lecture 3 bioprocess control

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14 th . July 2010 CEPP, UTM Skudai, Johor Prof. Dr. Hesham A. El Enshasy Faculty of Chemical Engineering CEPP, UTM, Skudai, Malaysia Bioprocess Control (On-line, off-line and in-line)

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Page 1: Lecture 3  bioprocess control

14th. July 2010CEPP, UTM Skudai, Johor

Prof. Dr. Hesham A. El EnshasyFaculty of Chemical Engineering

CEPP, UTM, Skudai, Malaysia

Bioprocess Control(On-line, off-line and in-line)

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Parameters for measurements and control for cultivation system

Cell Input and Cell out-put (conditions and nutrients requirements)

Sensors used for bioreactors

Main Items of Presentation

Feed back loops for bioprocess control

Summary screen for different control system

SCADA system for control using ethernet platform

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Cell In-put and Cell Out-put

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CELL

Oxygen

Carbon and Energy

Sources

Nitrogen Source

Other requirements(P, S,Na,K,Mg,etc…)

Carbon dioxide

Biomass

Metabolite(s)

Water

Heat

Substrate(s) Input and Output

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Physical Chemical Biological - Temperature- Bioreactor Pressure (St. St. Bioreactors)- Agitation Speed- Gas Flow rate - Total volume- Feeding rate- Power Input- Foam

- pH- Dissolved oxygen

- Cell Morphology- Cell viability- Optical Density - Cell Dry weight- Cellular composition- Specific growth rate- Specific substrate(s) consumption rates. - Specific production rate

- Reactor weight- Feeding tank weight- Culture Viscosity- Gas Hold up - Gas Mixing pattern

- Dissolved carbon dioxide- Redox potential- Out gas analysis (O2, CO2, N2)- Substrate(s)- Product(s)- Enzyme activities- Volatile compounds- Conductivity - Biomass composition (C,H,O,N,P,S)- Metabolite profiling- Mineral Ions

- Oxygen uptake rate- Carbon dioxide production rate- RQ- Growth inhibitors - Protein - DNA / RNA- ATP / ADP / AMP

Different Parameters for cultivation system

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Integrated of Mathematical Methods for Advanced Process Control Ref. (Clementschitsch and Bayer. Microbial Cell Factories 5:19 (2006)

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Input and Output of Bioreactor system (General overview)

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Main in situ sensors used for measuring cultivation parameters

Culture parameters Sensor Range Accuracy

Temperature Pt-100 0-150C 0.1C

Pressure Piezoresistor 0-2 bar 20 mbar

Gas flow Thermal mass flow meter

Upto 2 v v-1 minBased on bioreactor volume

0.1%

pH pH electrode 2-12 0.02

pO2 Polarografic electrode

0-400 mbar 2 mbar

pCO2 Membrane covered pH electrode

0-100 mbar 2 mbar

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Feed pump(s)

Temperature

Aeration

Power consumption

Stirrer Speed

Exhaust gasAnalyzer

pH

DO

Pressure

Weight / volume

Measurement and open or closed loop control

Measurement only

Common measurement and control of bioreactors as generally accepted as routine equipment

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Lower ports for in situ sterilizable STR

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Applicationmeasurement

Lower ports Upper ports Headplate ports

Temp./pH/DO/ DCO2/ Turbidity probes/substrate (s) on-line

+ (for pilot scale bioreactors)

- + (only for small scale bioreactors / Glass bioreactors)

Pressure gauge orPressure sensor

- - +

Line to outgas analysis - - + (after condenser and out-gas fileter)

Feeding / acid-based / Antifoam addition

- Highly suitable(Small scale pilot)Less Suitable (Large scale)

Highly suitable(Large scale)Less Suitable (Small scale pilot)

Harvest (Continuous Culture)(Repeated batch)

+ - -

Sampling + - -

Upper/lower ports and Headplate

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pH values of different liquids

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pH and hydrogen ion concentration

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pH measuring circuit and pH meter construction

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Temperature Effect on pH value

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Temperature Error Table

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DO meter construction

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The relation between DO and Temperature

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Standard Antifoam Sensor

Foam sensors: Low foam sensor High foam sensor

Type of foam: Early foaming Late foaming

Antifoam effects on: DO Growth morphology (Filamentous MO)

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On-line cell mass determination methods

Principle Advantages Disadvantages

Optical density Wide linear range Some interference

Culture fluorescence Measurement of cellular activity

Singanal interpretation is difficult

Capacitance Wide measurement range

Measurement of cellular activity

Interferance from aeration and aerationSignal interpretation is difficult

Ultrasonic Wide linear range

Self cleaning

Interference from aeration and agitationTemperature sensitive

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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.

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Stat-culture Sensor Controlled variables

pH-Stat pH electrode (online) Acid-based

DO-Stat DO electrode (online) AerationAgitationOxygen (optional)

Nutri-Stat(Chemo-Stat)

nutrient sensor (on-line), Off-line analyzer (online), FIA (online)

Feeding substrate (s)

Turbidistat Turbidity meter (online) Feeding substrate(s)Harvest pump

QO2 and QCO2 Stat

Out-gas analyzer (in-line)

AerationAgitationOxygen (Optional)Feeding substrate(s)

Controlling stat-culture

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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)

Feedback and Feedforward controllers

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Basic feedback loops for a fungal culture for antibiotic production

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Basic feedback loops for microbial high cell density formation

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Bioreactor Input and Output for basic PID control feed

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Connections to USB, controller software and Ethernet for SCADA

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Supervisory Control and Data Acquisition syste (SCADA)

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Thank You