ICAS-PAT manual for Design of process monitoring and ... - CAPEC

ICAS-PAT manual
for
Design of process monitoring and analysis systems
(PAT systems)
Ravendra Singh, Krist V. Gernaey, Rafiqul Gani
June 2009
Product & process
specifications
Provided by user
Fixed process
(without monitoring & control system)
Variant product quality
Process analysis
Performance
analysis of
monitoring tools
ICAS-PAT
Sensitivity
analysis
Interdependency
analysis
C
Consistent predefined
product quality
M
Flexible process
(Designed monitoring & control system)
Knowledge base
Knowledge/data
Model library
Department of Chemical and Biochemical Engineering
Technical University of Denmark
2800 Kgs. Lyngby, Denmark

Contents .................................................................................................................Page no.
1. Introduction................................................................................................................. 2
1.1. Prerequisites........................................................................................................ 2
1.2. Registration of COM object................................................................................ 2
1.3. Precheck.............................................................................................................. 2
2. Main interface ............................................................................................................. 2
2.1. Open solved example.......................................................................................... 2
2.2. Find applications of monitoring tools................................................................. 3
2.3. Retrieve knowledge/data..................................................................................... 4
2.4. Problem specific supporting tools....................................................................... 6
2.4.1. Problem specific knowledge base............................................................... 6
2.4.2. Problem specific model library................................................................... 7
2.4.3. Problem specific interface........................................................................... 7
3. Design of process monitoring and analysis systems (PAT systems).......................... 9
3.1. Product quality specifications (Step 1) ............................................................. 10
3.2. Process specifications (Step 2).......................................................................... 10
3.3. Process analysis (Step 3)................................................................................... 12
3.4. Sensitivity analysis (Step 4).............................................................................. 13
3.5. Interdependency analysis (Step 5) .................................................................... 16
3.6. Performance analysis of monitoring tools (Step 6)........................................... 19
3.7. Proposed process monitoring and analysis system (Step 7) ............................. 22
3.8. Validation (Step 8)............................................................................................ 22
3.9. Final process monitoring & analysis system (Step 9)....................................... 26
4. Data management...................................................................................................... 27
4.1. Save workbook.................................................................................................. 27
4.2. Build report in MS Word .................................................................................. 27
Appendix A: report generated in MS Word...................................................................... 29
1

1. Introduction
1.1. Prerequisites
• PAT_Prototype.xls, user interface, as an excel file
• knowledge base.xls, knowledge base, as an excel file
• Model library containing the MoT files
• MoT_Model_Interface.xls, MoT excel interface, as an excel file
• Installed ICAS in the computer
1.2. Registration of COM object
Double click on the bat file named, RegCOMMoT.bat in the bin folder:
C:\CAPEC\ICAS\bin
1.3. Precheck
Make sure that macros are allowed in the excel file. If this is not the case, the following
steps are needed to allow the use of macros in excel:
• On the Tools menu, click Options.
• Click the Security tab.
• Under Macro Security, click Macro Security.
• Click the Security Level tab, and then select the medium security level.
2. Main interface
Open the file, PAT_Prototype.xls, and allow the macros to run. The main interface of
ICAS-PAT is shown in Figure 1. Different features of ICAS-PAT are described as
follows:
2.1. Open solved example
To load a previously solved example click on the command button, “Open solved
example”, (see Figure 1, top, right) and follow the instructions. Solved examples are
saved in the folder PAT\result.
2

Figure 1: Main interface of ICAS-PAT
2.2. Find applications of monitoring tools
Click on command button, “Find applications of monitoring tools” (see Figure 1, top,
right) to find the applications of monitoring tools. This action will open a new window as
shown in figure 2. The following steps need to be taken to find the applications of
monitoring tools:
2.2.1 Write the path of the directory containing the knowledge base (e.g.
D:/PAT/knowledge base.xls) in the provided text box (the browse option can be
used to search the file and copy the directory) and click on the command button,
“Activate knowledge base”.
2.2.2 Click on the command button, “Type/select monitoring technique”, and select a
monitoring technique from the adjacent drop-down list.
2.2.3 Click on the command button, “Select monitoring tools”, and select monitoring
tools from the adjacent drop-down list (note that, multiple selections are possible).
2.2.4 Click on the command button, “Find applications”, to list the applications of
selected monitoring tools. Result will be listed in the same window as shown in
figure 2 (all applications are not shown in the figure because of space limitations).
2.2.5 Click on the command button, “Main interface”, to return to main interface.
3

