Bentley Incorporated : How Plant Managers can improve decision making

Case Study

Digital twins are empowering engineering, operations, and maintenance in plants to collaborate and capitalize on the opportunity of

Industry 4.0. If common pitfalls can be overcome, such as data overload, the lack of systems integration and interoperability, inconsistent business processes, and siloed data, then this open and connected data environment can become a sustainable competitive advantage. Digital advancement strategies like Asset Performance Management 4.0 are being coupled

with digital twins and are becoming critical strategies for operational excellence.

Maximizing the value of assets

The reason plant staff collect, store, and analyze plant data is to improve decision-making and operations. Ultimately, they want to maximize the return on assets, minimize production, labor, and material costs, reduce the total cost of asset ownership and investment, and deliver predictable performance, on time.

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Digital Twin photo courtesy of Bentley Systems

How Plant Managers can improve decision making with Asset Performance Management 4.0 and Digital Twins

Asset Performance Management

Asset Performance Management (APM) focuses on
meeting performance	requirements	through
reliability, and takes a cross-discipline approach to
fulfil plant goals and customer needs.
Some of the key characteristics of an Asset
Performance Management system include:
• Asset strategy and risk analysis
• Condition-based	or	reliability	centered

	maintenance processes and practices
We can improve the performance of the physical assets used	• A mobile inspection platform with augmented
for production through the way people operate equipment,	reality and virtual reality capabilities for remote
through improved maintenance practices, or through design	working and remote collaboration
and engineering. This is not a new concept, as an average plant	• Predictive analytics including statistical modeling,
might have 30 to 50 design optimizations, modifications, or	neural networks, artificial intelligence, and
additions per year.	machine learning
However, the siloed approach separating engineering,	• Spare parts optimization
operations, and maintenance is no longer good enough. Success	• Asset lifecycle information management
now requires a new way forward with a collaborative approach to	Asset performance management is the plant
information accessibility coupled a process for asset performance	manager's opportunity to extend asset life safely and
management for fast and accurate decision making.	reliably, which avoids capital expenditures.
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Case Study

Photo used with permission, courtesy of Oman Gas Company

Case Study

Oman Gas Company implemented a digitalized, automated framework for asset performance management. Establishing a connected data environment and digital workflows reduced failures and improved reliability performance by 9%. The technology transformed the team and how they manage assets, resulting in significant economic gains.

Gain Insights to make effective decisions

There are many ways APM 4.0 helps Plant Managers to gain insights from data to optimize asset performance. Automated rules, calculations, artificial intelligence, and machine learning are all valuable methods to enable faster and more effective decisions. But, engineering information for each must be complete, accurate, and available to ensure decisions can be made at the right time. Otherwise, it becomes harder to mitigate consequences, and avoid downtime and unnecessary costs when assets fails.

In short, effective decision-making depends on always knowing the current state of the asset and becoming informed immediately when that state changes. This knowledge should include essential engineering information, as well as how to bring the asset back to the as-built,as-commissioned, or as- designed state. Yet components, structures, systems, and operating states all change over time due to wear and tear, operator decisions, and overall plant conditions. Changes in any single asset can negatively impact wider systems and processes. Trustworthy engineering data enables plant engineers to determine why a change occurred and who caused the change. For this purpose, asset lifecycle information management systems are the backbone of APM 4.0.

The tipping point for IIoT

APM 4.0 is effectively deploying APM within a digital twin because the Industrial Internet of Things (IIoT) movement has arrived and is at the tipping point. The cost of sensors, data connection, and data storage is now a fraction of what it used to be. As a result, the amount of raw data being generated in plants from IIoT sources is growing exponentially, and many organizations cannot keep up. Every sensor you add produces thousands of additional data points. As a result, making sense of the data to gain meaningful insights and get to the right decisions can be time-consuming and difficult if you are not sure of its relevance or accuracy.

