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WO1996039658A1 - Systeme d'information integre pour un processus industriel et une entite externe - Google Patents

Systeme d'information integre pour un processus industriel et une entite externe Download PDF

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Publication number
WO1996039658A1
WO1996039658A1 PCT/US1996/007266 US9607266W WO9639658A1 WO 1996039658 A1 WO1996039658 A1 WO 1996039658A1 US 9607266 W US9607266 W US 9607266W WO 9639658 A1 WO9639658 A1 WO 9639658A1
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WO
WIPO (PCT)
Prior art keywords
information system
inquiry
recited
database
electric energy
Prior art date
Application number
PCT/US1996/007266
Other languages
English (en)
Inventor
William R. Rice
Stuart P. Simpson
Original Assignee
Westinghouse Electric Corporation
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Westinghouse Electric Corporation filed Critical Westinghouse Electric Corporation
Publication of WO1996039658A1 publication Critical patent/WO1996039658A1/fr

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Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computing arrangements using knowledge-based models
    • G06N5/04—Inference or reasoning models
    • G06N5/043—Distributed expert systems; Blackboards

Definitions

  • This invention relates to an information system for industrial process management and, more particularly, to an integrated information system for shared use by the operations, maintenance, engineering, human resources, management, and other functional units of one or more industrial plants, such as nuclear power plants, and/or by one or more other industrial plants and/or vendors for such plants.
  • Various management information systems are known for monitoring and recording process parameters in connec ⁇ tion with power generation as well as with industrial processes generally. These systems often are reactive in that they respond to present levels of monitored parame ⁇ ters, or at most respond to present trends to control generation of alarms and the like when a parameter exceeds preset values or threatens to do so.
  • a typical process control system monitors sensed parameters to ensure that they remain within present limits defined by the programmer of the system. Often the present levels can be displayed graphically to highlight trends.
  • Another form of management information system is known in connection with scheduling of maintenance proce ⁇ dures.
  • scheduling of maintenance proce ⁇ dures By defining a useful life for each article of equipment, among a number of articles which are related or inter-dependent, it is possible to schedule repair, re ⁇ placement or preventive maintenance operations more effi ⁇ ciently so as to minimize downtime.
  • the idea is to plan replacement or repair of articles of equipment for as late as practicable before an actual failure, preferably using intelligent scheduling procedures to minimize downtime by taking maximum advantage of any downtime.
  • the scheduling system prompts or warns plant personnel to attend to each of the articles which may need attention at or soon after the time at which the maintenance of any particular article becomes critically important.
  • Patent 4,908,775 discloses a cyclic monitor ⁇ ing system which counts down a defined useful life expected for various structures in a nuclear power plant. This system is responsive to operating levels in the plant and increases the predicted aging rate of plant structures to account for variations in usage including transient load ⁇ ing.
  • a sampling module is provided to detect the current loading of monitored equipment periodically. Transient and steady state operating levels are determined from the sampled data and used to generate a usage factor. Equip ⁇ ment degradation due to fatigue and the like is anticipated by integrating the usage factor over time.
  • the system can be used to plan maintenance and replacement activities or alternative plant operations, using a more accurate estimation of the useful life of the plant compo ⁇ nents.
  • U.S. Patent No. 5,311,562 discloses an integrated plant monitoring and diagnostic system for use within a nuclear power plant.
  • the diagnostic system integrates information regarding usage and expected useful life, design and technical specifications, and historical data into a system that monitors operational levels and equip- ment conditions.
  • the hierarchical data acquisition and processing system provides shared access to this informa ⁇ tion by different plant departments, especially operations, maintenance and engineering.
  • the diagnostic system of Patent No. 5,311,562 collects safety and control parameters using a data network arrangement that is shared .by primary and auxiliary system control and protection groups, plant maintenance groups, plant engineering and management.
  • the plant computerized information system is integrated generally with instrument data collection from a variety of sources, and stored design criteria information.
  • the information system includes at least one first database mechanism each of which is associated with at least one of the functional units for storing a corresponding one of the knowledge sets maintained thereby; at least one second database mechanism each of which is associated with at least one entity external to the electric energy enterprise for storing a knowledge set maintained by the entity; a mechanism for linking each of the first and second database mechanisms; a mechanism for inputting an inquiry related to at least one of the first and second database mechanisms; and an artificial intelligence mechanism for searching at least one of the first and second database mechanisms in response to the inquiry in order to determine whether the knowledge set of at least one of the first and second database mechanisms contains information pertinent to the inquiry, and for retrieving the information pertinent to the inquiry from at least one of the first and second database mecha ⁇ nisms.
