ARC's Tom Fiske APC Best Practices Presentation @ 2009 ARC Industry Forum
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ARC's Tom Fiske APC Best Practices Presentation @ 2009 ARC Industry Forum in Orlando, FL. APC and Local Optimization Definitions APC • Online real-time control • Popular method: linear multivariable control Optimization • Online real-time to determine optimum setpoints • Rigorous first-principle models • Empirical models • Offline or open loop for advisory • Rigorous or empirical models • Ad-hoc analytic tools • Statistical methods The purpose of the research was to develop an understanding of how process manufacturers around the world are using APC to create a sustainable competitive advantage. The survey was designed to capture information about the current status of APC usage.
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ARC's Tom Fiske APC Best Practices Presentation @ 2009 ARC Industry Forum
- 1. APC Best PracticeAPC Best Practice Tom Fiske Senior Analyst ARC Advisory Group tfiske@arcweb comtfiske@arcweb.com
- 2. AgendaAgenda APC Overview Market PerspectiveMarket Perspective APC Best Practice SummarySummary 2 © ARC Advisory Group
- 3. APC and Local OptimizationAPC and Local Optimization Definitions APC • Online real-time control • Popular method: linear multivariable control Optimization • Online real-time to determine optimum setpoints • Rigorous first-principle models • Empirical models • Offline or open loop for advisoryO e o ope oop o ad so y • Rigorous or empirical models • Ad-hoc analytic tools • Statistical methods 3 © ARC Advisory Group • Statistical methods
- 4. Types and Value of APCTypes and Value of APC Real-time Optimization lueasingVal Nonlinear Multivariable Control &Increa Control Linear Multivariable Control Other Supervisory Control Methods Inferential Sensors ngEffort Advanced Regulatory Control Regulatory Control ncreasin 4 © ARC Advisory Group Regulatory Control In
- 5. Advanced Predictive Control Reduces VarianceAdvanced Predictive Control Reduces Variance Variance Reduction allows Processes to Operate Closer to Limits or ConstraintsCloser to Limits or Constraints Specification Limit Targetpecification Before APC After APC Move closer to limit Sp 5 © ARC Advisory Group
- 6. Benefits of Control and OptimizationBenefits of Control and Optimization 100 Process Control Contribution 100100 Process Control Contribution st% 708090 Process Control Contribution st% 708090 st% 708090 Process Control Contribution Model Predictive >20% Real-time Optimized >25% CapitalCos 405060 Model Predictive >20% Model Predictive >20% Real-time Optimized >25% CapitalCos 405060 CapitalCos 405060 >20% C 102030 Regulatory Basic >45% Adv >10% >20%>20% C 102030 C 102030 Regulatory Basic >45% Adv >10% Regulatory Basic >45% Adv >10% Regulatory Basic >45% Adv >10% Regulatory Basic >45% Adv >10% Regulatory Basic >45% Adv >10% APC & O ti i ti B fit 3 5 7% f T t l A l G P fit Potential Performance Improvement 0 10 20 30 40 50 60 70 80 90 100 0 Potential Performance Improvement 0 10 20 30 40 50 60 70 80 90 100 Potential Performance Improvement 0 10 20 30 40 50 60 70 80 90 100 00 6 © ARC Advisory Group APC & Optimization Benefit: 3.5 – 7% of Total Annual Gross Profits
- 7. Creating and Sustaining ValueCreating and Sustaining Value Continuous Improvement ue Target Benefits p o Reven Time st S t i d Cos Time to Revenue Sustained Performance Improved 7 © ARC Advisory Group Time to Revenue
- 8. ScopeScope The purpose of the research was to develop an understanding of how process manufacturers around the world are using APC to create a sustainablethe world are using APC to create a sustainable competitive advantage. The survey was designed to capture information about the current status of APC usage. ARC received about 50 responses from the survey on APC usageAPC usage. 8 © ARC Advisory Group
- 9. Characteristics of Research Respondents Respondent come from a variety of industries Others, 4.1% Food & Bev, 2.0% Pharmaceutical, 4.1% Power, 6.1%Power, 6.1% Mining & Metals, 8.2% Oil & Gas, 10.2% Chemicals, 24.5% Petrochemical, 18.4% Refining, 22.4% The majority come from heavy process big APC users 9 © ARC Advisory Group The majority come from heavy process – big APC users
- 10. Ranking of Research Respondents ARC best practice reports group responses into the categories of Leaders, Competitors, and Followers. Over ten separate performance criteria were used to rank the responses. Ranking Leader Top 20% Competitor Next 50% Follower Last 30% For each survey response, each of the performance criteria was given a quantitative measurement and the total used ki d i 10 © ARC Advisory Group as a ranking demarcation.
