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Similaire à Knowledge Management: Using A “Flight Simulator” Concept To Support Succession Planning and Operator Training
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Knowledge Management: Using A “Flight Simulator” Concept To Support Succession Planning and Operator Training
- 1. Knowledge Management: Using A “Flight Simulator” Concept To Support Succession Planning and Operator Training Malcolm Fabiyi (PhD, MBA), Rajeev Goel (PhD, P.E, P. Eng.), Spencer Snowling (PhD, P. Eng.) Hydromantis Eric Nelson, Pima County Regional Wastewater Reclamation Department Thomas Kutcher, Metropolitan Sewer District of Greater Cincinnati
- 2. Outline • Overview • Drivers of knowledge management • The succession planning problem • Role of simulators in wastewater treatment • Case studies • Demonstration
- 3. The last 100 years of wastewater treatment 1914 Adern & Locket invent Activated Sludge Process 1972 Clean Water Act COD removal 1969 Cuyahoga River Fire 1970 EPA Established Removal of solids and large organic matter 1990s Growing concern about Nutrients (N,P) 2001 Regulations for N, P added to NPDES permits MBR Multistage, varying Dissolved Oxygen Biogas Nutrient recovery CEC Removal of soluble organics Removal / Recovery of N,P Toilet to Tap Increasing Complexity, Cost
- 4. Ageing Operator Population Pennsylvania Wastewater Operator Demographics -- October 12, 2012 (Source: PA DEP eFACTS) Increasing career transitions
- 5. • Loss of institutional knowledge • Heavy reliance on on-the-job training (OJT) rather than on formal training and development • Weak or non-existent Leadership Development Programs • Complications in bargaining agreements • Issues of employee retention, such as compensation and lack of advancement Succession Planning Succession Planning White Paper. NYWEA, 2012 Complexity, Cost, Career transitions
- 6. Simulators – Complexity, Cost & Risk
- 7. Real Plant Virtual Plant Use of Simulators in wastewater treatment • Predicting and Assessment of Water Quality • Technology Evaluation (process, aeration, etc.) • Limit of Technology • Assessment of Compliance
- 8. Why Use Modeling? • Cheaper than building/modifying the real system • Easier than carrying out testing on existing systems • Risk-free - see the consequences before implementation • Get results quickly
- 9. 0 10000 20000 30000 40000 50000 60000 0 50 100 150 200 250 300 Time (days) WASTSSConcentration(mg/L) Simulated Measured How Is It Used? Create Model Calibrate to Known Performance Simulate Different Scenarios Simulate “Base Case” Compare and Evaluate Models can be used to support training
- 10. • High fidelity – true to the actual process • Replicate reality – start-up, shutdown, dynamic ops, etc. • Support optimization and enhancement Simulation Based Learning Source: Vesel, 2013
- 11. 2D 3D 3D simulators offer High fidelity experience
- 12. Wastewater “Flight Simulator” • Advanced operator training and education • Identification and validation of plant optimization and cost saving strategies • Project and risk analysis • Key decision making support tool for all levels of management • Engagement with stakeholders
- 13. Case 1: MSDGC Goals for Simulator • Support wet weather & nutrient removal upgrades planning • Operations planning – shutdowns, schedule maintenance • Operations tool for plant staff training • “What – if” scenario operations • Enable plant optimization • Useable by MSD employees as well as consultants 220,000 accounts, 850,000 residents Flow: 1.5 to 130 MGD
- 14. Plant Overview • 8.0 MGD • NH3-N limits (1.5 mg/l) • Effluent NH3 < 0.1 mg/l • Effluent NO3 ~ 14 mg/l • 8 DO Zones MSDGC - Polk Run WWTP VWEA Operations Conference 2015 Development of Process Models for Planning, Operations, and Training (Yi, et al.) Goal: Optimize TN removal and reduce energy Initial Total Air Req’d – 2.4M CF/day Average Flowrate – 1680 CFM Eff NH3 < 0.1 mg/l; TN ~ 14.2 mg/l Total Air Req’d – 2.1M CF/day Average Flowrate – 1500 CFM Eff NH3 < 0.1 mg/l; TN ~ 10.3 mg/l Final Operator led optimization effort Variables in model • Tanks in and out of service • Flow splits • RAS/WAS rates • Air flow – cfm vs. DO control • Decanting / dewatering operations RAS PE ML 8 DO Zones
- 15. Total Air Req’d – 2.4M CF/day Average Flowrate – 1680 CFM Eff NH3 < 0.1 mg/l; TN ~ 14.2 mg/l Change DO in ABs Initial Conditions Lower DO Effluent NO3 = 14.2 mg/l Effluent NO3 = 10.3 mg/l No Change in Effluent NH3 VWEA Operations Conference 2015 Development of Process Models for Planning, Operations, and Training (Yi, et al.) Goal: Optimize TN removal and reduce energy Total Air Req’d – 2.1M CF/day Average Flowrate – 1500 CFM Eff NH3 < 0.1 mg/l; TN ~ 10.3 mg/l
- 16. Case 2: Pima County Tres Rios WRF • 3 metropolitan WRFs and 8 sub-regional facilities • Extensive upgrades and retrofits over last ten years • Calibrated GPS-X™ models and SimuWorks™ to support design, upgrades, optimization, operations & training
- 17. Beyond SCADA……Probe-X™ • Integrate SCADA and laboratory measurements • Develop process insights, ongoing operational assessment, performance review, reporting & internal benchmarking of performance across operational periods
- 18. Case 3: Ontario Clean Water Agency • Operate 200 water & wastewater facilities • Largest operator of water and wastewater facilities in Ontario • SimuWorks™ used for internal operator training & operator certification since 2012 “Hydromantis’ simulation technology is presenting our staff with an unparalleled operator training environment and the implementation of real-time links between GPS-X™ and operator control systems provide forward looking, actionable data for improved decision making support,” – OCWA President & CEO Operators at the Belleville (Ontario) Water Control Plant work on a troubleshooting scenario during a Sewage Simulator Solutions course (TPO Magazine, Virtual Reality, January 2014)
- 19. Case 4: WEF Operations Challenge • Create a platform for WEF Operations Challenge • Develop realistic, challenging scenarios • Operator friendly, and easy to use • Tracks progress, enables scoring WEF Operations Challenge: Simulation as a Process Skill …..simulators are primarily designed to help operators understand their plant and try new process strategies, they can also be used as training tools. An operator can be given a set of initial conditions and shown how treatment processes react. Then the operator can change process parameters, run a new simulation and see the results. This helps an operator understand how operating parameters affect treatment process performance, which is the basis for operating skills and process control. If an operator is presented with a preconfigured plant that is performing poorly, he or she can demonstrate their process skills by changing operating conditions and running simulations repeatedly until the plant is performing as desired. This makes performing a plant simulation a potential part of the Process Control event.
- 21. Demonstrations
- 22. SimuWorks™ Bird’s eye view 3D representation Replicate Plant SCADA
- 23. Conclusions •Flight simulator concept can support training and succession planning •Simulator interface allows user to make changes to plant operation, and see prediction of performance •Robustly handles complexity •Effective tool for planning, facility risk assessment, emergency planning & response, optimization •Visual tool to enhance stakeholder engagement