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Claims  |
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We claim:
1. In a processing plant having a plurality of processes performed by a
plurality of process means in a certain pattern to provide manufacturing
operations, control apparatus comprising:
a multiplicity of sensors coupled to a plurality of process means which
provide manufacturing operations, each sensor providing signals indicative
of current state of a respective process means;
a digital processor assembly coupled to the sensors for receiving the
sensor signals;
a video display coupled to the digital processor assembly;
control means coupled to the plurality of process means; and
computer means supported by the digital processor assembly for determining
from the sensor signals a quantitative measurement of current performance
of the manufacturing operations based on sensed current state of at least
one process means, and for providing indications, displayable on the video
display, of difference between the determined measurement of current
performance of manufacturing operations with respect to the process means
and a predetermined measurement of target performance of manufacturing
operations, the computer means determining measurement of current
performance of manufacturing operations (a) in terms of production cost
when sensed current state of a process means includes sensed amount of
resource used, and (b) in terms of yield when sensed current state of a
process means includes sensed rate of operation, such that measurement of
current performance is indicative of one of production factors and
resource factors, the predetermined measurement of target performance
being based on a same one of the production factors and resource factors
such that (i) said difference between the determined measurement of
current performance and the predetermined measurement of target
performance is indicative of current overall quality of manufacturing
operations in terms of said one of production factors and resource
factors, and (ii) operator adjustment of said one of production factors
and resource factors, through the control means of the process means in
accordance with the indicated difference is enabled, said operator
adjustment of the process means changing state of the process means to a
state of operation which provides the target performance of manufacturing
operations.
2. Apparatus as claimed in claim 1 wherein the plurality of process means
includes pumps, storage vessels, transfer lines and valves.
3. Apparatus as claimed in claim 1 wherein the sensors include temperature
sensors, volume sensors, weight sensors and pressure sensors.
4. Apparatus as claimed in claim 1 wherein the computer means determines
current performance of the manufacturing operations in terms of at least
one of down time, output product quality, and amount of production.
5. Apparatus as claimed in claim 1 wherein the computer means is coupled to
an external system for receiving therefrom the predetermined measurment of
target performance.
6. Apparatus as claimed in claim 1 wherein the control means are coupled to
the digital processor assembly; and
the apparatus further comprises a processor member supported by the digital
processor assembly for receiving from the computer means working
information including determined measurements of performance,
predetermined target measurements, indications of sensed states of process
means, operator adjustment with the control means, and predetermined
thresholds for alarms, the processor member storing the working
information in time order in a relational database for subsequent general
access.
7. Apparatus as claimed in claim 1 wherein the digital processor assembly
includes a plurality of processor modules, different sensors being coupled
to different processor modules, and the processor modules each having an
object manager for transmitting sensor signals from respective processor
modules to the computer means upon request by the computer means.
8. Apparatus as claimed in claim 7 wherein the processor modules store
respective sensor signals as blocks of data points in respective local
memory areas, each block having a different name than other blocks and
each object manager enables access of sensor signals by block name instead
of memory location.
9. Apparatus as claimed in claim 1 further comprising an alarm coupled to
the digital processor assembly, the computer means enabling the alarm when
one of a determined measurment of performance and sensed state of a
process means reaches a respective predefined threshold.
10. Apparatus as claimed in claim 9 wherein the computer means enables the
alarm when a determined measurement of cost exceeds a predefined
threshold.
11. Apparatus as claimed in claim 9 wherein the computer means enables the
alarm when a determined measurement of quality falls outside a predefined
range.