Figure 2: Find applications of monitoring tools, user interface (left) with a part of result (right)
2.3. Retrieve knowledge/data
Click on command button, “Retrieve the knowledge/data” (see Figure 1, top, right) to
access the direct search engine. This action will open a new window as shown in Figure
3. The following steps need to be taken to search the knowledge/data:
2.3.1. Write the path of the directory containing the knowledge base (e.g.
D:/PAT/knowledge base.xls) in the provided text box (the browse option (not
shown in figure) can be used to search the file and copy the directory) and click on
the command button, “Load knowledge base”.
2.3.2. Click on the command button, “Select process”, and select a process from the
adjacent drop-down list.
2.3.3. Click on the command button, “Select process points”, and select process points
from the adjacent list box (note that, multiple selections are possible). There are 3
additional options (‘Select all’, ‘Not found’ and ‘Do not know’) that can be
selected if needed.
4

2.3.4. Tick the box “Actuator candidates” (see Figure 3, left), if actuator candidates
also need to be retrieved.
2.3.5. Click on the command button, “Select process variables”, this action will retrieve
the process knowledge as shown in Figure 3 (see result selection). If the user is
only interested in retrieving process knowledge then there is no need to proceed
further, but if the user wants to retrieve the knowledge on measurement methods
and tools also then the next steps need to be followed as well.
2.3.6. Select process variables from the list box (adjacent to command button, “Select
process variables”) and also select the corresponding variable type from the list
box just below the list box containing the process variables.
2.3.7. Click on the command button, “Select monitoring techniques”, and select
monitoring techniques from the adjacent list box (note that, multiple selections are
possible).
2.3.8. Click on the command button, “Select monitoring tools”, and select monitoring
tools from the adjacent list box (note that, multiple selections are possible).
2.3.9. Click on the command button, “Select specifications”, and select specifications
from the adjacent list box (note that, multiple selections are possible).
2.3.10. Tick the box “Suppliers” (see Figure 3, bottom, left), if information on
equipment suppliers also needs to be retrieved.
2.3.11. Click on the command button, “Search specifications &/or suppliers of
monitoring tools”, to retrieve the process knowledge and knowledge on
measurement methods and tools.
2.3.12. Click on the command button, “Main interface”, to return to the main interface.
5

Figure 3: Knowledge/data retrieval system, user interface (left) with example of a result on the right
(only process knowledge is shown)
2.4. Problem specific supporting tools
For new problems, the problem specific supporting tools (knowledge base & model
library) need to be created first before the problem specific interface can be accessed,
while for existing problems, the user can move directly to the problem specific interface
(see Figure 1) and can go through each design step.
2.4.1. Problem specific knowledge base
The following steps need to be taken to create the problem specific knowledge base (see
Figure 1, left):
• Write the path of the directory containing the knowledge base (e.g.
D:/PAT/knowledge base.xls) in the provided text box (the browse option can be used
to search the file and copy the directory) and click on the command button, “Load
knowledge base”.
• Click on the command button, “Select process”, and select a process from the
adjacent drop-down list.
6

• Click on the command button, “Select process points”, and select process points from
the adjacent list box (note that, multiple selections are possible).
• Click on the command button, “Problem specific knowledge base”, to create a
problem specific knowledge base.
2.4.2. Problem specific model library
The following steps need to be taken to create the problem specific model library (see
Figure 1, left, bottom):
• Write the path of the directory containing the model library (e.g. D:/PAT/model
library.xls) in the provided text box (the browse option can be used to search the file
and copy the directory) and click on the command button, “Load model library”.
• Select the process models from the left list box and click on the command button,
“Add to problem specific model library”, to add the selected process model to the
right list box. This action will open the corresponding process model and the user
needs to save it in a folder named ‘problem specific model library’.
After creating the problem specific supporting tools, Click on the command button,
“Problem specific interface”, to proceed with the design of a PAT system.
2.4.3. Problem specific interface
Click on the command button, “Problem specific interface”, for design of PAT systems.
This action will open a new window containing all the design steps as shown in Figure 4.
Each design step needs to be followed sequentially in order to get the final PAT system.
As described in section 3 of this manual, each design step consists of a separate window
through which the input information can be provided and the output information can be
accessed.
7