  • an information system for managing operation of a first electric energy enterprise using a knowledge set associated with at least one second electric energy enterprise and related to the operation of the first electric energy enterprise includes a mechanism for acquir ⁇ ing real-time values of a plurality of parameters associat- ed with the operation of the first electric energy enter ⁇ prise; a first database mechanism for storing historical values of at least some of the parameters; a second data ⁇ base mechanism maintained external to the first electric energy enterprise for storing the knowledge set associated with the second electric energy enterprise; and an artifi ⁇ cial intelligence mechanism for integrating the real-time values of at least one of the parameters with the histori ⁇ cal values of at least one of the parameters and with the knowledge set according to a predetermined set of rules in order to analyze the operation of the first electric energy enterprise.
  • an information system for managing operation of a first industrial process using a knowledge set associated with at least one second industrial process and related to the operation of the first industrial process includes a mechanism for acquiring real-time values of a plurality of parameters associated with the operation of the first industrial process; a first database mechanism for storing historical values of at least some of the parameters; a second database mechanism maintained external to the first industrial process for storing the knowledge set associated with the second industrial process; and an artificial intelligence mechanism for integrating the real- time values of at least one of the parameters with the historical values of at least one of the parameters and with the knowledge set according to a predetermined set of rules in order to analyze the operation of the first industrial process.
  • Figure 1 is a block diagram illustrating generally an information system integrating maintenance, engineering, human resources and other functional units of a power generating utility with an external vendor of the power generating utility and an external utility in accordance with an embodiment of the present invention
  • Figure 2 is a block diagram illustrating generally an information system integrating plant operation, mainte ⁇ nance, engineering and management functional units of a power generating utility with an external vendor of the power generating utility in accordance with another embodi ⁇ ment of the present invention
  • Figure 3 is a block diagram illustrating generally an information system having an artificial intelligence decision task broker which integrates maintenance, engi- neering and human resources databases of a nuclear power generating plant with external industry databases outside of the nuclear power generating plant in accordance with another embodiment of the present invention
  • FIG. 4 is a block diagram of an artificial intelligence decision task broker which directs an inquiry to selected databases in accordance with the invention
  • Figure 5 is another block diagram of the artifi ⁇ cial intelligence decision task broker of Figure 4 which coordinates answers from the selected databases in response to an inquiry;
  • Figure 6 is a block diagram illustrating generally an information system network which integrates a plurality of databases of different electric power generating enter ⁇ prises and mechanisms for inputting an inquiry at two of such enterprises;
  • Figure 7 is a block diagram illustrating generally an information system having an artificial intelligence decision task broker which integrates a database of a nuclear power generating plant with an external industry database outside of the nuclear power generating plant in accordance with another embodiment of the present inven ⁇ tion;
  • Figure 8 is a block diagram illustrating generally an information system having an artificial intelligence decision task broker which integrates a plurality of databases of associated power plants of an electric power generating enterprise with external industry databases outside of the electric power generating enterprise in accordance with another embodiment of the present inven ⁇ tion;
  • Figure 9 is a block diagram illustrating generally an information system having an artificial intelligence decision task broker which integrates maintenance, engi ⁇ neering and human resources databases of a nuclear power generating plant with external vendor databases outside of the nuclear power generating plant in accordance with another embodiment of the present invention
  • Figure 10 is a block diagram illustrating general ⁇ ly an information system having an artificial intelligence decision task broker which integrates a plurality of databases of associated power plants of an electric power generating enterprise with external industry databases outside of the electric power generating enterprise in accordance with another embodiment of the present inven ⁇ tion.
  • electric power plant shall expressly include, but not be limited to nuclear power plants, fossil power plants, hydroelectric power plants, solar power plants, wind farms, and/or geothermal power plants.
  • electric energy enterprise shall expressly include, but not be limited to one or more organizations or facilities which sell energy related equipment and/or services, operate one or more electric power plants, generate electric power, transmit electric power, and/or distribute electric power.
  • the term "industrial process” shall expressly include, but not be limited to any indus ⁇ trial process needing intelligence for decision making such as, for example, chemical processing, chemical manufactur ⁇ ing, industrial manufacturing, and/or electric energy enterprises, including, but not limited to industrial processes which are either part of the same enterprise or else are parts of different enterprises.
  • the term "enterprise” shall expressly include, but not be limited to any business process needing organization or analysis for decision making such as, for example, industrial processes, corpora ⁇ tions, and/or other business processes.
  • the term "functional unit” shall expressly include, but not be limited to one or more sub-organizations of an enterprise such as, for example, companies, business units, divisions, and/or departments such as, for example, operations (i.e., the process, processes or sub-processes of the industrial process such as, for example, the nuclear containment structure and all auxiliary buildings associated therewith, turbine, genera ⁇ tor, and transmission and distribution facilities of a nuclear power plant) , maintenance, engineering, human resources, finance, purchasing, sales, marketing, and/or management.