12. In a processing plant having a plurality of process means operated in a
certain pattern to form manufacturing operations, a method of controlling
performance of manufacturing operations comprising the steps of:
operating a plurality of process means in a certain pattern providing
manufacturing operations;
sensing current state of process means;
providing indications of sensed current state of process means to a digital
processor assembly;
in the digital processor assembly, (i) establishing quantitative
measurements of performance of manufacturing operations from the
indications of sensed current state of process means, when sensed current
state of a process means includes sensed amount of resource used from a
start time to a current time, said establishing quantitative measurements
of performance including determining measurements of performance in terms
of production cost, and when sensed current state of a process means
includes sensed rate of operation, said establishing quantitative
measurements of performance including determining measurements of
performance in terms of yield, such that quantitative measurements of
performance are indicative of one of production factors and resource
factors, and (ii) comparing the established quantitative measurements to
predetermined measurements of desired overall performance of manufacturing
operations based on the same one of production factors and resource
factors, said comparing forming quantitative differences between current
state of process means and the predetermined measurements of desired
overall performance of manufacturing operations in terms of said one of
production factors and resource factors;
displaying on a video display coupled to the digital processor assembly, a
series of screen views indicating formed quantitative differences between
current states of process means and the predetermined measurements of
desired performance of manufacturing operations provided by the process
means, said formed quantitative differences being indicative of current
overall quality of manufacturing operations in terms of said one of
production factors and resource factors; and
adjusting said one of production factors and resource factors by adjusting
control means coupled to the process means in accordance with the
quantitative difference indicated in the screen views such that states of
process means approach operations thereof that provide the desired
performance of manufacturing operations.
13. A method as claimed in claim 12 wherein the step of establishing
quantitative measurements includes calculating at least one of down time,
output product quality, cost, yield and production.
14. A method as claimed in claim 12 further comprising the step of
recording in a globally accessable database, digital processor assembly
data including established quantitative measurements, indications of
process means, predetermined measurements, indications of control means
adjustments, and predefined alarm thresholds, such that the digital
processor assembly data is subsequently accessable by desired
applications.
15. A method as claimed in claim 12 further comprising the step of sounding
an alarm coupled to the digital processor assembly when established
quantitative measurements exceed a predefined threshold.
16. A method as claimed in claim 15 wherein the established quantitative
measurements include a cost measurement, and the alarm is sounded when the
cost measurement exceeds a predefined threshold.
17. A method as claimed in claim 15 wherein the established quantitative
measurements include a quality measurement, and the alarm is sounded when
the physical quality measurement exceeds a predefined threshold.
18. In a processing plant having a plurality of process means operated in a
certain pattern forming manufacturing operations, control apparatus
comprising:
a multiplicity of sensors coupled to the process means, each sensor
providing signals indicative of current state of a respective process
means;
a network of computer workstations, each workstation having:
(a) a digital processor assembly coupled to the sensors of a certain group
of process means for receiving the signals therefrom, digital processor
assemblies of different workstations being coupled to sensors of different
groups of process means to receive respective sensor signals;
(b) a video display coupled to the digital processor assembly;
(c) computer means coupled to the digital processor assembly for (i)
providing from the received sensor signals quantitative measurements of
current performance of manufacturing operations with respect to sensed
current states of process means of the workstation, the computer means
determining quantitative measurements of current performance of
manufacturing operations (a) in terms of production cost when sensed
current state of a process means includes sensed amount of resource used,
and (b) in terms of yield when sensed current state of a process means
includes sensed rate of operation, such that each quantitative measurement
of current performance is indicative of one of production factors and
resource factors, and for (ii) displaying on the video display indications
of the quantitative measurements in a manner which is indicative of
necessary adjustments of said ones of production factors and resource
factors and of the process means of the workstation to provide a
predetermined desired measurement of performance of manufacturing
operations, said adjustments changing state of the process means of the
workstation to a state of operation which provides the predetermined
desired measurement of performance of manufacturing operations; and
computer means of different workstations displaying on respective video
displays indications of respective quantitative measurements in manners
indicative of necessary adjustments of respective ones of production
factors and resource factors and of process means to provide the same
predetermined desired measurement of performance of manufacturing
operations. |
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Claims |
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Description |
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BACKGROUND OF THE INVENTION
In a process plant, various processes are employed to produce amounts of a
desired product. To measure general performance of manufacturing
operations of a product, it has been traditional to count the amount of
product produced over a certain period of time of operation and from that
amount calculate a cost per unit product made. The cost per unit product
made is based on a standard costs function for the operation, typically
developed at the beginning of a fiscal time period and used throughout
that period. The ratio (cost per unit product made) is used in periodic
reports to manufacturing management to evaluate manufacturing performance
and over the years has generally served as the primary measure of
manufacturing performance.
