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TEMP-0010-DOT-F - Verhaert Presentation

BIG DATA FOR CHEMICAL 4.0Business Implications

Gilles Vertongen – Innovation consultantZane Smilga – Innolab coordinator

gilles.vertongen@verhaert.com

15.02.2019

ESSENSCIA

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PREFACE BIG DATA LEADS TO BIG OPPORTUNITIES FOR CHEMICAL COMPANIES.…DO NOT START WITH DATA. START WITH VALUE & TARGETS FOR YOUR BUSINESSTo unlock the value of big data chemical companies need to realize that it is more than an incremental change in technology but a strategic transformation and disruption in competitive landscape. Chemical industry is lagging behind. It should catch up by taking use of the learning accumulated by other industries.

…APPLICATION DOMAINS AND KNOWLEDGE REQUIREMENTS WILL TELL YOU WHAT DATA YOU NEED…Big Data is changing the way chemical companies run operations, approach product development, supply chain management, HR and marketing. There are multiple options for data sources in each application domain. Smart selection of data sources and collection means is needed.

THINK BIG DATA, START WITH FIRST STEPS & MANAGE YOUR DATA MANAGEMENT RISKS UPFRONTThe volume, variety and velocity of data is generating massive amounts of information in real time about products, devices, supply chain, production, customers. The systems (to collect, store and analyze data) should span across the networks of related companies and their systems. Multiple technologies (e.g. cloud computing, edge computing, remote management software tools etc.) need to be in place. Chemical companies are extremely sensitive to potential cyberattacks.

Market evolution is not visible in IP landscape. “Big data” related technologies are not chemical industry specific.

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CONTENT

CHAPTER 1 CHEMICAL 4.0 - UNBEATABLE LOGICS FOR FUTURE TRANSFORMATION (slide 3)

CHAPTER 2: BIG DATA APPLICATIONS AND VALUE (slide 10)- Smart innovation and R&D- Smart marketing & supply chains- Operations: PRODUCTIVITY AND EFFICIENCY- Predictive maintenance

CHAPTER 3: BIG DATA WATCH OUT`s FOR IMPLEMENTATION (slide 17)

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CHEMICAL 4.0 UNBEATABLE LOGICS FOR FUTURE TRANSFORMATION “Industry 4.0 is no longer the technology of the future. It is the here and now. For the chemical sector, it is a way to secure their competitiveness.”/http://www.chemicalindustryjournal.co.uk/

CHAPTER 1:

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TRANSITION TOWARD FAVORABLE BUSINESS & OPERATING MODELS IN CHEMICAL

All manufacturers in chemical industry need to evaluate their existing processes and redefine their value propositions to survive and fit the future market evolution. In an increasingly cost-competitive market, no company in the chemicals sector can afford to lose opportunities to improve their cost and revenue position against their market peers.

• Cyclical market conditions

• Soaring cost of raw materials & labor

• Rising competition

• Changing customer preferences

• Slim profit margins

• Overproduction (due to

commoditization)

• Stringent environment and health

safety regulations

• Regional competitiveness (Europe, the

global leader until 2000, Asia-pacific

currently accounts for about 60% of the

global chemical revenue)

• Achieve operational efficiency &

productivity

• Enhance asset lifecycle

• Maximize resource utilization

• Shorter innovation cycles

• New revenue sources & business

models

• Better customer service

• Superior quality at optimal cost

• Reduced time-to-market

• Reduce risks

CHALLENGES FUTURE BENEFITS

INDUSTRY 4.0- Competitive edge- Prerequisite for investor funding

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A DIGITALLY CONNECTED ECOSYSTEM IN THE CHEMICAL MANUFACTURING

The goal of Industry 4.0 is to produce intelligent products using intelligent methods and processes.

• Digitalization of internal vertical value chain;

• Digitalization of horizontal partners along the supply chain;

• Enhancing product portfolio with digital functionalities and introducing innovative, databased services.

This is enabled through increased use of near-real-time data in the digital integration of value chains, seamless asset lifecycle information from plant concept to decommissioning, and business-to-plant production control.

https://ww2.frost.com/frost-perspectives/chemicals-40new-age-digital-manufacturing/http://www.chemicalindustryjournal.co.uk/industry-4-0-revolutionising-chemicals-industryhttps://www.smartindustry.com/articles/2018/industrie-4-0-what-does-it-mean-for-chemical-companies/

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INVESTMENTS OF CHEMICAL COMPANIES ~ 5% OF REVENUE PER ANNUM

Many industry 4.0 technologies are in place; full deployment remains limited.