Figure 4: Problem specific interface (steps for design of a PAT system)
8

3. Design of process monitoring and analysis systems (PAT systems)
The application of ICAS-PAT for design of a PAT system is demonstrated in this manual
through a fermentation process case study. The flowsheet of the fermentation process is
shown in Figure 5.
Figure 5: Fermentation process flowsheet
9

3.1. Product quality specifications (Step 1)
The following steps need to be taken in this phase of the design procedure (see Figure
6):
3.1.1. Click on the command button “1. Product quality specifications”
3.1.2. Write the number of products in the allocated place (cell C5 of the spreadsheet).
3.1.3. Click on the command button, “Next” and write the name of the products in the
allocated place (starting from cell C6 of the spreadsheet).
3.1.4. Click on the command button, “List the specifications” and type the
specifications of each product in the allocated place.
After completing Step 1, click on the command button “2. Process specifications” to
proceed to the next step of the design procedure.
Figure 6: Product quality specifications
3.2. Process specifications (Step 2)
The following steps need to be taken in this phase of the design procedure (see Figure
7):
3.2.1. Write the path of the directory containing the knowledge base (e.g.
D:/PAT/knowledge base.xls) in the provided text box (the browse option can be
used to search the file and copy the directory of file) and click on the command
button, “Load Knowledge base”.
3.2.2. Click on the command button, “Select the process” and select the process from
the drop-down list for which the PAT system has to be designed. Select the option
‘Not found’, if the process is not found in the list.
10

3.2.3. Click on the command button, “Next” and write the number of equipments used in
the process, in the spreadsheet cell that is reserved for that information. Write the
number of raw materials used in the process in the appropriate place and write the
name of each raw material under the heading, Raw material list.
3.2.4. Click on the command button, Select equipments and select the equipments from
the drop-down list. Select the option ‘Not found’ for further instruction, if any
equipment is not found in the list. The selected number of equipments must be
equal to the number of equipments specified in step 3.2.3.
3.2.5. Generate flowsheet: The open loop process flowsheet can be generated through
ICAS-PAT (see Figure 7, top, right corner). The following steps need to be taken
to generate the simplified process flowsheet:
• Click on command button, “Provide input/output information” and provide the
input/output information of the process as shown in Figure 8. Type the name of the
equipments, the corresponding operations, and the input/output streams under the
specified headings. Leave blanks, if some options are not applicable.
• Click on command button, “Draw flowsheet” to generate the flowsheet, as shown in
Figure 9.
After completing Step 2, click on the command button “3. Process analysis” to go to the
next step of the procedure.
Figure 7: Process specifications
11

Equipments Operations Main stream in Side stream in Main stream out Side stream out
Mixing tank Mixing Mixed media Water Mixed media
Media
Heat sterilizer Heat sterilization Sterilized media
Fermentor Fermentation Ammonia Biomass Air
Air
Figure 8: Input/output information to draw the flowsheet (fermentation process)
Water
Mixing tank
Heat sterilizer
Ammonia
Fermentor
Air
Media
Air
Mixing
Heat sterilization
Fermentation
Biomass
Figure 9: Generated flowsheet (fermentation process)
3.3. Process analysis (Step 3)
The following steps need to be taken in this phase of the design procedure (see Figure
10):
3.3.1. Click on the command button, “List the process points”.
3.3.2. Write the path of the directory containing the knowledge base (e.g.
D:/PAT/knowledge base.xls) in the provided list box (the browse option can be
used to search the file and copy the directory of file) and click on the command
button, “List the variables related to each process point”.
3.3.3. Process variables are user specific. Thus, the user has to check each listed process
variable thoroughly, and modify the list if needed (remove the unnecessary
variables from the list, or add extra variables if required. Note that no empty
(blank) cells should be left between the variables).
3.3.4. Write the values of the lower and the upper operational limit, and add the unit of
each listed variable in the place reserved for that information. The user can refer to
a data sheet (data_sheet.xls) to access this information.
After completing Step 3, click on the command button “4. Sensitivity analysis” to
proceed to the next step of the design procedure.
12