  • operations i.e., the process, processes or sub-processes of the industrial process
  • entity shall expressly include, but not be limited to one or more vendors, suppliers, and/or distributors external to an industrial process; and/or one or more other external industrial processes.
  • knowledge set shall expressly include, but not be limited to one or more real ⁇ time values of parameters associated with the operation of an industrial process and/or functional unit thereof; one or more historical values of such parameters; and/or data, information, and/or rules associated with the operation of the industrial process and/or functional unit thereof.
  • the exemplary infor- mation system 2 includes a remote communications network 4, such as a wide-area network, which is interconnected between a first industrial process 6, an external second industrial process 8, and an external entity 10, although the invention is applicable to other remote communications networks such as, for example, satellite, fiber optic or telephone networks.
  • the exemplary industrial processes 6,8 are electric power generating utilities A,B, respectively, and the exemplary entity 10 is a vendor C of utility A.
  • the utility A has a plurality of functional units including operations 12, maintenance 14, engineering 16, human resources 18, and management, purchasing and finance 20.
  • the exemplary operations functional unit 12 includes a nuclear containment structure 22 and all auxiliary build- ings 24 associated therewith.
  • Each of the exemplary functional units 12-20 has a function related to the operation of the industrial process 6.
  • the maintenance functional unit 14 is responsible for repairs and periodic maintenance of the operations functional unit 12.
  • the management, purchasing and finance functional unit 20 is responsible for procuring components or maintenance services for the operations functional unit 12 from the external vendor C or other external vendors (not shown) .
  • the human resources func- tional unit 18 is responsible for hiring and administration of maintenance personnel for the maintenance functional unit 14.
  • the engineering functional unit 16 is responsible for defining a loading plan for the reactor core (not shown) within the containment structure 22.
  • the functional units 12,14,16,18,20 maintain knowledge sets 26,28,30,32,34, respectively, of information pertaining to the function thereof.
  • the utility B or other utilities (not shown)
  • vendor C or other vendors (not shown) maintain knowledge sets 36 and 38 of information pertaining to the processes of utility B and the products and services of vendor C, respectively.
  • the information system 2 manages the knowledge sets 26-34 of the respective functional units 12-20 and, also, manages the knowledge sets 36 and 38 of the utility B and vendor C, respectively.
  • the functional units 12,14,16,18,20 include databases 40,42,44,46,48 which store the information of the knowledge sets 26,28,30,32,34 maintained by such functional units, respectively.
  • the database 48 is associated with and shared by the separate functional units of management 20A, purchasing 20B and finance 20C of the management, purchasing and finance functional unit 20.
  • the utility B and vendor C include databases 50 and 52 which store the information of the knowledge sets 36 and 38 maintained by such utility and vendor, respec ⁇ tively.
  • the exemplary wide-area network 4 includes three local-area networks 54,55,56 associated with the first industrial process 6, the external second industrial process 8, and the external entity 10, respectively.
  • the databases 40-48,50,52 are interconnected with the local- area networks 54,55,56, respectively.
  • the wide-area network 4 provides a mechanism for linking each of the databases 40-52.
  • the exemplary local-area networks 55,56 are interconnected with the exemplary local-area network 54 by gateways (G/W) 58A-58B,60A-60B which are connected by data links 62,64, respectively, such as Tl communications links. In this manner, the external databases 50,52 are integrated with the local databases 40-48 of the industrial process 6.
  • the functional units 14,16,18,20 of utility A, the utility B, and the vendor C include inquiry mechanisms (I) 66,68,70,72,74,76, respectively.
  • the inquiry mechanisms 66- 72,74,76 are interconnected with the local-area networks 54,55,56, respectively.
  • the inquiry mechanisms 66-76 input inquiries to the wide-area network 4 related to one or more of the databases 40-52.
  • a search mechanism (S) 78 Also connected to the local-area network 54 of the wide-area network 4 is a search mechanism (S) 78 which receives the inquiries of the inquiry mecha ⁇ nisms 66-76 from the network 4.
  • the search mechanism 78 searches selected databases 40-52 in response to an inquiry in order to determine whether the respective knowledge sets 26-38 contain information pertinent to the inquiry. In turn, the search mechanism 78 retrieves the information pertinent to the inquiry from the selected databases 40-52 and provides a response to the appropriate one of the inquiry mechanisms 66-76. It will be appreciated by those skilled in the art that the exemplary search mechanism 78 and inquiry mechanisms 66-76 may each include a personal computer, a workstation or any other network-based proces- sor NP (as shown with the search mechanism 78) suitable for accessing a database.
