-depth understanding of supplier

cost structures and continuously squeeze out

waste while allowing margins appropriate to the

current market environment.

Cost-optimization management.�:RUOG�FODVV�

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costs to reduce, thus avoiding a downward

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which illustrates the vicious circle that many

operators can go into when reducing maintenance

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Exhibit 3

False economies

Short-term cost savings must be balanced against long-term performance.

Maintenance cost gap,% to top quartile

Increased focus on preventive maintenance brings slow improve-ment in reliability

Falling reliability forces operator to spend more on reactive maintenance

Operator cuts cost by eliminating planned maintenance activities

Production efficiency, % of production potential

Web 2010MoOG Upstream operationsExhibit 3 of 3Glance: Short-term cost savings must be balanced against long-term performance.Exhibit title: False economies

50

45

40

35

060 65 70 75 80 85 90 95 100

1998

1999

2000

2001

30

20

15

10

5

25

Target area

Producing assets Specific producing asset, over time

Precisely what ISO 55000 defines

§ Good practices in defining asset management system

§ Quality of governance is key


Implementation examples Dr. Tauchnitz of Sanofi implemented his vision

§ Developed engineering modules (multi-year effort)

§  Internal collaboration required adjustment to processes and mutual trust

§ Developed with Siemens first one-way then bidirectional interface with PCS7, from which NE150 was derived

Christoph Jauslin of Novartis implemented paperless integrated engineering globally

§ Paperless engineering, handover, operations and maintenance

§ Developed e-compliance, implemented by Siemens in COMOS

Monitoring & controlling

High-level risk

assessment Review & approval

Test & confirmation

Review & approval

Definition & setup

Review & approval

User requirements

Detail design

Performance qualification

Implementation

Validation master plan

Validation report

Quality, project & test planning

Quality report & handover

Installation qualification

Functional design Operational qualification

Creation & release

Review & approval

COMOS Provides Project and Workflow Support for Integrated Asset Information and Compliance management


Expected benefits §  Manage information and processes

for compliance §  Guarantee safe operation,

maintenance and change with up to date “as built” information

§  Single version of the truth §  Eliminate non-value adding work §  Reduce search time §  Stream-line work processes

•  Speed up management of change §  Improve collaboration §  Reducing engineering and contractor

cost OR improved quality

Unexpected benefits §  Maintenance quality reduces cost in

maintenance and production §  Cost of compliance constant despite

more complex regulation §  Reduced on-boarding time §  Increased % as-built documentation

Adding documents to the equation: KANEKA Belgium

Plant Environment Project

Environment

Changes

Corrective Changes

Documents

Assets

Standards and Specifications

Archive

Controlled Copies

Approved Revision

Controlled Copies

Approved Revision

SAP Intrane

t Plant 4D e-plan

CAD

e-mail

Solution


Asset information integrity as key enabler

Design & Build Operate & Maintain

Portfolio Mgt.

Plan Design Procure Build Operate Maintain Re=re&RecyclePlan Design Procure Build Operate Maintain Re=re&Recycle

Project Performance Management (PPM)

Asset Performance Management (APM)

Project PerformanceManagement

(PPM)

Asset PerformanceManagement

(APM)

Asset & ProjectPortfolio

Management(APPM)

Handover

ModificationRequestsFunded

Projects

New Facility

Requests

AssetLifecycleInforma2onManagement


2. MANUFACTURING


The Emerging Smart Production Environment

New or Changing … § Software: Analytics,

APS, MES/MOM, EAM/CMMS, LIMS, PAM, Security, etc.

§ Mobility and enhanced worker connectivity

§ Remote services; Product ‘as-a-Service’

§ Smart sensors, assets, network connectivity, cloud

§  Increased variety and changeovers

… All along with traditional automation and enterprise systems Smart

Products

Connected Products

Smart Metrology

3rd Party Services

Plant Systems and

Assets

Enterprise Systems

Connected Enterprise

Flexible Worker Schedules

Location/Nav Services

Video Presence (Expert Help)

Augmented Reality

Smart Tools

Connected Worker

Collaboration

Self-Planning Systems

Smart Components

Smart Logistics Smart Carriers

RFID

Smart Warehouse

IIoT Smart Module

Remote Monitoring &

Services

Connectivity Platform

Advanced Analytics

Apps

Smart Machines

Connected Machine

Smart Containers

Advanced Analytics

Logistics Services

Connected Supply Chain

Value Chain

Smart Consumers


Modular equipment, units and lines Revolution in engineering, construction and production

• Bayer’sproduc=onunitinstalledatINVITE

(Fine)Chemicals,PolymersandPharmaceu=calsDockingamodularplant


Standards for functions and integration well-defined

Functions for Production, quality, inventory, maintenance ops

Integration content Paperless is feasible Missing:

§ Value chain interoperability

§ M&A

IIoT implications for MES § More generic

specifications § More real-time

instantiation

Level 4

Level 1

Level 2

Level 3

Business Planning & Logistics Plant Production Scheduling, Operational Management, etc

Manufacturing Operations Management Dispatching Production, Detailed Production Scheduling, Reliability Assurance, ...

Batch Control

Discrete, Packaging Control

Continuous Control 1 - Sensing the production process,

manipulating the production process

2 - Monitoring, supervisory control and automated control of the production process

3 - Work flow / recipe control to produce the desired end products. Maintaining records and optimizing the production process.

Time Frame Days, Shifts, hours, minutes, seconds

4 - Establishing the basic plant schedule - production, material use, delivery, and shipping. Determining inventory levels.

