Presented by. Dr. Osvaldo A. Bascur, IP and OSIPress Initiative

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Enabling Enterprise Operational Intelligence in the Process Industries: Improvements, Innovation and Reinvention Presented by Dr. Osvaldo A. Bascur, IP and OSIPress Initiative

Abstract: Large industrial complexes have more data than a small city and much it is in real-time, changing rapidly as internal and external conditions evolve. As corporations buy and sell assets and reengineer their staff, the structure and tools that were used to understand these data are lost. This results in significant deterioration in the ability to maintain a smart operation. By embracing a real-time infrastructure with a data centric approach mining companies are enabling their people to optimize the availability of their assets and reducing operating costs. The integration of chain supply for asset and energy optimization are one off the most critical factor due to the large changes in the raw materials. This presentation summarizes how early adopters are empowering their local and strategic support teams to get insight from the overall process effectiveness index based on key variables such as losses due to (mobile or static) equipment availability, energy savings, and production optimization. Three commonalities become evident: People empowerment aligned to Enterprise Mission, A continuous Improvement and Innovation program at the local and enterprise, and A data Infrastructure to facilitate local operational intelligence and enterprise intelligence. In summary, these organizations are embracing a smart data infrastructure to move ahead to become leaders in their field. 2

Agenda Current Industry Challenges and the Evolving Operations Are you really using your information? Examples of Success Defining our Journey to Operational Excellence Conclusion and Call to Action 3

Rethinking our approach to innovation Collaboration Knowledge transfer New approaches Creating sustainable value Local partnerships 4

Innovation is the key to solving these challenges Mining needs to leap forward 20 years in the next five 5

Coordination and Integration Outside Influences Government Stockholders Human Resources Financial Markets Crude Supply Operations Maintenance Feed Stock Inv. Just in Time Training Specs Process Safety Management Process Targets Distribution / Orders / Scheduling Inventories S U P P L I E R S Data Reconciliation LP Model Plant Wide Optimization Inventory Plans Engineering Execution Proposals Nov. Jan Communication Measuremen Project Schedule t Sep Planning P1 P2 Specials Training Strategic Business Plan Prod Tanks Performance Monitoring Yields Costs March Reporting Markets Needs Project Area 1 Task 1 Task 2 Project Area 2 Task 1 Task 2 Resources / Cost Control Performances Rules C U S T O M E R S July Assessment May Approvals Simulation Engineering Standards Design/ Cost 6

Enterprise Infrastructure Data Engineering Analysis for the IDEA Division Plant Unit 7

Coordination and Collaboration Support Plant Management Operations Maintenance Engineering Services Customers Visualization Tools Presentation Layer Tons Shipped Tons Trucked Operations Delays Power & Water Usage Consumables Transactions RM Losses T O TRANSF R Waste C1 MANUF C2 Tons Processed Heats, Consumables Power & Water Usage Asset Information, Process Data C3 PRODUCT Tons Grade, Assays, Samples C4 Receivable & Storage Ship Loading Port Operations and Delays 8

Enterprise Dynamic Performance and Notification INPUTS RT History Data Capture Data Validation PLANT Controls Event Detection PRODUCTS Panel Station Alarm Summaries PI-AF Class. Analysis Asset Conditions Operations Maintenance SQL Server Model Estimation Process Coordination Plant Optimization Metrics, KPI Inventories Costs Reduction Management Planning Improvements Bascur 1988, ISA 9

Bimodal Continuous Improvement and Innovation Metrics: Production, Quality, Costs, Equipment Availability, Environmental and Safety alerts with fast resolution and improved decision making. Real Time Evaluation of Metrics => Mines, Mills, Smelters, Process Refineries Plants Continuous Improvement and Innovation MONITOR MONITOR In Control? In Control? Yes No Identify Root Causes Identify Root Causes Operations/Maintenance Yes No Local Operations/Maintenance Left Brain $ IMPROVE Satisfied? Establish Alternatives Yes No $ Strategic Competence Centers Maintenance/Engineering/Management Right Brain Technology Change Behavior One Center 10

Production Energy Fuel Water Limestone 11

Agenda Current Industry Challenges and the Evolving Operations Are you really using your information? Examples of Success Defining our Journey to Operational Excellence Conclusion and Call to Action 12

PI System Infrastructure in CEMEX 2011-2013 2009-2010 1995 1995-2004 2005-2006 2007-2008 PI Infrastructure as Enterprise Platform Cement Production Management First PI System Installed Expanding PI System Installs Enterprise Agreement Worldwide PIMS Project EA Agreement Access to Industry Principals, Center of Excellence, Software, etc. 13

Cemex Production Model Sys. Administrator Plant Configuration Daily Validation SAP Interfaces Reports DVM Equipment Operation Schedule Hours Inventory Levels Equipment Production Capacity Maintenance Production Kwh Low Heat Value 14

