• Improve product quality • Increase throughput and/or yield • Reduce energy usage
2
Benefits of PlantPAx Advanced Controls
Smart, Safe & Sustainable Production
0.34 0.45 0.12 0.34
143.0
∂u ∂ 2u 2 0.45 = c12.34 ∂t ∂ t2
0.12
+1
12.01
5.10 5.34 5.23
12.67
8
Real-time Process Data 0.67
0.14 ⌠ exp 2c √π t ⌡ 0.46 0.46 -1 0.67
13
CMM
– Crushing/Grinding Typical Benefits – Kilns & Drying – 2 to 5% production – Stockpile Blending increase Process Types – 2 to 5% energy consumption – Cementreduction – – 20Minerals to 40% product variability reduction – Fertilizer – 10 to 30% off-spec – Ammonia
• Control
– Closed-loop multivariable model predictive control (MPC) provides faster responses to changing operating conditions and constraints to minimize product variability and improve yields
• Prediction
– Build models that can accurately predict process changes based on changing process inputs and disturbances – Combine prediction models with real-time data to build Soft Sensors to identify product changes before they occur, allowing pro-active operator actions
• Advanced Supervisory Control
– Focus is on PRODUCT variables – production rate, product quality, product specifications (e.g. moisture, color, density, purity, etc.) – Sends setpoints to process control loops - good regulatory control is prerequisite to achieve full MPC benefits
11
The key to effective control is good modeling
Benefits of Model Predictive Control
SPECIFICATION OR LIMIT
KEY TARGET
BEFORE MPC
WITH MPC
WITH OPTIMIZATION
12
MPC Applications
CPG
– SprayBenefits Dryers Typical – Evaporators – 5 to 8% production – Energy Centers increase Process Types – 30 to 60 % moisture variability – Milk reduction Powder – – 20Coffee to 50% off-spec product reduction – Laundry – 5 to 10% energy Detergent consumption reduction – Conc. juice
product reduction
Polymer/Chemical
– Reactors/Extruders Typical Benefits – Distillation Towers – 4 to 8% prime – Furnaces product yield increase Process Types – 35 to 75% product variability reduction – PE, PP, PS, PC – – 20-40% transition Ethylene Plants time reduction – Styrene Plants – 3 to 7% feed stock – Crude Refining wastage reduction – Gas Plants
Bio-fuels
– DDGS Evap/Dryer Typical Benefits – Water Balance – 4 to12% ethanol – Fermentation production capacity – Distillation increase – 2 to 5% ethanol Process Types yield increase – Corn Ethanol – – 3 to 6% energy Cane Ethanol use/gallon reduction – Bio-diesel
9
Soft Sensor Applications
Prediction Actual
10
Model Predictive Control
A Systematic Approach for Control of Processes with Constrained Nonlinear Dynamics
3
What is a Model?
Models Represent “Knowledge”
A model explains or emulates the behavior of a process...
monomer melt index modifier catalyst y = a3 u3 + a2 u2 + a1 u + a0 density
Real-time Applications of Models:
– – – –
5
Soft Sensors Model Predictive Control Process Optimization Plant-wide Optimization
Usesቤተ መጻሕፍቲ ባይዱof Models
• Analysis
– Analyze vast amounts of historical data to discover unknown correlations and relationships to gain better insight into the process
Uo 0.14
(x13.03 4c 13.67
13.69
υ6.02 )2
6.70 4.98
2t
dυ
Building Soft Sensors
• Import Data – Raw data editor and formatter – Data extraction wizard for FT Historian • Preprocess data – Cleanse data of outliers, bad data, etc. – Numerical and graphical tools • Model – Build and train empirical process model – Compare various sets of inputs to determine best model • Analyze – Audit and learn from process model – What Ifs? test and exercise process model • Deploy – SoftSensor Designer converts models to AOI
• Optimization
– Steady-state models can identify the optimum operating parameters based on current conditions and constraints to meet desired economic objectives (maximize rate, minimize energy, minimize raw material, …)
6
You can’t control what you can’t measure
• What if in-line sensors are unavailable, unreliable, too expensive
Process Samples Analysis
Process Adjustments
One hour to one day delay !
Lab Results
7
143.0
Solution: Soft Sensor
• Software model that predicts process values based on real-time process data