One disadvantage to this approach to measuring manufacturing performance is
that all plant costs are allocated to each product or product line in the
determination of cost per unit product. However, most of the costs in a
manufacturing plant are not directly assignable to a product or product
line and therefore must be allocated based on other factors. The factors
usually have more to do with the perceived performance of the
manufacturing operation than the actually occurring manufacturing
practices.
A second disadvantage is a considerable percentage of the costs in a
manufacturing plant that are used to calculate the cost per unit product
made is totally out of the scope of manufacturing's authority. Thus, the
performance measurement of cost per unit product made has led to a pure
"volume base" manufacturing approach, which may not be the best approach
to meet market and corporate requirements.
Another disadvantage is that the calculation to determine cost per unit
product made is based on the amount of each product or product line that
is produced and is not sensitive to any specific problems incurred in the
production of a specific product. For example, if a bad batch of a given
product is produced and thrown away, the standard allocation algorithm has
no way of assigning the costs associated with that batch to the specific
product. Instead these costs are allocated to all products made.
Other approaches to measuring manufacturing performance involve
non-cost/non-financial measurements and include measurements of quality,
delivery integrity and customer satisfaction. These approaches have been
directed primarily to the discrete manufacturing industry and still
involve collecting information and displaying results in the traditional
daily, weekly or monthly report format. Hence, such approaches do not
timely provide measurements such that operations personnel can improve on
the process on which the measurements were made.
SUMMARY OF THE INVENTION
The present invention recognizes that the cost per unit product made ratios
produced by a traditional performance measurement system are inaccurate
and unrepresentative of the manufacturing operations. Further, the present
invention recognizes that traditional manufacturing performance
measurements are not provided in a sufficiently timely manner to allow
operations personnel to improve their performance. That is, the present
invention recognizes that if manufacturing people receive their measure of
performance long after the completion of the production on which they were
measured, they will not be able to efficiently apply the performance
measurement and effect improvement of manufacturing performance.
To that end, the present invention provides a real-time (dynamic),
sensor-based performance control apparatus. The control apparatus operates
within a manufacturing or process plant having a plurality of process
means for providing various processes to form an output product. The
process means are operated in a pattern to provide manufacturing
operations. The control apparatus employs a multiplicity of sensors
coupled to the process means and computer processing means for providing
from sensor signals a real-time indication of current performance of
manufacturing operations. Performance is indicated in terms of quality of
generated products, cost of production, down time, yield, and/or
production.
Specifically, each sensor provides signals indicative of current state of a
respective process means. A digital processor assembly is coupled to the
sensors to receive the sensor signals. Supported by the digital processor
are computer means which determine from the sensor signals a quantitative
measurement of current performance of the manufacturing operations based
on current operation of at least one process means. For example, the
computer means calculates production cost as a function of sensed current
amounts of resources used, and calculates quantity of production as a
function of sensed rate of operation of certain process means.
The computer means further provides screen views displayed on a video
display coupled to the digital processor assembly. The screen views
display indications of the determined measurement of current performance
of manufacturing operations with respect to a predetermined target
performance measurement. Subsequent operator adjustment through control
means coupled to the process means in accordance with the indications in
the screen views causes states of the process means to approach operation
which provides the predetermined target performance of the manufacturing
operations.
Along with screen view displays, the computer means provides sounding of
alarms in accordance with determined performance measurements. The alarms
are coupled to the digital processor assembly. In particular, the computer
means sounds an alarm when certain thresholds are crossed by process means
and/or by determined performance. For example, the computer means enables
an alarm when determined performance measurement based on current cost of
production exceeds a predefined threshold, and/or when determined
perfomance measurement based on quality falls outside a predefined range.