• Chemical companies have started pilot programs across their operations;

• Technologies like cloud, robotics, artificial intelligence, mobility/wearables and cybersecurity lack widespread adoption;

• Some cyber-physical systems enabling the intelligent plant are mainstream in the process industry.

https://newsroom.accenture.com/news/digital-technologies-in-chemical-plant-operations-beginning-to-drive-profits-fueling-further-investments-accenture-research-finds.htm

Many chemical companies employ analytics based on first principles, empirical, and hybrid models. New data-driven analytics are emerging.

https://www.pwc.nl/nl/assets/documents/industry-4-0-building-the-digital-enterprise-chemicals.pdfhttps://www.smartindustry.com/articles/2018/industrie-4-0-what-does-it-mean-for-chemical-companies/

(Source: PWC survey, 2016)

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HIGH EXPECTATIONS OF COST SAVINGS, INCREASED REVENUE & EFFICIENCY GAINS

Industry 4.0 will likely impact the way chemicals companies operate and grow their businesses.

1. Change in costs / operations- Production excellence & productivity;- Linkages & transparency across the value

chain; - Improved forecasting and planning of

operations

2. Change in revenue generation Shift away from the pay-by-the-ton revenue model to provide value-added products and services to their customers.

The chemicals industry needs to act quickly to reap the benefits of Industry 4.0, yet build sound foundation by making myriad of make small moves.

https://www.smartindustry.com/articles/2018/industrie-4-0-what-does-it-mean-for-chemical-companies/https://www2.deloitte.com/insights/us/en/focus/industry-4-0/chemicals-industry-value-chain.htmlhttps://www.pwc.nl/nl/assets/documents/industry-4-0-building-the-digital-enterprise-chemicals.pdf

source: PWC survey report, 2016

EXPECTED BENEFITS FROM DIGITISATION OVER THE NEXT 5 YEARS (CHEMICAL INDUSTRY)

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ULTIMATE VISION – BIG DATA BASED INDUSTRY DISRUPTION

Digitization leading to chemical 4.0 can be fulfilled by three approaches that follow each other. The digital disruption opportunity is in digital business models.

1. TRANSPARENCY AND DIGITAL PROCESSES:

• Collecting and presenting operational data digitally.

2. DATA BASED OPERATING MODELS:

• End-to-end integration of plant design and engineering for the commissioning, operation, and maintenance;

• Constant optimization of processes (detect future outages, predictive maintenance, optimize centrally at all sites…);

• Simulation of alternative operational models;

• Reduction of operating costs: real time operational, well-supported decisions to increase performance and reduce operational costs.

https://new.siemens.com/global/en/markets/chemical-industry/digitalization.html

3. DIGITAL BUSINESS MODELS:

• Customer-centric business models (customization);

• Selling business outcomes instead of products;

• Delivering first-pass quality products or semi-finished goods instead of paints, coatings or reactive resin components.

Stefan Guertzgen, Senior Director; Chemicals, SAP, Walldorf, Germany

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START WITH TARGETS; BIG DATA IS ONLY AN ENABLER…

Transforming data into knowledge and actions is key to gain a competitive edge.

Data management and analysis are the key enablers.

Data

KnowledgeAction

Platform+

Machine learning

UX+

Decisiontheory

Measure+

Feedback

DigitalSupply chains

Smart supply chainSmart delivery

Digital factory

Yield increaseUptime increase

Energy savings

Digital services

New servicesNew business models

Benefits can be related to different business functions, applications, KPIs, business focus areas…

STEP 2: DEFINE WHAT KNOWLEDGE YOU REQUIRE FOR ACHIEVING YOUR GOALS. THIS WILL TELL YOU WHAT TYPE OF BIG DATA YOU NEED TO GENERATE AND HOW TO COLLECT, MANAGE IT..

STEP 1: START WITH THE GOAL. DEFINE WHAT VALUE (BENEFITS) YOU WOULD LIKE TO GAIN WITH BIG DATA;

Operational excellence

Predictive maintenance

Digital customer

experience

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CHEMICAL 4.0 APPLICATIONS AND VALUE“Industry 4.0 will likely impact the way chemicals companies operate and grow their businesses” / https://www2.deloitte.com/insights/us/en/focus/industry-4-0/chemicals-industry-value-chain.html/

CHAPTER 2:

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OPERATIONAL PAINS/GAINS TRIGGER CHEMICAL COMPANIES TO INVEST IN BIG DATA

Chemical company management team

What is the use rate of each unit?How optimizing network’s yields while best servicing demand?How to save energy?