  • the containment structure 22 includes a plurality of character- istics 80 such as, for example, the exemplary pressure (P) 82, flow (F) 84 and temperature (T) 86. These characteris ⁇ tics 80, in turn, are monitored by sensors 88 which update the database 40 with corresponding values.
  • the other databases 42-52 are updated with other characteristics (CH) associated with the respective knowledge sets 28-38.
  • the exemplary information system 2' includes a remote communi ⁇ cations network 4', such as a wide-area network, which is interconnected between an industrial process 6', such as a nuclear power generating plant of a nuclear utility, and an external entity 10', such as a vendor D of the industrial process 6'.
  • the industrial process 6' has a plurality of functional units including plant operations 12', plant maintenance 14', plant engineering 16', and plant manage ⁇ ment 20A'.
  • Each of the exemplary functional units 12',14',16',20A' has a function related to the operation of the industrial process 6'.
  • each of the functional units 12',14',16',20A' maintains a knowledge set 26',28',30',34', respectively, of information pertaining to the function thereof.
  • the external entity 10' has a plurality of knowledge sets 90,92,94,96 which are respectively associat ⁇ ed with the functions of plant operations, plant mainte- nance, plant engineering, and plant management for other industrial processes 8'.
  • the exemplary industrial process ⁇ es 8' which are external to the industrial process 6' , provide functions related to the functions of the industri ⁇ al process 6' and include a plurality of different nuclear power generating plants 8A',8B',8C' of various different nuclear utilities (not shown) .
  • the information of the knowledge sets 90,92,94,96 is stored within databases 98,100,102,104, respectively.
  • the databases 98-104 collec ⁇ tively form a database 105 which is maintained by the vendor D.
  • the database 105 stores the information of the knowledge sets 90-96 from the other related industrial processes 8'. Hence, these knowledge sets 90-96 are related to the operation of the industrial process 6'.
  • the exemplary wide-area network 4' includes two local-area networks 54' and 56' which are respectively associated with the first industrial process 6' and the external entity 10'.
  • the databases 98-104 are intercon ⁇ nected with the local-area network 56' through security mechanisms (SEC) 106,108,110,112, respectively, each of which permits authorized inquiries from selected locations and, also, prohibits unauthorized inquiries from non- selected locations on the wide-area network 4'. In this manner, commercially sensitive information, from either the entity 10' or the industrial processes 8', is not generally accessible from the network 4'.
  • SEC security mechanisms
  • the exemplary local-area networks 54',56' are interconnected by gateways 114A,114B which, in turn, are connected by a data link 116 such as a Tl communications link.
  • the databases 98,100,102,104 are also intercon ⁇ nected with inquiry mechanisms (I) 118,120,122,124, respec ⁇ tively.
  • the inquiry mechanisms 118-124 input inquiries to the respective databases 98-104 and to the wide-area network 4'. These inquiries are related to one or more of the databases 98-104 and/or one or more of the knowledge sets 26'-34'.
  • a search mechanism (S) 78' similar to the search mechanism 78 of Figure 1, is connected to the local- area network 54' of the network 4' and inputs inquiries from the network 4'.
  • the inquiry mechanisms 118-124 are directly associated with the databases 98-104 and input inquiries directly to these databases 98-104 without using the security mechanisms 106-112, respectively.
  • the functional units 12',14',16',20A' include security mechanisms (SEC) 126,128,130,132, inquiry mecha- nisms (I) 134,136,138,140, and integration mechanisms ( ) 142,144,146,148, respectively.
  • the knowledge sets 26'-34' are interconnected with the local-area network 54' through the integration mechanisms 142-148 and security mechanisms 126-132, respectively.
  • the security mechanisms 126-132 and inquiry mechanisms 134-140 have similar functions as the functions of the security mechanisms 106-112 and inquiry mechanisms 118-124, respectively.
  • Each of the security mechanisms 126-132 permits authorized inquiries from selected locations and, also, prohibits unauthorized inquiries from non-selected locations on the wide-area network 4'.
  • the inquiry mechanisms 134-140 input inquiries directly to the local-area network 54' for processing by the search mechanism 78'.
  • the search mechanism 78' searches selected databases 98-104 and/or selected knowledge sets 26'-34' in response to each of such inqui ⁇ ries in order to determine whether the knowledge sets 26'- 34' and/or 90-96 contain information pertinent to the inquiry.
  • the search mechanism 78' which is described in greater detail below with Figure 6, retrieves the information pertinent to the inquiry from the selected knowledge sets 26'-34' and/or 90-96.