- 11. Organizational Aspects – APC Implementation Number of APC Applications Leaders Followers Competitors 0% 20% 40% 60% 80% 100% Followers 0 5 6 10 11 25 25 User’s Perspective • About 22 % of users believe APC provides a competitive advantage Ab t 78% f b li APC i t i titi 0-5 6-10 11-25 25+ 11 © ARC Advisory Group • About 78% of users believe APC is necessary to remain competitive Leaders: APC culture & Adopt BP
- 12. Organizational Aspects – APC Implementation APC Outsourcing Strategy Leaders Competitors Followers 0% 20% 40% 60% 80% 100% Less than 25% Between 25 and 50% Between 50 and 75% Over 75% 12 © ARC Advisory Group Leaders: View APC as competitive Advantage, they have more internal resources and outsource less
- 13. Organizational Aspects – APC Implementation Use of Internal Resources during Implementation Leaders Competitors Followers 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% Dedicated Teams Manufacturing Staff EngineeringStaff Other 13 © ARC Advisory Group
- 14. APC Maintenance MethodologyAPC Maintenance Methodology APC Outsourcing Strategy Competitors Leaders Followers p 0% 20% 40% 60% 80% 100% Lessthan 25% Between 25 and 50% Between 50 and 75% Over 75% 14 © ARC Advisory Group
- 15. APC Maintenance MethodologyAPC Maintenance Methodology Internal Resources Emerging Best Practice Criteria APC Applications/ APC Expert 0% 20% 40% 60% 80% 100% APC Expert Certificaion Yes No APC Applications/Expert range typically range 15 © ARC Advisory Group pp / p g yp y g between 5 and 10 depending upon its complexity
- 16. APC Maintenance MethodologyAPC Maintenance Methodology Use of Internal Resources for Maintenance Competitors Leaders Followers 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% Dedicated Teams Manufacturing Staff EngineeringStaff 16 © ARC Advisory Group
- 17. RTO Implementation MethodologyRTO Implementation Methodology Number of RTO Applications Leaders F ll Competitors 0% 20% 40% 60% 80% 100% Followers User’s Perspective • About 30 % of users believe RTO provides a competitive advantage 0 1-2 3-5 over 5 17 © ARC Advisory Group About 30 % of users believe RTO provides a competitive advantage • About 70% of users believe RTO enables more effective manufacturing
- 18. RTO Implementation MethodologyRTO Implementation Methodology RTO Outsourcing Strategy Competitors Leaders Followers 0% 20% 40% 60% 80% 100% Lessthan 25% Between 25 and 50% Between 50 and 75% Over 75% 18 © ARC Advisory Group Leaders more heavily involved in Implementing RTO
- 19. Focus Areas for APC Current and Future UseFocus Areas for APC Current and Future Use APC Focus Areas for Various Situations Large Cont. Units Large Cont. Units Large Units: Abnormal Small Units: Transitions Large Units: Tranisitions Small Cont. Units Leaders Large Units: Abnormal Small Units: Transitions Large Units: Tranisitions Small Cont. Units Competitiors 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% Small Units: Abnormal Large Units: Abnormal Deployed BeingDeployed Short-term Long-term No Plans 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% Small Units: Abnormal Large Units: Abnormal Deployed BeingDeployed Short-term Long-term No Plans Small Cont. Units Large Cont. Units s • Note: These charts do i di Small Units: Abnormal Large Units: Abnormal Small Units: Transitions Large Units: Tranisitions Followers not indicate percent saturation. The charts show only that users are deploying or plan to deploy APC on some process units in the indicated category 19 © ARC Advisory Group 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% Deployed Being Deployed Short-term Long-term No Plans
- 20. Adoption Level of APCAdoption Level of APC Current Level of APC Adoption for Continuous Processes Leaders Competitors All Followers 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% Large Units/Plants Small-Midsize Units/Plants 20 © ARC Advisory Group g
- 21. Adoption Level of APCAdoption Level of APC Current Level of APC Adoption for Transition Management in Continuous ProcessesManagement in Continuous Processes Competitors Leaders All Followers 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% All 21 © ARC Advisory Group Large Units/Plants Small-Midsize Units/Plants