Advanced analytics in OPEX and CAPEX

How can you anticipate delays in delivery times?

End-to-end supply chain integration

How to detect anomalies and predict their propagation through the network?

Predictive maintenance

How will the demand evolve in the next hours/days/weeks?How to integrate external factors (weather, market prices, …) into the demand forecast?

Commercial engines

How to better adapt to changing customer demand?

Digitization of customer demand

…

How can you better adapt your processes to changing quality grades?

Digital procurement tools

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OPPORTUNITIES STRETCH ACROSS THE ENTIRE CHEMICAL VALUE CHAIN

PRODUCTIVITY/RISK REDUCTION TARGETS

GROWTHTARGETS

1. SMART MANUFACTURING

2.SMART SUPPLY CHAIN 3. SMART INNOVATION 4. SMART MARKETING &

CUSTOMER SERVICE

Predictive maintenance

Energy management

Remote asset management

Safety improvement

Quality improvement

Planning optimization

Demand forecasting

Process monitoring

Safety management

Examples of benefitsSimulation in new product development

Analyzing profitability

Automate tasks, report performance levels, flag anomalies and generate alerts

Automated design of experiments Accelerated innovation cycles

New business models, revenue formulas

End-to-end supply chain integrationAdvanced analytics in OPEX

and CAPEX

Demand forecasting

Optimal price pointsInnovation cost reduction

Future customer requirements

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BIG DATA CAN DRIVE CHEMICAL INNOVATION AND R&D

1. Innovation risk management- Predict the outcome of that investment;- Enable experiments for systematic

optimization of formulations for performance and costs.

2. New innovation opportunities- Understand the chemical properties of

available materials;- Consider possible new combinations;- Virtual simulation (multiple trials of new

innovative chemical in small portions);- Understand design, characteristics and

reaction of new formulations.

3. Faster innovation cycles- Faster time to market;- Real-time intelligence.

4. Reduced innovation cost• More effective R&D (integrating lab data with

chemical databases and academic literature);• Automating design of experiments.• Cheap satellites and drones that gather data

about chemicals in the environment.

BASF hopes that digitalization in R&D will enable them to be the most innovative company in chemical industry/BASF Round Table, 2017/

http://www.luxresearchinc.com/news-and-events/press-releases/read/big-data-and-analytics-can-tame-rising-cost-chemical-rdBASF Round Table, 2017

CASE EXAMPLE

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BIG DATA WILL ENABLE SMART MARKETING & SUPPLY CHAINS

Digitally transform operations and enable “smart” supply chains and factories as well as new business models.

1. Cost optimization in Supply Chain Management

Data analysis of freight, raw material prices, procurement schedules, and storage costs, etc

2. Accuracy in go-2-market

Insight into product trends, demand, future customer requirements, and so on.

3. Optimal price point setting

Quick real time insights and price adjustment opportunities (based on the cost of raw materials, exchange rates, utility costs, competitors).

4. Demand forecasting

Accurate marketing and production decisions.

CASE EXAMPLE

“Digitalization dismantles the old partitions, allowing the supply chain to become a fully integrated ecosystem

transparent to all involved.” / Covestro/

https://pureinsights.covestro.com/digitalization-is-changing-everything-including-how-we-do-business/https://www.degruyter.com/downloadpdf/j/ci.2017.39.issue-3/ci-2017-0312/ci-2017-0312.pdf

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PRODUCTIVITY AND EFFICIENCY AND STOP FURTHER MARGIN PRESSURE

Operational excellence in chemical plants to the level that has not been possible before. Digital technologies such as advanced analytics, HPC and cognitive computing, chemicals companies have far wider and deeper insight than ever before, enabling more informed strategy decisions.

1. Optimizing the production process• Simulate, predict, and prescribe maintenance to

increase assets’ availability, • Optimize uptime, • Improve operational performance

2. Increasing production efficiency• Assessment and management of batch production

of multiple variants at any given time;• Efficient utilization of resources by allocating in

value-adding activities.

3. Reducing energy consumption and operational cost• Real-time monitoring;• Enhance asset life cycle;• Improve plant reliability.

https://www.digitalistmag.com/digital-supply-networks/2018/02/27/iot-machine-learning-boost-chemical-companies-to-next-level-05921363

“Using technology to increase operational efficiency could save $91,261 per chemical company employee, on average.