In accordance with one aspect of the present invention, the plurality of
process means includes pumps, storage vessels, transfer lines, valves and
the like found in a processing plant. Also, the multiplicity of sensors
includes temperature sensors, volume sensors, weight sensors, pressure
sensors and the like.
In a preferred embodiment of the present invention, the digital processor
assembly includes a plurality of processor modules. Different sensors are
coupled to different processor modules. Each processor module has an
object manager which transmits respective sensor signals to the computer
means upon request by the computer means. Preferably, each sensor signal
is formed of a named series of data points stored in a memory area, and
each object manager enables access of data points by name instead of
memory location.
Further the computer means may be coupled to an external system for
receiving therefrom pertinent predefined measurements of target
performance.
In accordance with another aspect of the present invention, the control
means may be coupled to the digital processor assembly.
In addition, a processor member supported by the digital processor assembly
receives from the computer means various working data and stores the
working data on a common time line in a global data base for general
access. The working data includes determined performance measurements,
predetermined target measurements, indications of sensed states of process
means, operator adjustments and predefined thresholds for alarms. In a
preferred embodiment, the database is a relational database accessable
globally at subsequent times as desired for different applications.
BRIEF DESCRIPTION OF THE DRAWINGS
The foregoing and other objects, features and advantages of the invention
will be apparent from the following more particular description of
preferred embodiments of the invention, as illustrated in the accompanying
drawings in which like reference characters refer to the same parts in
throughout the different views. The drawings are not necessarily to scale,
emphasis instead being placed upon illustrating the principles of the
invention.
FIG. 1 is a schematic view of an embodiment of the present invention
employed in a manufacturing or process plant.
FIG. 2 is a flow diagram for implementation of the embodiment of FIG. 1
including a software program employed therein.
FIG. 3 is a schematic illustration of a group of process means in a plant
which may be represented in a sequence programming block in the software
of FIG. 2.
FIG. 4 is a schematic flow diagram of the sequence programming block of
FIG. 3.
FIG. 5 is a schematic illustration of a screen view graph displayed in the
embodiment of FIG. 1.
FIGS. 6a-6c are schematic views of screen views displayable in an
embodiment of the present invention.
FIG. 7 is a detailed flow diagram of one implementation block in the flow
diagram of FIG. 2.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT
A manufacturing or process plant employs various and numerous equipment to
provide different functions or effects on source materials to form desired
finished products. The different pieces of equipment or groups thereof are
generally referred to herein as process means. And the functions provided
by the different pieces of equipment or groups thereof are generally
referred to herein as processes.
Generally the present invention employs (i) real-time sensing (i.e. sensing
during processing) of the current state of the processes and the process
means which are involved in the processing of subject materials, and (ii)
computer processing of the real-time data. Specifically, through computer
executed calculations, the present invention determines from the real-time
sensor based data, quantitative measurements of performance of current
manufacturing operations. Measurements of performance include but are not
limited to measurements of down time, quality of output products, cost,
yield and/or production.
The present invention also provides for display of the determined
performance measurements to operations personnel during processing.
Further, the performance measurements change or are recalculated with the
constant sensing of the state of the process means and hence manufacturing
operations, and thus are herein referred to as "dynamic performance
measurements". Such dynamic performance measurements are not only more
accurate than prior art financial based performance measurements by being
based on in-process information instead of post-process quantity of
product made, but are also more useful to operations personnel by being
provided/displayed in a timely (real time) manner which enables operations
personnel to readily make necessary adjustments to increase performance of
current plant operations.
Said another way, the present invention provides (i) dynamic performance
measures which are calculated right off the production process using real
time, preferably object-based process data, and (ii) results which are
displayed in real-time, in a graphical format to the appropriate
manufacturing personnel. In a preferred embodiment of the present
invention, the results are also historized into a real-time database
management system for later use, aggrandizement, and integration with
other computer information systems of the manufacturing plant.
