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.
Author(s): Osvaldo A. Bascur
Publisher: CRC Press
Year: 2020
Language: English
Pages: 320
City: Boca Raton
Cover
Half Title
Title Page
Copyright Page
Dedication Page
Contents
Foreword
Preface
Acknowledgments
Authors
Commonly Used Terms and Abbreviations
1. Advancing to an Industrial Digital Data Infrastructure
The Disaster
Journey to an Enterprise Industrial Digital Infrastructure
Assessing the Current State
Identifying the Problem
The Current Data Infrastructure
Understanding the Barriers to Success
The Process Engineer’s View
The Plant Manager’s View
The Planning and Economics Coordinator’s View
The Production Manager’s View
The Maintenance Manager’s View
The IT Department’s Role
The Cost of Downtime
Envisioning a Strategy
Creating a Breakthrough Vision
Assessing Data Infrastructure Maturity
Laying a Foundation
First Step to Action: Convening an Operational Team
Engaging Corporate Leadership and Plant Employees
What You Should Take Away
References
Additional Reading
2. Building the Foundation
Chapter Overview
The View from the Refinery Manager’s Office
Identifying Workflow Information Gaps
Improving Scheduling, Operations, and Maintenance
Process Unit Template for Smart Thinking
Operational Excellence Methods and Tools
Workflow Management
The First Loop: Are We on Target?
The Second Loop: Are We Satisfied?
Presenting the Digital Data Infrastructure Project to the Entire Company
Operations Standardization for an Enterprise Competence Center
Enterprise Level
Regional Level
Individual Refineries
What You Should Take Away
References
Additional Reading
3. Using EIDI Data as a Strategic Asset
Chapter Overview
The Need for an Enterprise Industrial Data Infrastructure
Determining What Is Important
What Is an Enterprise Industrial Data Infrastructure?
A Decision Is Made
A Modern EIDI Implementation Approach
Decision-Making through Plant Data Hierarchy
EIDI Deployment and Configuring the EIDI Templates
Using Templates to Define Assets and Event Frames
Data Object Models
Data Acquisition, Validation, and Classification
Block and Process Flow Diagrams
Block Flow Diagrams
Process Flow Diagrams
Organizing Operational Data
Process Flow Diagram Leads to Digitizing the Plant
What You Should Take Away
References
Additional Reading
4. Advanced Analysis Using Unit Data and Event Templates
Chapter Overview
Innovative Use of EIDI Capabilities
Step 1: Develop Unit Process Templates Using Plant Block Diagrams
Step 2: Analyzing and Visualizing Operational Variance from the Generated Events
Classifying Asset Behavior for Process Improvement
Step 3: Employing Offline Visualization Tools Using Unit Process Template Data
Advanced Visual Analytics
Using Microsoft Excel Analytics Tools
Step 4: Using Contextualized Data for Modeling and Predictive Analysis
Data-Driven Analytics
What You Should Take Away
References
Additional Reading
5. The Humans behind the Data: Visualization and Collaboration
Chapter Overview
Who Will Be the ProcIndustries EIDI Users?
The Impact of Change
Rome Wasn’t Built in a Day
People-Driven Benefits from the EIDI Implementation
Getting the Visualization Right
Best Practices on Process Graphics and Ways to Present and Share Information
Mobile Access to Information
Asset-Relative Displays
Process Improvement through Visualization
Creating Dynamic Performance Operational Displays
Data Turns into Workflows: Workflows Adopted by People Turn into Meaningful Change
What You Should Take Away
Reference
Additional Reading
6. Preventing Abnormal Situations
Chapter Overview
Real-Time Data Analytics to Improve Operational Support
Business Objectives Pyramid
The Left Side of the Pyramid
The Right Side of the Pyramid
Enhancing Equipment Availability
Reactive Maintenance
Preventive Maintenance
Condition-Based Maintenance
Predictive Maintenance
Condition-Based Maintenance: The P–F Curve
Condition-Based Maintenance Using a Real-Time Data Infrastructure
Assigning Context to the Equipment Template
Assigning Analytics to Detect Abnormal Conditions and Trigger Events
Generating Notifications from the Events
Assigning the Event Templates for Analysis and Root Cause Determination
Assigning Equipment Parameter Tables
Pump Asset Example
Pump Monitoring and Analysis
Visualizing Pump Actionable Output
Integration with Other Systems
Implications of Improving Asset Availability
Operational Performance Management
Enhancing Process Control Performance Monitoring
What You Should Take Away
References
Additional Reading