Accenture, 2018https://www.accenture.com/nl-en/insight-power-plant-operations

REDUCE ENERGY

REDUCE PRODUCTION COSTS

INCREASE CAPACITY/PLANT AVAILABLITY

IMPROVE YIELD

IMPROVE QUALITY

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TIGF CASE – EXPERIENCE WITH BIG DATA & OPEX OPTIMIZATION

COMPANY PROFILE: An operator of gas transmission network in France;a 5.000 km network –16% of the total French network;six compressor stationstwo sites for underground natural gas storage.

CHALLENGE: TIGF’ gas movement are planned on a daily basis according to in- and outflows predictions using outdated Excel macros• Manual integration of the data (network topology, consumption patterns, in- and

outflows of the gas in the network) • Calculation of each compressor use rate

SOLUTIONA data lake collecting data from sensors has been setup with and graph analysis + machine learning algorithm were applied

CASE EXAMPLETIGF aims at improving its compressor OPEX (mainly electricity and gas consumption)

OPERATIONAL GAINS:

Learning the output curve of each compressor using historical data has enabled the automatic selection of the right compressing mix for a specific demand.

Both transport and storage teams had access to a tool with the following functionalities:• Tuning parameter calculation. • Impact analysis in terms of costs and CO2 emissions• Maintenance operation simulation,• Impact analysis on tuning parameters• Automatic report generation • Identifying compressor output optimum.• Better fine tune compressor use rate depending on gas demand

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POWER OF PREDICTIVE MAINTENANCE THROUGH BIG DATA

Big Data can lean from real time asset monitoring to Predictive maintenance

1. Real time data: Asset status and performance, process parameters, product quality, production costs, storage capacity and inventory (telemetry), inbound/outbound logistics, workers’ safety, pairing products with services, and more.

2. One integrated system:- All aspects of the management, planning, operation and

maintenance, including plant documentation, are carried out in a single system;

- Any changes due to maintenance processes communicate to related processes

3. Generate new insights & instant alerts: - Sensors can automate tasks, report performance levels,

flag anomalies and generate alerts- New insights into business processes and performance- Predictive analytics to forecast problems

Predictive maintenance will prolong component service life, prevent unscheduled downtimes, and thus significantly increases plant availability. Bear in mind that it will require a combination of different data sources.

“Half of the companies sets uptime improvement as primary goal for implementing predictive maintenance 4.0”Predictive maintenance 4.0. PwC & Mainnovation. 2017.

“ Big data analytics can reduce breakdowns by as much as 26 percent and unscheduled downtime by as much as 23 percent.” Forbes, https://www.capgemini.com/2018/11/big-data-potential-to-eradicate-challenges-in-the-manufacturing-industry/

(1) Source: Predictive maintenance 4.0. PwC & Mainnovation. 2017.

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COMPANY PROFILEManufacturing services and assets management for 22 chemical companies based in Chemelot (The Nederlands).

PDM DEVELOPMENT• Centralization and standardization across customers cut of

maintenance costs by €50m• Increase of processes efficiency: cut of €50m• Increase of uptime (today): Downtime can amount up to €500k per

day in missed revenues, making maintenance costs of marginal significance

• Increase people and asset safeties: aging is big issue: with people retiring, predictive maintenance secures the assets

THE INITIAL APPROACH• One reliability engineer assigned (a project pilot)• Focus on one single filter as a critical piece of equipment• Installation of sensor on it, monitoring and built a predictive model• Prediction of filter failure reduction of downtime annual

savings of €60k (a fraction of the costs) • In two years seven models were developed, leading to €500k

uptime improvements for €200k costs.

THE ROLL OUT OF PREDICTIVE MAINTENANCE• Funding the scale up of the implementation of PdM. • Dedicated models and sensors for each type of equipment

SITECH CASE – EXPERIENCE WITH BIG DATA & PREDICTIVE MAITNENANCE

CASE EXAMPLE

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CHEMICAL 4.0 WATCH OUT`s FOR IMPLEMENTATION“In the chemicals industry, there is a certain degree of skepticism with regard to digital technologies…

https://www.smartindustry.com/articles/2018/industrie-4-0-what-does-it-mean-for-chemical-companies/

/

CHAPTER 3:

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In the chemicals industry, there is a certain degree of skepticism with regard to digital technologies. This is largely due to cyber threats that infringe enterprises’ intellectual property and plant network.