For most plant managers, the vision of a completely autonomous plant is still a pipe dream. Industry 4.0 can connect physical assets in the plant to their digital counterparts to improve the automation of plant operations and maintenance. Using edge computing to implement artificial intelligence and automated rules is a fast and easy way to alert personnel of problems that must be addressed. However, edge computing might not monitor all aspects of every asset over the long-term and should not be used in isolation. To fully oversee a facility, you need a systematic, sustainable approach for tracking asset performance over time with visible, accessible, and trusted engineering data.

Case Study

BP created a central information store (CIS) to manage information needed for operations, including all documents, tags, metadata, and 3D model visualization. Using a Microsoft Azure-based cloud deployment of Bentley Systems' AssetWise asset performance software, the project team seamlessly integrated engineering information into operations. Doing so supports safe, reliable, and efficient operations throughout the life of their assets. With safety at the heart of all operations, BP ensures it continuously maintains the integrity of operational information.

Photo used with permission, courtesy of BP

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Digital Twins enable collaboration between engineering, operations and maintenance

A digital twin is a digital representation of a physical asset, process or system, as well as the engineering information to understand and model its performance. Typically, a digital twin can be continuously synchronized from multiple federated sources, including sensors and continuous surveying, to represent its near real-time status, working condition or position. Digital twins enable users to visualize the asset, check status, perform analysis and generate insights in order to predict and optimize asset performance. As a result, digital twins eliminate silos of data to deliver situational awareness and intelligence.

Additionally, a continually updated digital twin provides proof of accurate information needed for regulatory compliance. Engineering, operations, and maintenance greatly benefit from the combination of APM and digital twins. APM provides the strategy and analytics, while digital twins unify the data, provide situational awareness and insights, and deliver actionable information in the hands of those who need it when they need it.

Case Study

EPCOR Utilities Inc implemented an ISO 55000-aligned,risk-based asset management process supported by Bentley

Photo used with permission, courtesy of EPCOR

System's APM technology. The digital twin shows the results of asset health indexing. They gained an understanding of the consequence of asset failures, including replacement costs, damage to adjacent assets, impacts to safety, and environmental cleanup costs. Coupling this information with outage times and electrical load data, they could better predict the annual risk cost. The result was lowering their SAIDI Interruptions Duration Index score to 0.833, well below the regulated threshold of 1.15 hours/customer.

Who needs a Digital Twin and Why?

From the plant floor to the boardroom, digital twins quickly give plantstafftheinformationtheyneedtomakeimportantdecisions.

• Global and Regional Executives - Use digital twins to generate informative visualizations of large-scaleassets, track and compare plants and fleets, identify high-performingand under-performingplants, then determine what makes them succeed or fail; provide proof that the plants are in control and that assets are safe and reliable.
• Plant Managers - A unified view of asset health to ensure plant production is predictable, safe, and efficient. Get accurate information for audits and course-corrections and provide a complete, consistent view of plant data for the team to collaborate and solve problems.
• Engineers - Quickly identify potential operational problems and consider solutions. Know that the data is trustworthy to investigate, troubleshoot, and make fast and informed decisions.
• Operations - Review as-operated and historical data to understand what field changes and engineering decisions were made and why. Digital twins help operators see the big picture and optimize production.
• Maintenance and Reliability - Monitor and manage equipment health and easily spot trends and bad actors. They need to know what engineering changes were made.

Digital transformation

APM 4.0 and digital twins are digitally transforming plants to help them stay ahead of the competition. Everyone from the plant floor to the boardroom needs insights to make more informed decisions. Digital twins provide a federated portal view of all necessary systems and data, which gives workers at all levels the insight needed for overall success.

Sandra DiMatteo is the Global Director of Marketing for Digital Twin Solutions, Asset and Network Performance at Bentley Systems. She has more than 20 years of experience in digitalization solutions in asset performance management and reliability software, asset lifecycle information management and EAM enterprise asset management operating in a connected data environment in energy and process industries, utilities and public infrastructure. She is an advocate and speaker on digital twins, IIoT analytics, AI and machine learning, BIM and asset management technology solutions. Sandra is on the Reliability Leadership Institute Board of Advisors and founded the Ontario Chapter of the Society of Maintenance and Reliability Professionals.

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