Figure 10: Process analysis
3.4. Sensitivity analysis (Step 4)
If process operational data are already available (either from experiments or based on a
simulation), then load the saved data by clicking on the command button, “Load the
saved data (open loop)” (see Figure 11), and skip the steps 4.2 to 4.3. If the process
operational data are not available then the following steps need to be taken (see Figure
11):
3.4.1. Click on the command button, “Select a process point”, and select a process point
from the adjacent drop-down list. Click on the command button, “Select the
operational objective”, and select the operational objective from the adjacent
drop-down list. Type the operational objective, if the desired objective is not found
in the list (the operational objective is the objective that the user wants to achieve in
the selected operation).
3.4.2. Write the path of the directory containing the file MoT_Model_Interface.xls (e.g.
D:/PAT/MoT_Model_Interface.xls) in the provided list box (the browse option can
be used to search the file and copy the directory of file). Then click on the
command button, “Solve the model”. This step will direct the user to a new excel
workbook named, MoT_Model_Interface.xls (see Figure 12):
• Click on the command button, “Load MoT Model”. This step will open a
browsing window (see Figure 12, right).
• Browse the model (models are saved in the folder PAT/Model library) and load
the model details in to the excel sheet (see Figure 12, left).
13

• Click on the command button, file name.mot to solve the model. The final value
of the variables are shown in Figure 12 (highlighted with red color) and the
whole dynamic simulated data is stored in a different file.
• Activate the workbook (maximize the window), PAT_Prototype.xls
3.4.3. Click on the command button, “Load simulation result” .
3.4.4. Click on the command button, “Select variable”. To analyze the objective
function, select the X axis (independent) variable (usually, ‘Time’ should be
selected as a X axis variable) and Y axis variable (objective function) from the
drop-down list and select the corresponding symbol of the selected variable
(objective function) from the drop-down list.
3.4.5. Click on the command button, “Operational limits of selected variable”.
3.4.6. To plot the selected variable (operational objective), click on the command button,
“Plot”. If the operational objective is not achieved (if it violates the limits), then
the next step in the procedure needs to be followed.
3.4.7. Select a process variable and corresponding symbol from the drop-down list
(similarly as mentioned in step 4.4), specify operational limits (similarly as
mentioned in the step 4.5) and plot the result (see Figure 11 for an example of the
result of this operation).
3.4.8. Click on the command button, “Analyze the selected variable”. This command
will open a message box. Select ‘Yes’ if the variable violates the operational limit
and ‘No’ if it is within the operational limit.
3.4.9. Repeat steps 4.7 and 4.8 for each process variable involved with the selected
process point. The result of this step is stored in the result section (see Figure 11,
right).
Open loop simulation data management
• To save the open loop simulation data, write the path of the directory where the
data has to be saved and click on the command button, “Save the open loop
simulation data” (see Figure 11).
• To load the saved data click on the command button, “Load the saved data (open
loop)” (see Figure 11). Follow the steps 4.4 to 4.9 for sensitivity analysis based on
the saved data.
14

After completing step 4 for the selected process point, click on the command button “5.
Interdependency analysis” to proceed to the next step of the design procedure.
Figure 11: Sensitivity analysis
15

Figure 12: MoT model interface
3.5. Interdependency analysis (Step 5)
The following steps need to be taken in this phase of the design procedure (see Figure
13a):
3.5.1. Click on the command button, “Select a process point”, and select a process point
from the adjacent drop-down list (note that the process point selected in this step
must be identical to the process point selected in Step 4).
3.5.2. Selection of actuator candidates:
3.5.2.1. Click on the command button, “Select a critical process variable”, and select a
critical process variable (or select all) from the adjacent drop-down list.
3.5.2.2. Click on the command button, “List the actuator candidates”. This command
will list the actuator candidates for the selected critical process variable. Note
that this list provides the actuator candidates to the user based on data available
16