Illustrated in FIG. 1 is a general manufacturing or process plant control
system 10 that embodies the present invention. Manufacturing operations
begin at 11 and involve processing through a series or pattern of process
means collectively indicated at 15. The final (output) product or batch
thereof exits the manufacturing operations at 13. The process means 15
include vats, mixers, heating units, conveyer belts, pumps, transfer lines
together with valving assemblies and the like for performing various
processes required to make the various products of the plant.
Operating personnel of the plant control the process means 15 in a manner
such that a desired amount and kind of output product is produced in a
given work period. The controllable aspects of the different process means
15 and hence processes of the manufacturing operations include pressure,
temperature, flow volume, flow rate and the like as is known in the art.
The operating personnel control these aspects of the process means through
various control means 56 including valves, heating units, venting units
and the like. Operation of the controls 56 may be manually or through a
computer processor (electronic means) as known in the art.
In order for operations personnel to adjust control means 56 in a manner
which aids (especially increases performance of) current processing such
that quality and/or quantity of output products is improved, the present
invention provides a computer program for generating and displaying
dynamic performance measurements at each operations personnel workstation
17, 19 of the plant. Each workstation 17, 19 includes various I/O devices
coupled to the computer processor such as a video display 21 and keyboard.
Also, workstations 17, 19 are supported by respective workstation
processor modules 41 (described later) which enable the different
workstations 17, 19 of the plant to communicate to each other and to
global data bases 45 over a carrier band local area network (LAN) 25 or
other suitable bus assembly. Upon command by an operations person at a
local workstation 17, 19, the computer program provides screen views on
the workstation video display 21 which present (a) indications of plant
performance based on current state of manufacturing operations, (b)
indications of predetermined desired or target levels of performance of
manufacturing operations, and/or (c) indications of adjustments (direction
and amount) to process means which are necessary to increase or optimize
performance of the manufacturing operations.
The computer program is preferably an object-oriented program. The
necessary objects and their functionality are described after a discussion
of the hardware/computer processing environment in which the preferred
embodiment is implemented.
In the preferred embodiment, the process means 15 of the manufacturing
operations are thought of as grouped according to local workstation 17, 19
of operations personnel responsible for overseeing the process means 15.
Referring to FIG. 1, sensors 27 are coupled to the process means 15 to
detect temperature, pressure, volume, weight, flow volume, flow rate and
other desired physical and/or chemical aspects of the process means 15.
Such sensors 27 include but are not limited to temperature sensors,
pressure gauges and the like for detecting the desired physical and/or
chemical aspects. The sensors 27 of a group of process means 15 which
correspond to a workstation 17, 19 generate analog or digital signals
which are received by field bus modules 29a, 29b, 29c of the workstation
17, 19.
The field bus modules 29a, 29b, 29c convert and format the received sensor
signals as described in Product Specifications PSS 21H-2B1 B3,
"Intelligent Automation Series Fieldbus Modules" by the Foxboro Company,
Foxboro, Mass. and herein incorporated by reference. Each field bus module
29a, 29b, 29c of control system 10 transmits across a field bus 31a, 31b,
31c, preferably of the multidrop type, the converted and formatted digital
sensor signals to computer node 35, 33 which supports the workstation 17,
19. The supporting computer node 33, 35 is formed of a plurality of
processor modules and an interface module to the LAN 25. Each processor
module has its own operating system 53 and applications environment.
Shown in FIG. 1, the supporting computer node 33 of workstation 19 includes
a LAN interface module 37, a plurality of control processor modules 39a,
39b, a workstation processor module 41 and an application processor module
43. The workstation processor module 41 interfaces to the workstation 17,
19, and the application processor module 43 interfaces to bulk storage and
in particular to a global database 45 described later. It is the control
processor modules 39a, 39b which receive across respective field buses
31b, 31c the converted and formatted sensor signals from the corresponding
field bus modules 29b, 29c.
