Digital transformation for the process industries : a roadmap / Osvaldo A. Bascur.

By: Bascur, O. A. (Osvaldo A.) [author.]Material type: TextTextPublisher: Boca Raton : CRC Press, Taylor & Francis Group, 2021Edition: First editionDescription: 1 online resource (xxxiv, 286 pages) : illustrationsContent type: text Media type: computer Carrier type: online resourceISBN: 9781003010524; 1003010520; 9781000165432; 1000165434; 9781000165388; 1000165388; 1000165485; 9781000165487Subject(s): TECHNOLOGY / Engineering / Chemical & Biochemical | Chemical engineering -- Data processing | Industrial management -- Data processing | Operations research -- Data processing | Production management | Business enterprises -- Technological innovationsDDC classification: 660.028/5 LOC classification: TP184 | .B37 2021ebOnline resources: Taylor & Francis | OCLC metadata license agreement
Contents:
1. Advancing to an Industrial Digital Data Infrastructure2. Building the Foundation3. Using EIDI Data as a Strategic Asset4. Advanced Analysis Using Unit Data and Event Templates5. The Humans behind the Data: Visualization and Collaboration6. Preventing Abnormal Situations7. Energy Management and Operational Improvements8. Successful Examples of Enterprise-Wide Digital Transformation9. Beyond the Refinery--Connecting the Ecosystem10. Operational and Business Analytics Integration11. ProcIndustries Enterprise-Wide Rollout12. The Future of the Digital Enterprise
Summary: Imagine if your process manufacturing plants were running so well that your production, safety, environmental, and profitability targets were being met so that your subject matter experts could focus on data-driven business improvements. Through proper use and analysis of your existing operations data, your company can become an industry leader and reward your stakeholders. Written in an engaging and easily understandable manner, this book demonstrates a step-by-step process of how an organization can effectively utilize technology and make the necessary culture changes to achieve operational excellence. You will see how several industry-leading companies have used an effective real-time data infrastructure for mission-critical business use cases. The book also addresses challenges involved, such as effectively integrating operational (OT) data with business (IT) systems to enable a more proactive, predictive management model for a fleet of process plants. Some of the things you will take away: Learn how a real-time data infrastructure enables transformation of raw sensor data into contextualized information for operational insights and business process improvement. Understand how reusing the same operational data for multiple use cases significantly impacts fleet management, profitability, and asset stewardship. See how a simple digital unit template representing production flows can be repeatedly used to identify critical inefficiencies in plant operations. Discover best practices of deploying real-time situational awareness alerts and predictive analytics. Realize how to transform your organization into a data-driven culture for continuous sustainable improvement. Find out how leading companies integrate operations data with business intelligence and predictive analytics tools in a corporate on-premises or cloud-enabled environment. Learn how industry-leading companies have imaginatively used a real-time data infrastructure to improve yields, reduce cycle times, and slash operating costs. This book is targeted for process industries production and operations leadership, senior engineers, IT management, CIOs, and service providers to those industries. Academics will benefit from latest data analysis strategies. This book guides readers to use the best, results-proven approaches to ensure operational excellence.
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Imagine if your process manufacturing plants were running so well that your production, safety, environmental, and profitability targets were being met so that your subject matter experts could focus on data-driven business improvements. Through proper use and analysis of your existing operations data, your company can become an industry leader and reward your stakeholders. Written in an engaging and easily understandable manner, this book demonstrates a step-by-step process of how an organization can effectively utilize technology and make the necessary culture changes to achieve operational excellence. You will see how several industry-leading companies have used an effective real-time data infrastructure for mission-critical business use cases. The book also addresses challenges involved, such as effectively integrating operational (OT) data with business (IT) systems to enable a more proactive, predictive management model for a fleet of process plants. Some of the things you will take away: Learn how a real-time data infrastructure enables transformation of raw sensor data into contextualized information for operational insights and business process improvement. Understand how reusing the same operational data for multiple use cases significantly impacts fleet management, profitability, and asset stewardship. See how a simple digital unit template representing production flows can be repeatedly used to identify critical inefficiencies in plant operations. Discover best practices of deploying real-time situational awareness alerts and predictive analytics. Realize how to transform your organization into a data-driven culture for continuous sustainable improvement. Find out how leading companies integrate operations data with business intelligence and predictive analytics tools in a corporate on-premises or cloud-enabled environment. Learn how industry-leading companies have imaginatively used a real-time data infrastructure to improve yields, reduce cycle times, and slash operating costs. This book is targeted for process industries production and operations leadership, senior engineers, IT management, CIOs, and service providers to those industries. Academics will benefit from latest data analysis strategies. This book guides readers to use the best, results-proven approaches to ensure operational excellence.

1. Advancing to an Industrial Digital Data Infrastructure2. Building the Foundation3. Using EIDI Data as a Strategic Asset4. Advanced Analysis Using Unit Data and Event Templates5. The Humans behind the Data: Visualization and Collaboration6. Preventing Abnormal Situations7. Energy Management and Operational Improvements8. Successful Examples of Enterprise-Wide Digital Transformation9. Beyond the Refinery--Connecting the Ecosystem10. Operational and Business Analytics Integration11. ProcIndustries Enterprise-Wide Rollout12. The Future of the Digital Enterprise

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