  • the knowledge set 26' includes a plurality of characteristics 80' (e.g., various parameters such as pressures, flows, temperatures, etc.) associated with the operation of the functional unit 12' of the industrial process 6'.
  • characteristics 80' are periodically sensed and monitored by a plurality of real ⁇ time data acquisition units (R/T) 150A,150B,150C,150D.
  • R/T real ⁇ time data acquisition units
  • Each of the units 150A-150D acquires real-time values of the characteristics 80' and periodically broadcasts such real-time values to the local-area network 54' for shared usage by the functional units 12'-20A'.
  • the knowledge set 26' also includes an historical database 152 which is connected to the local-area network 54'.
  • the real-time data acquisition units 150A-150D provide a mechanism for acquiring real-time values of the characteristics 80'.
  • the local-area network 54' provides a transfer mechanism for transferring the real ⁇ time values to the historical database 152 which periodi ⁇ cally receives such values from the network 54' for storage as historical values.
  • the historical database 152 periodi ⁇ cally receives selected real-time values of the character ⁇ istics 80' from the local-area network 54' and stores historical values within the database 152.
  • Each historical value includes a sample of a selected real-time value along with the time and date of the sample.
  • the other functional units 14',16',20A' also include historical databases 154,156,158, respectively, which operate in a similar manner as the historical data ⁇ base 152.
  • the databases 152-158 collectively form a database 159 maintained by the industrial process 6' for storing the information of the knowledge sets 26'-34'.
  • the local-area network 54' links the databases 152-158 to the wide-area network 4' which, with the local-area network 56', links these databases 152-158 to the database 105 of the external entity 10'.
  • the information system 2' manages operation of the industrial process 6' using the local knowledge sets 26'-34' and the external knowledge sets 90-96.
  • the inquiry mechanism 134 for example, inputs an inquiry related to the operation of the first industrial process 6' and, then, the search mechanism 78' searches one or more of the local historical databases 152-158 and/or external databases 98-104 in response to the inquiry.
  • the integration mechanism 142 includes artificial intelligence for integrating the real-time values of the characteristics 80' with the historical values of one or more of the characteristics 80' and with the knowledge set 26' according to a predetermined set of rules in order to analyze the operation of the industrial process 6'.
  • the other integration mechanisms 144-148 operate in a similar manner as the integration mechanism 142.
  • Figure 3 illustrates another information system 2" including the search mechanism 78 of Figure 1 for an electric energy enterprise 6", such as, for example, a nuclear utility.
  • the information system 2" also includes a maintenance database 42', an engineering database 44', and a human resources database 46' of the nuclear utility 6".
  • the information system 2" further includes two external databases 50',52' associated with two external entities 10A,10B, respectively.
  • the exemplary entities 10A,10B are external electric energy enterprises, such as, for example, other nuclear utilities.
  • the search mechanism 78 which is discussed in greater detail below with Figures 4 and 5, includes an artificial intelligence (Al) decision task broker which integrates the exemplary databases 42',44',46' with the exemplary external industry databases 50',52'.
  • Al artificial intelligence
  • the exemplary nuclear utility 6" includes characteristics 80" (e.g., various parameters such as pressures, flows, temperatures, etc.) associated with the operation of the utility 6". These characteristics 80", in turn, are periodically sensed and monitored by a real ⁇ time data acquisition system 160. The system 160 acquires real-time values of the characteristics 80" and periodi ⁇ cally broadcasts such values on line 162 to the wide-area network 4".
  • characteristics 80 e.g., various parameters such as pressures, flows, temperatures, etc.
  • the system 160 transfers the real-time values to the real-time data filters 164,166 on lines 168,170, respectively.
  • each of the filters 164,166 periodically receives selected real-time values of the characteristics 80" from the system 160 on the lines 168,170.
  • the filters 164,166 store the historical values, as discussed above with Figure 2, within the databases 42',44', respectively. In this manner, the system 160 acquires real-time values of the characteristics 80' and transfers such characteristics to the real-time data filters 164,166.
  • the filters 164,166 provide a mechanism for periodically receiving the real-time values from the system 160 and storing some of such values as historical values in the databases 42',44', respectively.
  • the search mechanism 78 is interconnected with a network interface (I/F) 79 which is connected to the network 4" by line 171.
  • the real-time values from the system 160 are periodically broadcast to the search mecha ⁇ nism 78 by the network 4".
  • the databases 42',44',46',50',52' include network interfaces (not shown) and are connected to the network 4" by lines 172,174,176,178,180, respectively.
  • An inquiry mechanism 182 which is similar to the inquiry mechanisms 66-76 of Figure 1, includes a network interface (not shown) and is connected to the network 4" by line 184.