Each control processor module 39a, 39b receives converted and formatted
sensor signals from a respective field bus module 29b, 29c and stores them
in local memory 47a. 47b In object oriented program structures called
input blocks 61. Each input block 61 is assigned a block name and the
block name is catalogued in the control processor modules 39a, 39b object
or datapoint directory 49a, 49b. Each entry in the directory 49a, 49b also
provides a pointer or other memory address indicator to the corresponding
input block 61.
The workstation processor module 41 similarly holds data in local memory
47c as object oriented blocks. Names of these blocks and corresponding
memory addresses are catalogued in object directory 49c of the module 41.
Each of the control processor modules 39a, 39b and workstation processor
module 41 and application processor module 43 employs an object manager
55a, 55b, 55c, 55d which manages the import and export of input and other
data blocks, more accurately referred to as objects and data points,
between modules of a supporting computer node 33 as well as between
modules of different supporting computer nodes 35 along the carrier band
LAN 25. To accomplish the former, a serial backplane 51 provides
communication between the modules 37, 39, 41, 43 of a supporting computer
node 33. The operating system 53a, 53b, 53c and object manager 55a, 55b,
55c of each supporting computer node module maintains an import list 57a,
57b, 57c of objects (e.g. input or data blocks) not found locally in the
module and, hence, required to be imported from other modules in order to
execute certain processing. The import list 57a, 57b, 57c indicates
objects memory addresses or locations which are known to the module. For
those objects indicated in the import list 57a, 57b, 57c which the module
does not know the respective memory address, the object manager 55a, 55b,
55c of the module establishes an object list indicating those objects. The
object list also specifies the requesting module 39, 41.
The object manager 55a, 55b, 55c broadcasts the object list across the
serial backplane LAN 51 to the other modules 39, 41 of the supporting
computer node 33. The object manager 55a, 55b, 55c of each of the (other)
receiving modules 39, 41 compares the object names on the received object
list to the object names on the object or datapoint directory 49a, 49b,
49c of the respective receiving module 39, 41. For each requested object
name found on the respective module object directory 49a, 49b, 49c, the
object manager 55a. 55b, 55c of the receiving module 39, 41 places the
object name and memory address from the directory on an export list 59a,
59b, 59c of the module. Along with the object name and address, the object
manager 55a, 55b, 55c places a user specified value in the export list
59a, 59b, 59c. This value serves as an exception value such that the block
entered in the export list 59 is not transferred for values within the
exception value.
The object manager 55 of each module 39, 41 of a supporting computer node
33 routinely (preferably about every half second) checks the exception
values on the export list 59 of the respective module 39, 41. For the
listed objects with values outside of the respective exception values, the
object manager 55 of that module 39, 41 transmits across the serial
backplane 51 to the requesting module 39, 41, the memory address of the
requested object. Upon receipt of the object address, the requesting
module operating system 53a, 53b, 53c through the module object manager
55a, 55b, 55c records this address in the modules import list 57a, 57b,
57c next to the name of the requested object. Common handshaking and other
protocol between the operating system 53a, 53b, 53c of the exporting
module 39, 41 and that of the requesting module 39, 41 is subsequently
performed before the object manager 55a, 55b, 55c of the exporting module
transmits the requested information from the object.
At a subsequent time, the operating system 53a, 53b, 53c of the requesting
module 39, 41 may cease the further transmission of the requested object
information as desired, by transmitting across the serial backplane 51 a
pertinent message to the operating system 53a, 53b, 53c of the exporting
module 39, 41. The operating system 53 of the exporting module 39, 41
responds to the pertinent message by directing the object manager 55 of
the exporting module to erase the name of the subject object from the
exporting module's export list 59.