CPM Cement Production Model ERP Systems BI Systems Quality Management Production Data Validation Energy Management Emissions Management Condition Base Maintenance OSIsoft EA PI System Infrastructure 15

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Sustainable Value Added to the Enterprise Center for Monitoring and Diagnosis Operational Excellence On Line Analytics Continuous Improvement and Value Creation Copyright 2015 17 OSIsoft, LLC 17

Drastic Energy Reductions 18

Future: Moving into Interconnected Systems Mobile Equipment Manufacturer Equipment Manufacturer Chemical Manufacturer Outotec Finland Cloud Chris Mining Video Mining and Metallurgical Enterprise Power Generation Government Universities External Engineering Support 19

Agenda Current Industry Challenges and the Evolving Operations Are you really using your information? Examples of Success Defining our Journey to Operational Excellence Conclusion and Call to Action 20

Towards Operational Intelligence Transformation Integration Stream Line Synchronize Business Processes With Operational Processes 21

7 Key areas for Operational Improvements 1. - Production Monitoring 2. - Quality Monitoring 3. - Asset Monitoring 4. - Energy-Water-Reagents Monitoring 5. - Environmental Monitoring 6. - Safety Monitoring 7. - Systems Monitoring 22

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A Five Tier Framework for Business Optimization Mission, Strategy and Goals Business Process Support Plant Management Operations Maintenance Engineering Services Customers Visualization Tools Presentation Layer Cloud Knowledge Coordinator Application Layer Repository Manager Data Servers DataBase Data Services Virtual Server Business Improvement Process Plant Process Flow Diagram 24

Standardizing for common understanding the Process Industry Unit Template Raw Materials Scheduled Targets, Process Requirements Select Major Process Areas Input - Output Production Streams Consumption (Energy, Water, Materials) Inventories Define Process and Equipment Events Input Consumption Process Industry Unit Template Output Waste Do not use quality measure at the object level Availability Safety 25

Operational Intelligence Basics Infrastructure Engineering Analysis People Notifications Notifications Notifications Notifications Data Aggregation Data Aggregat ion Data Classification Event Generation Data Classification Event Generation Data Discovery Operational Intelligence Data Analysis Enterprise Intelligence Data Context + Events Information Insight Actionable Information 26

Requests Production Quality Equipment Energy Water Costs Environmental Safety Communities Enabling Enterprise Operational Intelligence Metrics Targets Continuous Improvement and Innovation MONITOR In Control? Identify Root Causes Yes No Dollars IMPROVE Satisfied? Establish Alternative Yes No 1.- Strategic 2.- Support 3.- Real Time Results Yields Quality Products Equipment Availability Energy/ton Specific/ton Cost/ton Losses Waste Emmissions Incidents Data and Events R Empowerment Materials Reject T O Process Waste C1 Products C3 Shipping C4 C2 27

Towards Integrated Business and Operational Intelligence Integrated Planning, Continuous Improvement and Innovation Process 28

Excellence in Sustainability Programs! Business / People Enterprise Intelligence CONTINUOUS Improvement and Innovation Positioned as development partner of choice with the Local Government, Communities and Value from Sustainability programs Avoid surprise events, reduce the costs associated with stoppages. Operational Intelligence Achieving Improvements on water and energy usage results in direct financial benefit 29

Agenda Current Industry Challenges and the Evolving Operations Are you really using your information? Examples of Success Defining our Journey to Operational Excellence Conclusion and Call to Action 30

Things to think about Embrace the use of data and analytics to anticipate disruption and analyze responsive scenarios. Consider how to provide infrastructure and investment for incubating and scaling growth, new ideas and innovation. Business processes through the entire value chain of industrial process shift to digital-driven and human enabled model. 31

Enterprise Infrastructure Data Engineering Analysis for the IDEA Division Plant Unit 32

Infrastructure Data Engineering Analysis Osvaldo Bascur osvaldo@osisoft.com IP and OSIPress Initiative OSIsoft, LLC

Questions Please wait for the microphone before asking your questions State your name & company 34

Summary: Operational Intelligence Foundation People Infrastructure Bimodal Continuous Improvement and Innovation Operational Intelligence Business Intelligence Enterprise Intelligence 35

Real Time Data Capture Real Time Event Capture Real Time Data Classification Real Time Data Aggregation Real Time Data Notification Data Aggregation Notifications Presentation and Consumption Business Views Data Analysis, Cubes, Modelling Models, Real Time Predictive Analytics, Views, Aggregation at Detail Enterprise Plant Area Unit Data Classification Event Generation Data Classification Monitor Strategy Improve Strategy Data Events Capture and Storage Interfaces Action Root Cause Measure Action Measure Improvement and Innovation Expert User User Collaboration User 36