- 22. Adoption Level of APCAdoption Level of APC Current Level of APC Adoption for Abnormal Situations in Continuous Processesin Continuous Processes Competitors Leaders All Followers 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% All 22 © ARC Advisory Group Large Units/Plants Small-Midsizde Units/Plants
- 23. APC Techniques vs. Objectives for Non-Steady StateAPC Techniques vs. Objectives for Non-Steady State Transition Management is Becoming Competitive Advantage Operator Guidance Sequence Control S f C id i Safety Consideration Improve Quality Increase Throughput Increase Energy Savings Safety Consideration Improve Quality Increase Throughput Increase Energy Savings Safety Consideration 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Man-Hour Saving Faster Swith Over Very Important Important Somewhat Important Less Important Not Important 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Man-Hour Saving Faster Swith Over Very Important Important Somewhat Important LessImportant Not Important Model Predictive Control Increase Energy Savings Safety Consideration Faster Swith Over Improve Quality Increase Throughput gy g 23 © ARC Advisory Group 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Man-Hour Saving Very Important Important Somewhat Important LessImportant Not Important
- 24. Focus Areas for Online Opt. Current and Future UseFocus Areas for Online Opt. Current and Future Use Online Optimization Focus Area for Various Situations Large Units Large Units Dyn Opt Small Units Large Units Leaders Dyn Opt Small Units Large Units Competitiors 0% 20% 40% 60% 80% 100% Batch Deployed BeingDeployed Short-term Long-term No Plans 0% 20% 40% 60% 80% 100% Batch Deployed Being Deployed Short-term Long-term No Plans Small Units Large Units s • Note: These charts do i di Batch Dyn Opt Small Units Followers not indicate percent saturation. The charts show only that users are deploying or plan to deploy Online Optimization on some process units in the i di t d t 24 © ARC Advisory Group 0% 20% 40% 60% 80% 100% Deployed BeingDeployed Short-term Long-term No Plans indicated category
- 25. Adoption Level of Online OptimizationAdoption Level of Online Optimization Current Level of Adoption for Online Optimization for Various SituationsVarious Situations Competitors Leaders All Followers 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% All 25 © ARC Advisory Group Large Units Small Units Dynamic Optimization Batch Optimization
- 26. Adoption Level of APCAdoption Level of APC Current Level of APC Adoption for Batch Processes Leaders Competitors All Followers 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% Soft Sensors Profile Control Run-to-Run Control MPC 26 © ARC Advisory Group Soft Sensors Profile Control Run to Run Control MPC
- 27. Controller PerformanceController Performance Control Performance Deteriorates Over Time 10% Continuous Improvement with Online Monitoring APC Performance fits 25% Good Support With No Online Monitoring APC Performance degradation Bene 40% Poor Support APC Turned On pp No Online Monitoring 27 © ARC Advisory Group Time
- 28. Adoption Level and Focus Areas for Control Performance Monitoring Adoption Level and Focus Areas for Control Performance Monitoring Control Performance Monitoring Focus Regulatory APC Competitors Regulatory APC Leaders 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% Deployed BeingDeployed Short-term Long-term No Plans 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% g y Deployed BeingDeployed Short-term Long-term No Plans • Note: These charts do not indicate that users APC • About 40% of users currently use Regulatory Performance deploy performance monitoring tools on all of its regulatory and APC applications, but rather a portion of its control applications Regulatory Followers Regulatory Performance Monitoring Applications • Approximately 30% of users currently use APC Performance Monitoring 28 © ARC Advisory Group 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% Deployed BeingDeployed Short-term Long-term No Plans Performance Monitoring Applications