  • the network interface 79 of the search mechanism 78 provides a plurali- t y o f l o g i c a l c o n n e c t i o n s 162A,172A,174A,176A,178A,180A,184A which correspond to the lines 162,172,174,176,178,180,184, respectively.
  • the inquiry mechanism 182 also includes a plurali ⁇ ty of individual inquiry mechanisms 186,188,190,192 which generally provide standard queries, ad hoc queries, moni ⁇ toring queries, and fixed-variable queries, respectively.
  • the inquiry mechanism 186 inputs various predetermined standard inquiries (e.g., "What is the present cost per KW-H of generated electricity at the current power demand?") .
  • the inquiry mechanism 188 is similar to the inquiry mechanism 186 and inputs various user-specified inquiries.
  • the inquiry mechanism 190 is similar to the inquiry mechanism 186 and periodically (i.e., at a regular time interval such as, for example, every minute, every hour, every 1:27:32 hours, every day, etc.) inputs various predetermined inquiries.
  • the inquiry mechanism 192 is similar to the inquiry mechanism 188 and inputs various user-specified inquiries.
  • the inquiry mechanism 192 substitutes a selected value for one of the real-time or historical values of the characteristics 80".
  • the inquiry mechanism 192 simulates a hypothetical condition related to the operation of the industrial process 6" (e.g., "What is the present cost per KW-H of generated electricity assuming a current power demand of 90%?") .
  • the search mechanism 78 integrates the information pertinent to the inquiry with at least some of the characteristics 80" according to a predetermined set of rules in order to evaluate a portion of the opera ⁇ tion of the industrial process 6".
  • FIG 4 a block diagram of the search mechanism and Al decision task broker 78 is illus ⁇ trated.
  • Figure 4 also illustrates the inquiry mechanism 182 and the databases 42',44',46' of Figure 3 in addition to an external database (XY) 194, although the invention is applicable to any number of inquiry mechanisms, local databases or external databases.
  • the database 194 is connected to the network 4" by line 195 and is logically connected to the task broker 78 by logical connection 195A.
  • the task broker 78 includes an Al coordinator 196 which receives the inquiries from the inquiry mechanism 182 on logical connection 184A. As discussed below, the coordinator 196 provides Al filtering for each inquiry and directs each inquiry to selected databases 42',44',46',194 as a function of the content of the particular inquiry. With such Al filtering, for example, local inquiries of the inquiry mechanisms 66-76 of Figure 1 to the respective individual local databases 42-52 do not create additional contention for access to the other databases of the system 2.
  • the task broker 78 also includes a plurality of Al mechanisms 198,200,202,204 associated with the exemplary databases 42',44',46',194, respectively.
  • the Al coordina ⁇ tor 196 uses a set of rules (see, for example, Table I and the rule-based Al decision mechanisms 206,208,210,212 of Figure 5 below) and selects one or more of the databases 42',44',46',194 as a function of each inquiry. Then, the coordinator 196 forwards the inquiry to one or more of the Al mechanisms 198,200,202,204 associated with the selected databases 42',44',46',194, respectively. In turn, each of such associated Al mechanisms
  • the 198.200.202.204 uses another set of rules (see, for exam ⁇ ple, Table II and the rule-based Al decision mechanisms 214,216,218,220 of Figure 5 below) to access the databases 42',44',46',194, respectively, and determine a response to the inquiry.
  • the Al mechanisms 198,200,202,204 include experience sets
  • Figure 5 illustrates another block diagram of the task broker 78 of Figure 4 which coordinates answers from the databases 42',44',46',194 of Figure 4 in response to each inquiry.
  • the coordinator 196 includes rule-based Al decision mechanisms 206,208,210,212 which are associated with the databases 42',44',46',194, respectively.
  • the decision mechanisms 206,208,210,212 determine whether the inquiry is for the associated databases 42',44',46',194, and forward the inquiry to the corresponding rule-based Al decision mechanisms 214,216,218,220 which are associated with the Al mechanisms 198,200,202,204, respectively, of Figure 4.
  • each of the rule-based Al decision mechanisms 214,216,218,220 queries the corresponding databases 42',44',46',194, respectively, of Figure 4. Then, these rule-based Al decision mechanisms 214,216,218,220 retrieve information pertinent to the inquiry and provide the corresponding responses to a query/response coordinator 221 on lines 222,224,226,228, respectively.
  • Inquiry I illustrates the operation of the task broker 78 of Figure 4 and the coordinator 196 of Figures 4 and 5. In ⁇ uirv I
  • the exemplary Inquiry I is "How long until failure of PUMP 2A?" This inquiry is parsed by the rule-based Al decision mechanisms 206,208,210,212 of Figure 5 as shown in Table I below.