The global or network wide requesting and receiving of a desired object is
performed in a manner similar to the foregoing. Additionally, broadcast of
the request for a desired object and response for the module to transport
the address of the requested object is transmitted across the broad band
LAN 25 via the LAN interfaces 37 of the different supporting computer
nodes 33, 35.
Thus, the object managers 55 of the supporting computer nodes 33, 35 enable
objects (e.g. input/data blocks) to be accessed by name instead of memory
location or address wherever in the network the object may be stored.
The operating systems 53a, 53b of the control processor module 39a, 39b
executes the computer program of the present invention with the sensor
data accessed through object managers 55 as described above. To that end,
the computer program at operating system 53a,b provides the dynamic
performance measurements of the process means 15 for which the operator at
workstation 19 is responsible. Implementation details of that computer
program are discussed next in conjunction with the flow chart of FIG. 2.
The actual dynamic performance measures required for a particular plant
operation are a function of the manufacturing strategy that has been
developed for that operation. The dynamic performance measures that are
most appropriate for process means or a group thereof in one plant may not
be appropriate at all for the same of a similar but different plant. For
example if a plant is production limited, the primary measures will tend
to be yield or some other production based statistic, but if the plant is
not production limited, the measures may be more resource based. Therefore
the first two steps 67, 68 of FIG. 2 in the implementation details of a
computer program for generating dynamic performance measures is to
determine the manufacturing strategy for the plant, and translate that
strategy to specific measurements that should be made to determine if the
strategy is working, on a process means (or group thereof) by process
means (or group thereof) basis.
By way of example and not limitation, in a paper mill, performance strategy
of a continuous digester focused on production rate, quality within
predetermined limits and stability of the digester such that the digester
is operated in a smooth and continuous manner. As a consequence, the
measurements to determine if the strategy is working include chip meter
rpms, amount of production below the expected amount, start time of the
digester, time to return to peak production after slowdown period of the
digester, quality K number, lower cook conductivity, amount of time the K
number was out of specification limits, amount of time digester level is
out of target zone and time required to stabilize from upsets in digester
level or chip bin level. Also, occurrences of the number of kickouts of a
top separator feeder, lack of net upflow in the digester, or rate
variation in the chip feeder rate greater than a target value can all be
recorded for improvement work. Level control in a number one blow tank is
a measure of the balance between the digester and washers, and the amount
of change during a shift is representative of the stability of the two
operations.
Once the specific measures are determined, the sensor information required
71 to make the measures has to be determined. In many process plants, the
sensors 27 required to make the measures will already be installed in the
process or with the process means of interest. In some cases, new sensors
need to be installed to complete the collection of sensor-based
information required to measure the performance of the manufacturing
operations at a particular process means or group thereof.
The next step 69 in the implementation process is to be sure that the
required sensor-based information is directly connected to the supporting
computer nodes 35, 33 of the pertinent workstation 17, 19. This is
typically done in one of two basic ways. The transmitters associated with
the sensors 27 can transmit an analog signal that represents state of the
process means or process 15 along a predefined continuum, or the
transmitters can transmit a digital signal to the supporting computer node
35, 33. Each supporting computer node 35, 33 is equipped with appropriate
input/output capability to receive the sensor-based information.
At this point 73 in the implementation process, the object oriented
programming structures called input blocks 61 (FIG. 1) are constructed for
each the required sensor-based inputs. These blocks 61 convert the
incoming sensor signals into digital values in the engineering units
required for the dynamic performance measurement calculation discussed
later. Each input block 61 is formed of a collection of records or fields,
each of which holds particular sensor data. The input block 61 also
provides general system access to the sensor data by name, where the
global name is based on the name assigned to the input block 61. This data
point or "object" value is now available to any application in the network
by specifying the name of any input block 61 or the name of the field or
record of interest in the input block 61. Alarming can also be provided at
this point 73 (FIG. 2) if desired.