CAN YOU TRUST IT?# MANAGING CYBER RISK IS A CRITICAL COMPONENT

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CYBER ATTACKS: MOST RECOGNIZED RISK BY CHEMICAL COMPANIES

KEY RISKS RELATED TO CYBER SECURITY 1) Commercial risks

- Production loss and breach of customer supply contracts

- Potential threat to IP and commercial secrets

2) Environment, health and safety risks

E.g. cyber attacks on plant operations could present a threat to the security and health of employees and the wider public.

3) Operational reliability risks

E.g. cyber attacks can negatively impact production and availability of the facility. Chemical companies lack abilities to identify the cause of a breach monitor for breaches.

CHEMICAL COMPANIES’ ABILITIES TO IDENTIFY, HANDLE AND RESPOND TO THE THREATS ARE LIMITED OR LACKING AT ALL.

“Currently, only 42 percent can manage the financial risk due to a cyber security event targeting their plant operations, or minimize the disruption. Even less (39 percent) can identify the cause of a breach, and only a third (33 percent) are able to monitor for breaches.”

SOLUTION is about applying tools, standards and capabilities that will allow to react and intervene efficiency.

Source: Accenture’s “Digital Technology in Chemical Plant Operations” survey, 2018; https://newsroom.accenture.com/news/digital-technologies-in-chemical-plant-operations-beginning-to-drive-profits-fueling-further-investments-accenture-research-finds.htm

CASE EXAMPLES

In August, 2018 a petrochemical company with a plant in Saudi Arabia was hit by a new kind of cyber assault. The attack was not designed to simply destroy data or shut down the plant, investigators believe. It was meant to sabotage the firm’s operations and trigger an explosion.Computers crashed at sites including Sadara Chemical Company, a joint venture between the oil and chemical giants Saudi Aramco and Dow Chemical (Sadara).

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CAN YOU CONNECT IT?

# INTERCONNECTED DATA FLOWSChemical processes are highly complex and intermingled. They go beyond single enterprise.

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DATA ARCHITECTURE FOR THE ENTIRE VALUE CHAIN/NETWORK

CONNECTING DATA FLOWS OF A NETWORK OF COMPANIES

Safety considerations constrain supply-chain flexibility and create stringent requirements for security and process safety.

• Components in chemical processes are often produced by a network of companies;

• Components can be very toxic, making them difficult or impossible to transport safely (transported directly by pipeline from one company’s site to another’s).

CONNECTING A NETWORK OF SYSTEMS ALONG THE VALUE CHAIN

• Sensors, machines, workpieces, and IT systems are connected along the value chain beyond a single enterprise;

• The connected systems form cyber-physical systems that can interact with one another using standard Internet based protocols and analyse data.

The implementation challenges will be to resolve interface and architecture challenges and to successfully build outwards and beyond the boundaries of individual plants.

https://www.smartindustry.com/articles/2018/industrie-4-0-what-does-it-mean-for-chemical-companies/

http://www.cefic.org/Policy-Centre/

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CHEMICAL 4.0 BUSINESS IMPLCATIONS – KEY MESSAGES

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KEY MESSAGES

• Industrial internet of things (iiot) and digital technologies are a boon for chemical manufacturers to transition toward favorable business and operating models;

• Investments of chemical companies ~ 5% of revenue per annum;

• Many chemical companies employ analytics based on first principles, empirical and hybrid models. New data-driven analytics are emerging;

• Chemical companies have high expectations of cost savings (4,2%/annum), increased revenue (3,1%/annum);

• Digitization leading to chemical 4.0 can be fulfilled by three approaches that follow each other (digital processes, digital operations, digital business models). The digital disruption opportunity is in digital business models;

• Big data benefits can be related to different business functions, applications, KPIs, business focus areas;

• Transforming data into knowledge and actions is key to gain a competitive edge;

• Big data can drive chemical innovation and R&D, smart supply chain management, smart marketing, operational excellence, predictive maintenance and other processes;

• Cyber attacks is the most recognized risk for chemical companies;

• Safety considerations constrain supply-chain flexibility and create stringent requirements for security and process safety for big data implementation;

• The implementation challenges will be to resolve interface and architecture challenges and to successfully build outwards and beyond the boundaries of individual plants.

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CONFIDENTIAL

Industry 4.0 journey starts with first applications of BIG DATA Leading to a future of an end-to-end support from product development, planning and scheduling and commissioning to production, packaging, inventory management and marketing and distribution.

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