Time Frame Months, weeks, days

Level 0 0 - The actual production process

Level 5 Business Management

5 - Strategic level, long term business planning, Financial, HR .. Time Frame

Years, Quarters, Months, Weeks


Impact on Integration Standards

Implications for standards

§ Reference Architecture Industrie 4.0 investigates extension of the physical model of ISA-88 and ISA-95 standards

Enterprise

Site

Area

Produc=onUnit

MayContain1ormore

Produc=onLine

WorkCell

SpecifiedbyISA95

StorageZone

StorageModule

ProcessCell

Unit

SpecifiedbyISA88

BatchorCon2nuousOpera2ons

DiscreteOpera2ons

InventoryOpera2ons

Con2nuousOpera2ons

Unit

Workcenter

Workunit

(GenericOpera2ons)

ConnectedWorld

(Connected)Product

FieldDevice

EquipmentModule

ControlModule

MayContain

MayContain

ExtensionproposedbyRAMI4.0

ExtensionproposedbyRAMI4.0

Sta=on

ControlDevice


Fast, world-wide production visibility and support

•  SMLC:ALCOAOpera=onalIntelligence•  Globalreal-=mesmelterproduc=ondatawithreal-=meanaly=cs•  Internet

Source:GeoffWoods,ALCOA,livedemo,OSIsoZUC,2014


Impact on applications: IoT as MES add–on Optimizing Manufacturing with IoT at Intel

•  IoT solution in parallel with MES §  Flat architecture §  Processing at the ‘edge’ §  Controller connection to Cloud §  Storage, analytics and predictions

•  Complex partner network •  Case 1: predictive combined asset and

quality analytics: 9M$ benefits §  Reduce non-genuine off-spec (losses -25%) §  Predictive maintenance (cost -20%)

•  Two other cases with major benefits

•  Lessons for other sectors §  Incremental Industrial IoT application §  Large data streams from ubiquitous

sensing need large bandwidth §  Data selection at controller level §  Wide range of analytics applications

possible h^p://www.intel.com/content/www/us/en/internet-of-things/white-papers/industrial-op=mizing-manufacturing-with-iot-paper.html

Short-termgainspossiblebyincrementalsteps


3. SUPPLY CHAIN


Traditional Supply Chain • A

dapt

ive

Pro

duct

ion

§ Dem

and

pull

§ Mat

eria

l sup

ply

coul

d be

pro

vide

d vi

a S

CO

N

Source:Poe^er,NamurGeneralAssembly2013


Source:Poe

^er,N

amurGen

eralAssem

bly2013

Industrie 4.0: Cyber-physical systems, real-time operating networks • V

MI u

sing

cyb

er-p

hysi

cal

syst

ems

§ R

equi

res

real

-tim

e op

erat

ing

SC

ON

!


From MRPII to Advanced P&S

• Manufacturing agility and supply chain speed will cause

• High Supply Chain volatility

• Traditional supply chain management will be insufficient

• Can be damped with near real-time predictive analytics

Collaborative Forecasting

and Demand

Management

Supply &

Demand Balancing

Scheduling And

Capable to Promise

Rough Cut Capacity Planning

Distribution Requirements Planning

Sales and Operations Planning

Master Production Scheduling

Material Requirements Planning

Infinite Capacity Scheduling Available to

Promise

Statistical Forecasting


From MRPII to Advanced P&S and Analytics

Collaborative Forecasting

and Demand

Management

Supply &

Demand Balancing

Scheduling And

Capable to Promise

Rough Cut Capacity Planning

Distribution Requirements Planning

Sales and Operations Planning

Master Production Scheduling

Material Requirements Planning

Infinite Capacity Scheduling Available to

Promise

Statistical Forecasting

Towards Predictive Supply Chain Analytics

and Network Optimization

Volatility can be damped with near real-time predictive analytics


Emerging SM / IIoT Architecture – SC Analytics

PlantOpera=ons

CorporatePurchasingEngineering

XYZChemical XYZChemical XYZChemical

Enterprise

Maintenance

XYZChemical

Device buses

Production Management

Logic & Motion

Discrete ControlProcess Control

Infrastructure (Networks…)

Wireless

HMI / Workstations

Fieldbus

Application Specific

Appliances

Safety

XYZChemical

Client

3rdPar.es

Supplier

Physicalassetwithsensors,actuators

LocalIoTComputeandCommunicatemodule

SmartMachine

IoTSmartModule

EmergingOp=on:ConnectAssetsUsingNewTechnologies

NewIoTAnaly=csandApplica=ons

PurdueHierarchy

IIoTHierarchy


Shorten SCM implementation time dramatically • SMLC Testbed General Mills • Complex integrated solution

requirement § Each implementation

iteration takes years § Objective: reduce

application building and integration to a few months.


OUTLOOK AND RECOMMENDATIONS


Mastering the 4th Industrial Revolution: Davos 2016

Great opportunities §  Consumer opportunities §  Economic growth opportunities §  Job opportunities for the highly skilled §  Mobility without physical relocation §  Barriers for entry shrink (investment to compete digitally is small) §  Digital transformation can go hand in hand with sustainability

Great challenges §  Rising inequalities, shrinking middle class §  Privacy and cyber security §  Skills transformation (every job will have digital components) §  Low Investment/Savings ratio §  Lack of physical interaction between people


Davos 2016: All stakeholders must take responsibility and contribute to make digital transformation a success


It’s not just a matter of technology

In the end, it all comes down to people and values. We need to shape a future that works for all of us by putting people first and empowering them. Prof. Klaus Schab, Founder and Chairman of the World Economic Forum

Thank You. Formoreinforma=on,contacttheauthorat

[email protected]

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