in the knowledge base. However, the user can modify this list according to
his/her needs.
3.5.2.3. Click on the command button, “Select critical variables”, and select critical
process variables from the list box, containing unknown variables (the effect of
actuator candidates on these variables has to be studied).
3.5.2.4. Click on the command button, “Select actuator candidates”, and select actuator
candidates from the list box containing known variables and parameters.
3.5.3. Perturbation: If the interdependency analysis data are already available (either
from experiments or based on a simulation) then load the saved data by clicking on
the command button, “Load the saved data (interdependency analysis)” (see
Figure 13a, left) and skip the step 3.5.3.1:
3.5.3.1. Perturbation setup: type the values of the lower and upper bound as well as the
step for perturbing the actuator candidates (an example is given in Figure 13b,
where the lower bound of the perturbation corresponds to -15% and the upper
bound corresponds to +15%, whereas the step size for modifying the perturbation
is 5%). Click on the command button, “Performed interdependency analysis”.
This command will perturb the actuator candidates and record the effect of the
perturbation on selected critical process variables.
3.5.3.2. Click on the command button, “Select critical variable”, and select the variable
from the drop-down list for which you want to see the result. Make sure that the
critical process variable selected in step 3.5.2.1 is the same as the one selected in
this step. If this is not the case then select the same variable in step 3.5.2.1 also.
3.5.3.3. Click on the command button, “Result” , to see the result (in table form). To plot
the result click on the command button, “Plot” and analyze the result to identify
the most sensitive actuator candidate (see Figure 13b).
3.5.4. Click on the command button, “Select actuator”, and select the most sensitive
actuator candidate as the final actuator for the selected variable.
3.5.5. Repeat steps 3.5.2 – 3.5.4 for each critical process variable involved with the
selected critical process point. Result of this step is stored in the result section (see
Figure 13b, right).
17

Data management (interdependency analysis)
• To save the interdependency analysis data, write the path of the directory where
the data has to be saved and click on the command button, “Save simulation data
(interdependency analysis)” (see Figure 13a).
• To load the saved data click on the command button, “Load the saved data
(interdependency analysis)” (see Figure 13a).
After completing step 5 for the selected process point, click on the command button “6.
Performance analysis of monitoring tools” to proceed to the next step of the design
procedure.
Figure 13a: Interdependency analysis
18

Figure 13b: Interdependency analysis
3.6. Performance analysis of monitoring tools (Step 6)
The following steps need to be taken in this phase of the design procedure (see Figure
14):
3.6.1. Click on the command button, “Select a process point”, and select a process
point from the adjacent drop-down list (note that the process point selected in this
step must be identical to the process point selected in Step 4).
3.6.2. Click on the command button, “Select a critical process variable”, and select a
critical process variable (or select all) from the adjacent drop-down list (see
Figure 14). Follow steps 3.6.2.1-3.6.2.2:
3.6.2.1. Tick on the performance criteria of the monitoring tools that you want to list (see
Figure 14)
3.6.2.2. Click on the command button, “List the monitoring tools” (see Figure 14). This
command will generate a table containing the monitored variable, monitoring
techniques, monitoring tools and corresponding specifications. The user can
modify this table according to his/her needs.
19

3.6.3. Grading of monitoring tools: select the variable from the drop-down list (or select
all) and Click on the command button, “Grade the monitoring tools” (see Figure
14). This command will assign a grade in the range 5 to 1 to the top 5 monitoring
tools in the category of the selected specification, whereas the rest of the tools
will get the grade zero. Note also that in case the value of any specification of a
monitoring tool is not assigned (e.g. because no information was available in the
literature, then that monitoring tool will automatically get the grade zero (see
Figure 15).
3.6.4. Selection of monitoring tool: select a critical process variable (or select all) from
the drop-down list and follow steps 6.4.1-6.4.2 (see Figure 14):
3.6.4.1.Click on the command button, “Select performance criteria” and select the
criteria on the basis of which the monitoring tool has to be selected. Note that the
choice of the final selected monitoring tools will depend on the selected
performance criteria!
3.6.4.2.Click on the command button, “Select monitoring tool”.
3.6.5. Repeat step 3.6.2-3.6.4 for each critical process variable involved with the
selected critical process point. Result of this step is stored in result section (not
shown).
After completing the step 6 for the selected process point, click on the command button
“7. Proposed process monitoring and analysis system” to proceed to the next step of
the design procedure.
20

Figure 14: Performance analysis of monitoring tools
Figure 15: Grading of monitoring tools
21