  • the term "PUMP”, which is a mechanical device, is applicable to the maintenance database 42', the engineering database 44' and the external utility database 194, but is not applicable to the human resources database 46'.
  • the term “HOW LONG UNTIL”, which is related to a schedule, is applicable to all of the databases 42',44',46',194.
  • the terms "FAILURE OF” and “2A”, which modify "PUMP", are not included in this analy ⁇ sis by the Al decision mechanisms 206-212.
  • the term “HOW LONG UNTIL” implies that the rule “[time]” should be used for the databases 42',44',46',194.
  • the term “PUMP 2A” implies that: the "maintenance logs” table should be consulted with the attribute " ⁇ PUMP 2A>” in the database 42' in order to examine the recommended overhaul time for such pump; the "design parameters” table should be consulted with the attribute " ⁇ PUMP 2A>” in the database 44' in order to examine the impact of real versus recommended operating conditions on the expected operating time for such pump; and the "parameters” table should be consulted with the attribute " ⁇ PUMP 2A>” for the database 194 in order to examine the history of similar related pumps at other industrial processes. Since the database 46' pertains to human resources, and not to mechanical devices, the term “PUMP 2A” implies no meaning for such database 46'.
  • the term “FAILURE OF” implies that: the attribute " ⁇ recommended overhaul time>” should be used for the database 42'; the attribute " ⁇ FMEA and PRA data>” should be used for the database 44'; and the attribute “ ⁇ MTBF>” should be used for the database 194.
  • the term “FAILURE OF” also implies that: the rule “[time - time since last maintenance]” should be used for the database 42'; and the rule “[time - time already operating]” should be used for the database 194.
  • the terms “MTBF”, “FMEA” and “PRA” refer to "Mean Time Between Failures", “Failure Modes and Effects Analysis” and “Probabilistic Risk Assess- ment”, respectively. Since the database 46' pertains to human resources, and since the term “FAILURE OF” modifies a mechanical device, such term implies no meaning for the database 46'.
  • ⁇ PUMP 2A> 450 hours for "time” and for "time since last maintenance"
  • the databases 42',44',194 are accessed, as a function of the Al decision, by the rule-based Al decision mechanisms 214,216,220 of Figure 5, respectively, each of which returns one or more variables.
  • the rule-based Al decision mechanisms 214,216,220 generally apply the appropriate rule and return the resulting answer to the query/response coordinator 221 on lines 222,224,228, respectively.
  • the rule- based Al decision mechanism 218 does not access the data ⁇ base 46' because no Al decision was reached as indicated in Table III, above. Accordingly, no answer is returned to the query/response coordinator 221 on line 226.
  • the rule-based Al decision mechanism 214 determines a "time” value of 550 hours, a "time since last maintenance" of 100 hours, and returns a result of "550 hours - 100 hours” or "450 hours” on line 222.
  • the rule-based Al decision mechanism 216 determines a "time” value of 250 hours and returns a result of "250" hours on line 224.
  • the Al decision mechanism 216 retrieves and compares expected design parameters and actual real-time data for the PUMP 2A such as running time and operating temperature, flow, motor current, oil viscosity or pressure.
  • the Al rules examine, for example, trends, maximums, minimums and time at or above operating limits.
  • the Al rules indicate that, based on real operating conditions, PUMP 2A should fail after 250 hours. Also, the rule-based Al decision mecha ⁇ nism 220 determines a "time" value of 300 hours for a related pump in the external database 194 and determines that the "time already operating" of the particular PUMP 2A is not available in the external database 194. In turn, the rule-based Al decision mechanism 220 returns a result of "300 hours - time already operating" on line 228.
  • the query/response coordinator 221 of the Al coordinator 196 determines, for PUMP 2A, a "time already operating" of 100 hours (which, in this example, is the same time as the "time since last maintenance") from the real-time data acquisition system 160 on logical connection 162A of Figure 3. Then, the Al coordinator 196 calculates the net time of 200 hours (i.e., "300 hours - 100 hours").
  • the query/response coordinator 221 After delaying for a predetermined time and receiving no response from the rule-based Al decision mechanism 218 on line 226, the query/response coordinator 221 averages the net times (i.e., 450, 250 and 200 hours) from the databases 42',44',194 and determines the answer 229 to the inquiry "How long until failure of PUMP 2A?" to be 300 hours.
  • the block diagram of Figure 6 illustrates general ⁇ ly another information system 230 similar to the system 2' of Figure 2.
  • the system 230 includes a wide-area network 232 which integrates four different databases 42",44",46",194' of four electric power generating enterprises such as, for example, electric power generating plants Of UTILITY W, UTILITY X, UTILITY Y, UTILITY Z, respectively.
