Z Score,T Score, Percential Rank and Box Plot Graph
Lecture 3 bioprocess control
1. Bioprocess Control (On-line, off-line and in-line) 14th. July 2010 CEPP, UTM Skudai, Johor Prof. Dr. Hesham A. El Enshasy Faculty of Chemical Engineering CEPP, UTM, Skudai, Malaysia
2. Main Items of Presentation Cell Input and Cell out-put (conditions and nutrients requirements) Parameters for measurements and control for cultivation system Sensors used for bioreactors Feed back loops for bioprocess control Summary screen for different control system SCADA system for control using ethernet platform
4. Substrate(s) Input and Output Oxygen Carbon dioxide Carbon and Energy Sources Biomass CELL Metabolite(s) Nitrogen Source Water Other requirements (P, S,Na,K,Mg,etc…) Heat
8. Main in situ sensors used for measuring cultivation parameters
9. Exhaust gas Analyzer Feed pump(s) pH Temperature DO Aeration Pressure Power consumption Weight / volume Stirrer Speed Measurement and open or closed loop control Measurement only Common measurement and control of bioreactors as generally accepted as routine equipment
20. Standard Antifoam Sensor Type of foam: Early foaming Late foaming Antifoam effects on: DO Growth morphology (Filamentous MO) Foam sensors: Low foam sensor High foam sensor
22. On-line cell mass and viability measurement Theory: Cells with intact plama membranes act like tiny capacitors under the influence of electric field. The nonconducting nature of plasma membranes allows charge to build up. The resulting capacitance can be measured and is usually expressed in picofarad per centimeter (pF/cm). It depends on the cell type and is directly proportional to membrane bound volume of viable cells.
24. Feedback and Feedforward controllers Feedback control:A control algorithm to reduce the error between the set point and the controlled variable (most often PID or model predictive controller algorithm is used) Feedforward control: A computation of the manipulated variable from a measurement of the disturbance (most often corrected by a PID or model predictive controller)