3.7. Proposed process monitoring and analysis system (Step 7)
Click on the command button, “Propose a process monitoring and analysis system”.
This command creates a table containing the critical process points, the critical process
variables, the selected actuators, monitoring techniques and monitoring tools (see Figure
16).
After completing step 7 for the selected process point, click on the command button “8.
Validation” to proceed to the next step of the design procedure.
Figure 16: Proposed process monitoring and analysis system
3.8. Validation (Step 8)
If the process operational data (closed loop) are already available (either from
experiments or based on a simulation), then load the saved data by clicking on the
command button, “Load the saved data (closed loop)” (see Figure 17, bottom left) and
skip the steps 3.8.2 to 3.8.5. If the process operational data are not available then the
following steps need to be taken in this phase of the design procedure (see Figure 17):
3.8.1. Click on the command button, “Select a process point”, and select a process
point from the adjacent drop-down list (note that the process point selected in this
step must be identical to the process point selected in step 4).
3.8.2. Click on the command button, “Select the control variable” and select the
control variable from the drop-down list.
3.8.3. Click on the command button, “Select the actuator” and select the actuator from
the drop-down list. Follow steps 3.8.3.1-3.8.3.3 for setting of controller
parameters.
22

3.8.3.1. Click on the command button, “Select the control parameters” and select the
controller parameters from the drop-down list. A message box, asking whether
the user wants to select the default value of the controller parameters will
appear, on selection of controller parameters. The value of controller parameters
will be assigned automatically, if the user will accept the default option.
Otherwise the user needs to type the value of the controller parameters in the
provided text box. Note that only a PI & on-off controller is implemented at this
moment, so the derivative controller constant K D is always set equal to zero. For
on-off controller K switch =0 means open loop and K switch =1 means closed loop.
3.8.3.2. Click on the command button, “Activate the loop”. Similarly the command
button “Deactivate the loop” can be used to deactivate the unwanted control
loop.
3.8.3.3. Repeat the above steps 3.8.2-3.8.3 for all control loops (as a rule of thumb, the
number of control loops should be equal to the number of critical process
variables).
3.8.4. Click on the command button, “Solve the closed loop model”.
3.8.5. Click on the command button, “Load simulation result”.
3.8.6. Click on the command button, “Select variable” and select a critical process
variable that you want to plot. Also select the corresponding set point and
actuator.
3.8.7. Click on the command button, “Operational limit of selected variable”. This
command will provide the lower and upper limit of the critical process variable
(note that the user can modify this limit). The user can also specify the limit of the
actuator in the cells allocated for that information.
3.8.8. To see the result, click on the command button, “Plot”. The closed loop response
of two variables (dissolved oxygen and pH) are shown in Figure 18 as an
example. Actuator plots are not shown.
3.8.9. To analyze the variable, click on the command button, “Analyze the selected
variable” and follow the instructions. If the set point of the controlled variable is
achieved and the actuator is within the limit, then this control variable-actuator
pair can be selected for the final design. As shown in Figure 18 dissolved oxygen
23

and pH are within the limits and corresponding actuators are also within the limits
(not shown).
3.8.10. Repeat steps 3.8.6-3.8.9 for all critical process variables involved with the
selected critical process point.
3.8.11. Sensitivity verification: to analyze the relative sensitivity of the controlled
variable follow the following steps (see Figure 19):
3.8.11.1. Click on the command button, “Select objective function” and select the
operational objective from the adjacent list box (for instance cell growth rate
(mue) is selected as the operational objective in fermentation process).
3.8.11.2. Click on the command button, “Select control variable (set point)” and select
the controlled variables (set points) from the adjacent list box (for instance
dissolved oxygen (DO_set), pH, pH_set, and temperature (T_set) are selected as
the controlled variables).
3.8.11.3. Perturbation setup: type the values of the lower and upper bound as well as the
step for perturbing the control variables (set points) (an example is given in
Figure 19, where the lower bound of the perturbation corresponds to -4% and
the upper bound corresponds to +4%, whereas the step size for modifying the
perturbation is 2%).
3.8.11.4. Click on the command button, “Sensitivity verification”. This command will
perturb the controlled variables (set points) and record the effect of the
perturbation on the objective function.
3.8.11.5. Click on the command button, “Select objective function”, and select the
objective function from the drop-down list.
3.8.11.6. Click on the command button, “Result” , to see the result (in table form). To
plot the result click on the command button, “Plot” and analyze the result. If the
sensitivity of the proposed controlled variable is negligible then it should not be
included in the final list of the PAT system. Figure 19 shows the relative
sensitivity of the cell growth rate (objective function) w.r.t. dissolved oxygen,
pH and temperature (controlled variables). The Figure shows that the cell
growth rate is most sensitive for dissolved oxygen followed by pH and
temperature.
24