- 29. Adoption Level and Focus Areas for Control Performance Monitoring Adoption Level and Focus Areas for Control Performance Monitoring Performance Monitoring: COTS vs. In-House Development APC Leaders APC Competitors 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% Regulatory COT In-House Combination 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% Regulatory COT In-House Combination • Note: These charts do not indicate that users APC • About 40% of users currently use Regulatory Performance not indicate that users deploy performance monitoring tools on all of its regulatory and APC applications, but rather a portion of its control applications Regulatory Followers Regulatory Performance Monitoring Applications • Approximately 30% of users currently use APC Performance Monitoring 29 © ARC Advisory Group 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% COT In-House Combination Performance Monitoring Applications
- 30. Plant Database ApplicationsPlant Database Applications Current Level of Automation Integration for Plant Applications and Databases Used for Process Control and Operations PAM PAM AlarmHistory MOC LIMS PAM Leaders AlarmHistory MOC LIMS PAM Competitiors 0% 20% 40% 60% 80% 100% ProcessData Storage Fully Integrates BeingIntegrated Short-term Long-term No Plans 0% 20% 40% 60% 80% 100% ProcessData Storage Fully Integrates BeingIntegrated Short-term Long-term No Plans LIMS PAM ers ProcessData Storage AlarmHistory MOC Followe 30 © ARC Advisory Group 0% 20% 40% 60% 80% 100% Fully Integrates BeingIntegrated Short-term Long-term No Plans
- 31. Control Performance MonitoringControl Performance Monitoring Key Performance Indicators for Control Monitoring Regulatory Control Advanced Process Control Prediction Accuracy % Utiliztion Prediction Accuracy % Utiliztion % Loopsat Limit Control Accuracy % Loopsat Limit Control Accuracy 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% % LoopsNormal Very Important Important Somewhat Important LessImportant Not Important 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% % LoopsNormal Very Important Important Somewhat Important LessImportant Not Important 31 © ARC Advisory Group
- 32. Control Performance MonitoringControl Performance Monitoring Key Performance Indicators for Control Monitoring Advanced Process Control Leaders Followers Competitors 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% APC % Utilization 32 © ARC Advisory Group APC % Utilization
- 33. Plant Database ApplicationsPlant Database Applications Current Level of Adoption and Functionality of Alarm Management Applications AlarmFiltering State Based Alarming AlarmAnalysis: Root Cause ReducingStanding Alarms ReducingPeak Alarms Leaders AlarmFiltering State Based Alarming AlarmAnalysis: Root Cause ReducingStanding Alarms ReducingPeak Alarms ompetitiors 0% 20% 40% 60% 80% 100% AlarmHistory AlarmAnalysis: Frequency AlarmAnalysis: Combination Deployed BeingIntegrated Short term Long term No Plans 0% 20% 40% 60% 80% 100% AlarmHistory AlarmAnalysis: Frequency AlarmAnalysis: Combination C Deployed BeingIntegrated Short-term Long-term No PlansDeployed BeingIntegrated Short-term Long-term No Plans Deployed BeingIntegrated Short term Long term No Plans AlarmAnalysis: Root Cause ReducingStanding Alarms ReducingPeak Alarms AlarmHistory AlarmAnalysis: Frequency AlarmAnalysis: Combination AlarmFiltering State Based Alarming AlarmAnalysis: Root Cause Followers 33 © ARC Advisory Group 0% 20% 40% 60% 80% 100% Deployed BeingIntegrated Short-term Long-term No Plans
- 34. Plant Database ApplicationsPlant Database Applications Plant Database Integration Plant Database Integration for Operator Assistance and Decision Support Adoption of Data Analysis Technologies Effi i M it i Sensor Diagnostics Performance Monitoring QC Improve QC ID Key ProcessFactors Estimate Key Properties 0% 20% 40% 60% 80% 100% Control Monitoring PV-MV Correlation Efficiency Monitoring 0% 20% 40% 60% 80% 100% Abnormal Situation Detection Improve Batch Ops Deployed Being Integrated Short-term Long-term No Plans % % % % % % Deployed BeingDeployed Short-term Long-term No Plans 34 © ARC Advisory Group
- 35. Th k YTh k YThank YouThank You 35 © ARC Advisory Group