The next step 74 in the implementation process of FIG. 2 is to construct
the calculation algorithms for the dynamic performance measures of
interest. The calculation algorithms mathematically state the measurements
established at 68 of FIG. 2 that determine if the manufacturing strategy
is working and generally are common or determinable mathematics. Also the
calculation algorithms include target, predetermined values and
comparisons between currently calculated values and the target values. For
example if a sensed flow rate from a last mixing vat in an operation is 8
units/hour, the production rate for the operation personnel whose shift is
known to last 10 hours can be currently determined at 80 units/shift This
calculation can be made anytime in his shift with current sensed flow rate
data. Additional calculations compare the calculated 80 units/shift to a
predetermined target value of 85 units/shift and provides output
indicating that the current flow rate of the mixing vat should be
increased by 0.5 units/hour (i.e. (85-80) units/10 hrs) to provide ideal
operation/performance.
For each calculation algorithm, an object oriented programming based block
structure is established. These "algorithm" blocks 63 (FIG. 1) can be
preprogrammed for dynamic performance measurements that are frequently
encountered or they can be programmed as the need arises. The sensor-based
data as represented by input blocks 61 (FIG. 1) developed in the previous
steps 73 are used as input to the algorithm blocks 63 (FIG. 1). This is
accomplished by specifying in the algorithm block 63 the name of the input
block 61 and the input block parameter (field or record) of interest. In
executing the algorithm block 63, the operating system 53a,b of the
control processor module 38a, b, in which the computer program of the
present invention resides, requests and obtains the sensor-based data in
the specified input block 61 (as described previously) and performs
computations on the obtained input data as directed by the mathematical
relationships set forth in the algorithm block 63.
The output of the algorithm block 63 becomes a global object 65 (FIG. 1) in
the network that can be accessed from anywhere in the network by
specifying the name of the producing algorithm block 63. The computed
values in this output object 65 serve as the basis for the dynamic
performance measures of interest.
An example (by way of illustration and not limitation) of a dynamic
performance measure algorithm block 63 is as follows. Assume that the
manufacturing operation (i.e. produced by a group of or a single process
means) under consideration is not production related, but requires
significant resources in terms of raw material, catalyst and energy to
perform the desired operation. The algorithm block 63 in this case would
set forth a resource cost relationship of the type:
RC=M1*C1+M2*C2+M3*C3+(Cat1-Cat2)C4+E1*C5+E2*C6
where:
RC is the dynamic resource cost;
M1, M2, and M3 are the quantities of the three raw materials used in a
given period based on sensor-based data;
C1, C2, and C3 are the respective cost factors of the raw materials per
unit measured;
Cat1 is the amount of catalyst at the beginning of the operation
(sensor-based;
Cat2 is the amount of catalyst recovered after one cycle of performance of
the operation (sensor-based);
C4 is the cost of the catalyst;
E1 is the amount of energy used in the unit operation for the given period
(sensor-based);
C5 is the cost of E1 per unit consumed;
E2 is the amount of energy used in the catalyst recovery operation
(sensor-based);
C6 is the cost of E2 per unit consumed.
It should be noted that the cost factors, Cn, could either be constants in
the algorithm block 63, or could be provided by another computer
information system of the plant based on current market conditions. Also,
a target value of resource cost may be stated in the algorithm block 63 as
a constant or variable to which the dynamic (above calculated) resource
cost is compared. The comparison can provide a numerical output which is
subsequently useable as a dynamic performance measurement.
Other examples of algorithm blocks are as follows for the paper mill
digester. Start-up time of the digester is defined in a mathematical
relationship as the time from initial feed start to the point when both
rpm and K number are within specification limits. A timer is triggered by
the start of the chip meter (sensor-based) and continues to accumulate
time counts until the production conditions are satisfied. The operating
system 53a,b of the control processor module 39a,b constantly computes rpm
and K number, according to common definitions thereof and using sensor
based data, until both are within specification limits. At that moment,
the timer is stopped. Some rules for interpolating K number data to
indicate when the K number is actually within range may be employed. The
output of the algorithm block 63 provides the elapsed time from the timer
for the startup time of the digester.
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