Closed loop simulation data management
• To save the closed loop simulation data, write the path of the directory where the
data has to be saved and click on the command button, “Save the closed loop
simulation data” (see Figure 17).
• To load the saved data click on the command button, “Load the saved data
(closed loop)” (see Figure 17). Follow the steps 3.8.6 to 3.8.11 for validation
based on the saved data.
After completing step 8, click on the command button “9. Final process monitoring &
analysis system” to proceed to the next step of the design procedure.
Figure 17: Validation
0.008
DO (Dissolved oxygen)
9
pH
0.007
8
O(Kg/m3)
0.006
0.005
Achieved profile
Lower limit
0.004
Upper limit
0.003
Set points
0.002
0.001
0
0 3 6 9 12 15 18
Time (hr)
pH
Figure 18: Closed loop response of variables
7
6
5
4
Achieved profile
3
Lower limit
2
Upper limit
1
Set points
0
0 3 6 9 12 15 18
Time (hr)
25

Figure 19: Sensitivity verification
3.9. Final process monitoring & analysis system (Step 9)
The following steps need to be taken in this phase of the design procedure (see Figure
20):
3.9.1. Click on the command button, “Process monitoring & analysis system”. This
command will create a table containing the critical process points, critical process
variables, actuators, monitoring techniques and monitoring tools as shown in
Figure 20.
3.9.2. Repeat step 1-8 for each process point.
3.9.3. Draw flowsheet: follow the following steps to generate a process flowsheet with
designed PAT system.
• Click on the command button, “Select specifications”, and select the
specifications from the adjacent list box (see Figure 20) that you want to include
in the flowsheet.
• Click on the command button, “Draw flowsheet”, to draw the flowsheet, as
shown in Figure 21.
26

4. Data management
The Following options are available for data management:
4.1. Save workbook
• Write the directory name where you want to save the workbook and click on the
command button, “Save the workbook”.
• Save the result of each analysis step: write the name of the directory where you
want to save the result and click on the command button, “Save the result”.
4.2. Build report in MS Word
Click on the command button, “Build report in MS Word” to make a report in MS
Word as given in Appendix A.
Figure 20: Final process monitoring & analysis system
27

Feed
Mixing tank
Mixing time
Homogeneity
C
RT= 00.002000 s
Pr= 0.100000 nm
Ac= 0.100000 nm
NIR
Stirrer speed
Coolant flow rate
Flow rate of NH3
Air flow rate
C
C
Sterilizer
Steam flow rate
Main stream
temperature
C
RT= 150.000000
Pr= 0.003000 oC
Ac= 0.400000 % of
Thermistor
Fermentor
DO (Dissolved
oxygen)
pH
Temperature
Homogeneity
RT= 1.000000 s
Pr= 0.100000 '%
Ac= 0.100000 % FS
Optical
sensor
RT= 10.000000 s
Pr= 0.003000 pH
Ac= 0.200000 pH
Electroche
mical
Figure 21. Process monitoring and analysis system for the fermentation process.
c: controller, Ac: Accuracy, Pr: Precision, RT: response time
C
C
RT= 150.000000
Pr= 0.003000 oC
Ac= 0.400000 % of
Thermistor
RT= 00.002000 s
Pr= 0.100000 nm
Ac= 0.100000 nm
NIR
Product
28

Appendix A: report generated in MS Word
Design of process monitoring and analysis system (PAT system)
Step1: Product quality specifications
1. Specifications of Biomass Value Unit
Composition 2.95 % (w/w)
Concentration 30.00 g/l
2. Specifications of Glucose Value Unit
Composition 4.00 % (w/w)
Concentration 40.69 g/l
3. Specifications of Salts Value Unit
Composition 0.58 % (w/w)
Concentration 5.93 g/l
4. Specifications of Water Value Unit
Composition 92.46 % (w/w)
Concentration 939.44 g/l
Step2: Process specifications
Equipment list
Fermentor
Sterilizer
Mixing tank
Raw material list
Starter culture
Glucose
Salts
Water
Ammonia
Air
Step3: Process analysis
Process points Process variables Lower limit Upper limit Unit
Fermentor DO (Dissolved oxygen) 0.00067 0.007 Kg/m3
Dissolved CO2 0.0005 0.004 Kg/m3
pH 6 7
Temperature 293 310 K
Pressure 1 2 atm
Inlet flow rate of air 0 10 m/s
Outlet flow rate of air 0 10 m/s
Inlet flow rate of NH3 0 10 m/s
Outlet flow rate of NH3 0 10 m/s
Substrate concentration 1 180 Kg/m3
Biomass concentration 1 30 Kg/m3
29