7. Energy Management and Operational Improvements
Chapter Overview
Revisiting Energy Consumption
International Energy Standards
Develop Clear Business Objectives
The Plan
Metering and Inputs
Data Capture and Reporting
Data Analysis, Visualization, and Reporting
A Takeaway for the Team on Measuring Power Consumption
Smart Grid and Refinery Resiliency Improvements
Using Process Flow Diagrams for Energy Management
Using Advanced Analytic Tools to Gain Real-Time Insights
Mass Balances and Data Reconciliation
What You Should Take Away
References
Additional Reading
8. Successful Examples of Enterprise-Wide Digital Transformation
Chapter Overview
OilCo—Use of EIDI Data in Downstream Refining
OilCo’s EIDI Deployment
Advanced Analytics and Machine Learning Leads to Significant Return on Investment
On-Premise versus Cloud Analytics? No: On-Premise Plus Cloud
OilCo’s Return on Investment
Lessons Learned
Use of EIDI Data by MidPetCo for Pipeline Operations
Overview and Challenges
MidPetCo 2.0 Initiative Leverages Operational Data for Profitability
Real-Time Visibility Enhances Decision-Making and Reduces Inefficiencies
MidPetCo’s Return on Investment and Future Plans
GoldMineCo—Use of EIDI Data in Gold-Mining Operations
Process Plant Optimization Successes at GoldMineCo’s Mines and Plants
Combining Time-Series Data and Location Data for Mobile Asset Maintenance
Big Data Analytics—Populated by Site Information
Other Initiatives to Extract Value from Data
GoldMineCo’s Use of the Digital Plant Template for Metallurgy Analysis
Future Plans
So, Was It Worth It?
MaterialsCo—Use of EIDI Data in Building Materials Manufacturing
Creating a Single Version of the Truth on a Global Scale
Integration with Corporate Business Intelligence Software
Forging Ahead—MaterialsCo Production Management Version 2.0
Lessons Learned from Global Deployment
Moving to the Next Level—Artificial Intelligence and Closed-Loop Control
EIDI Data Use by ChemCo for Specialty Chemical Manufacturing
Using Technology to Combat a Decreasing Market
Putting Data to Good Use for Improved Operations
Reducing Emissions and Energy Consumption through Data Analysis
Asset Management and Other Data-Driven Improvements
Lessons Learned and Next Steps
Reference
9. Beyond the Refinery—Connecting the Ecosystem
Chapter Overview
New Ways of Sharing Data to External Partners for Additional Value
PI Cloud Connect
PI Cloud Connect Customer Examples
Anglo American Platinum—Outotec
Benefits for Anglo American Platinum
Benefits for Outotec
Cloud-Based Services Provided to a Power Generation Company
PI Cloud Connect Scalability
What You Should Take Away
References
Additional Reading
10. Operational and Business Analytics Integration
Chapter Overview
From Operational Intelligence to Enterprise Intelligence
Types of Advanced Analytics
Holistic Analytics to Meet Business Objectives
ProcIndustries Integrates Operational and Business Data
Integration to Corporate Analytics Systems
Using a Real-Time Data Infrastructure versus a Data Lake Approach
Using a Standard Method for Advanced Analytics Integration
Integrating Production Event-Based Data to Advanced Analytics
Creating a Digital Twin for Process Simulation and Modeling
Integrating Time-Series Data with Geospatial Systems
What You Should Take Away
References
Additional Reading
11. ProcIndustries Enterprise-Wide Rollout
Chapter Overview
ProcIndustries Continues Their Digital Transformation
Building the Business Case
Financially Justifying the Proposed EIDI Enterprise Rollout
Quantifiable Benefits
Non-Quantifiable Benefits
Management’s Decision
Deployment of the Infrastructure and Initial Use Cases
Working Toward a Smooth EIDI Enterprise-Wide Rollout
Initial Rollout Activities
EIDI Architecture and Cybersecurity
Phase III: Ongoing Governance and Future Use Cases
Future Use Cases
What You Should Take Away
References
Additional Reading
12. The Future of the Digital Enterprise
Chapter Overview
How the Most Successful Companies Achieve Success
Alignment of Business Goals with Digital Strategies
Viewing Operations and Production Data as a Critical Strategic Asset
Successful Teaming with Strategic Partners
Architecting for the Unexpected
Effective Use of Analytics
Self-Serve Access to Needed Information
ProcIndustries Enterprise-Wide Rollout Results
Cloud Strategy
Edge Analytics and the Evolution of the Control System
The Leadership Meeting
Hybrid Cloud Strategy
The Next Challenge
And the ProcIndustries’ Story Continues
What You Should Take Away
Additional Reading
Index