Cell mass 30 900 kg
Foaming level 0 0.01 m
Stirrer speed 0 10 rps
Cell growth rate 0.1 0.15 hr-1
Homogeneity 0.7 1 fractional
homogeneous
Sterilizer Steam temperature 120 200 oC
Main stream temperature 120 150 oC
Main stream flow rate 300 700 Kg/hr
Steam flow rate 0 1000 Kg/hr
Sterilization duration 0 7 hour
Mixing tank Stirrer speed 0 36000 rps
Step4: Sensitivity analysis
Mixing time 0 3 hour
Homogeneity 0.95 1 Fractional
homogeneous
Critical process points
Mixing tank
Sterilizer
Fermentor
Fermentor
Fermentor
Fermentor
Fermentor
Critical process variables
Homogeneity
Main stream temperature
DO (Dissolved oxygen)
pH
Dissolved CO2
Temperature
Homogeneity
Step5: Interdependency analysis
Critical process points Critical process variables Actuators
Mixing tank Homogeneity Mixing time
Sterilizer Main stream temperature Steam flow rate
Fermentor DO (Dissolved oxygen) Air flow rate
Fermentor pH Flow rate of NH3
Fermentor Dissolved CO2 Air flow rate
Fermentor Temperature Coolant flow rate
Fermentor Homogeneity Stirrer speed
Step6: Performance analysis of monitoring tools
Critical points Critical variables Monitoring Monitoring tools
techniques
Mixing tank Homogeneity NIR EPP 2000 Fiber Optic Spectrometer-
NIR2
Sterilizer Main stream
temperature
Thermistor DO-35 Interchangeable Thermistor --
103JL1A
Fermentor DO (Dissolved
oxygen)
Optical sensor FOXY Sensor System
30

Fermentor pH Electrochemical Electrochemical sensor
sensor
Fermentor Dissolved CO2 Optical sensor Optical sensor
Fermentor Temperature Thermistor DO-35 Interchangeable Thermistor --
103JL1A
Fermentor Homogeneity NIR EPP 2000 Fiber Optic Spectrometer-
NIR2
Fermentor DO (Dissolved
oxygen)
Optical sensor FOXY Sensor System
Step7: Proposed process monitoring and analysis system
Critical
process points
Critical process
variables
Actuators
Mixing tank Homogeneity Mixing
time
Sterilizer Main stream Steam flow
temperature rate
Fermentor DO (Dissolved Air flow
oxygen)
rate
Fermentor pH Flow rate
of NH3
Fermentor Dissolved CO2 Air flow
rate
Fermentor Temperature Coolant
flow rate
Fermentor Homogeneity Stirrer
speed
Monitoring
techniques
NIR
Thermistor
Optical sensor
Electrochemical
sensor
Optical sensor
Thermistor
NIR
Monitoring tools
EPP 2000 Fiber Optic
Spectrometer-NIR2
DO-35 Interchangeable
Thermistor -- 103JL1A
FOXY Sensor System
Electrochemical sensor
Optical sensor
DO-35 Interchangeable
Thermistor -- 103JL1A
EPP 2000 Fiber Optic
Spectrometer-NIR2
Step9: Final process monitoring and analysis system
Critical process Critical process Actuators Monitoring Monitoring tools
points
variables
techniques
Mixing tank Homogeneity Mixing time NIR EPP 2000 Fiber Optic
Spectrometer-NIR2
Sterilizer Main stream
temperature
Steam flow
rate
Thermistor DO-35 Interchangeable
Thermistor -- 103JL1A
Fermentor DO (Dissolved Air flow Optical FOXY Sensor System
oxygen) rate sensor
Fermentor pH Flow rate Electrochemi Electrochemical sensor
of NH3 cal sensor
Fermentor Temperature Coolant
flow rate
Thermistor DO-35 Interchangeable
Thermistor -- 103JL1A
Fermentor Homogeneity Stirrer
speed
NIR EPP 2000 Fiber Optic
Spectrometer-NIR2
31