  • the system 230 also includes two inquiry mechanisms 233,234 associated with the databases 42",44" for inputting an inquiry to the associated databases 42",44", respectively, and/or to the network 232.
  • the exemplary databases 42",44",46",194' facilitate the sharing of utility industry information such as, for example, averages, maximums, minimums and means of particu ⁇ lar industry characteristics, as well as specific informa ⁇ tion regarding the functional units (not shown) of each of the utilities.
  • utility industry information such as, for example, averages, maximums, minimums and means of particu ⁇ lar industry characteristics, as well as specific informa ⁇ tion regarding the functional units (not shown) of each of the utilities.
  • the actual names of the other utilities are unknown to any particular utility and, instead, the utility names are merely generically known (i.e., UTILITY W, UTILITY X, UTILITY Y and UTILITY Z) in order to provide a level of protection of commercially sensitive information.
  • the exemplary network 232 is similar to the network 4' of Figure 2 and generally provides a mechanism for linking the individual databases 42",44",46",194', the inquiry mechanisms 233,234, and the task broker 78'.
  • the databases 42",44",46",194' are connected to the network 232 by network interfaces (I/F) 235A,235B,235C,235D, respectively.
  • the network interfaces 235A,235B also connect the inquiry mechanisms 233,234, respectively, to the network 232.
  • the task broker 78' similarly includes a network interface (I/F) 236 which is similar to the network interface 79 of Figure 3.
  • Inquiry II illustrates the operation of the coordinator 196' of Figure 6. Inquiry II
  • the exemplary Inquiry II is "Schedule, 6 months from today, a crew to rebuild pump 2A.” This inquiry is parsed by the rule-based Al decision mechanisms
  • the rule-based Al decision mechanisms 214',216',218',220' of Figure 6 access the databases 42",44",46",194', respectively, as a function of the Al decision and generally return "size", "cost” and "duration" variables for the utilities UTILITY W, UTILITY X, UTILITY Y, UTILITY Z, respectively.
  • the rule-based Al decision mechanisms 214',216',218',220' generally apply the appropriate rule and return the result ⁇ ing answer to the query/response coordinator 221' on lines 222',224',226',228', respectively.
  • the query/response coordinator 221' of the Al coordinator 196' optimizes the resulting answer to the inquiry in terms of, for example, cost.
  • the que ⁇ ry/response coordinator 221' determines the response to the inquiry "Schedule, 6 months from today, a crew to rebuild pump 2A.” to be a crew from UTILITY X of size 2 for 7 days at a cost of $5000, although the query/response coordinator 221' may, alternatively, optimize the answer in terms of, for example, duration and, hence, determine the response to this inquiry to be a crew from UTILITY Z of size 3 for l day at a cost of $7500. In either case, the response associated with the UTILITY W of size 0 indicates that no crew is available, six months from today, for the exemplary inquiry.
  • Figure 7 illustrates generally another information system 240 similar to the system 2" of Figure 3.
  • the system 240 includes a wide-area network 241 which inte ⁇ grates a database 242 of an electric power generating enterprise 244 (e.g., a nuclear power generating plant) and an external industry database 246 of an entity 248 outside of the enterprise 244.
  • the system 240 also includes the inquiry mechanism 182 of Figure 3 associated with the database 242 for inputting inquiries.
  • the exemplary entity 248 is a plurality of vendors 250,252,254,256 of the enterprise 244.
  • the exemplary database 246 includes information such as, for example, data associated with the products and services of each of the vendors 250-256.
  • Figure 8 illustrates generally another information system 258 similar to the system 240 of Figure 7.
  • the system 258 includes a wide-area network 260 which inte ⁇ grates a plurality of databases 262,264,266 of individual electric power generating facilities such as nuclear power generating plants 268,270,272, respectively, and two external industry databases 274,276.
  • the plants 268-272 are part of an electric power generating enterprise 278.
  • the two databases 274,276 are maintained by two vendors 280,282, respectively, of the enterprise 278.
  • the system 258 also includes the inquiry mechanism 182 of Figure 3 associated with the database 262 for inputting inquiries.
  • the vendors 280,282 form an entity 284 outside of the enterprise 278.
  • the databases 274,276 include information such as, for example, data associated with the products and services of each of the vendors 280,282, respectively, as well as general industry data for other electric power generating enterprises (not shown) .
  • the database 276 further includes a knowledge set 286 representative of regulatory information pertaining to the enterprise 278 which is maintained by the vendor 282.
  • Figure 9 illustrates generally another information system 288 similar to the system 240 of Figure 7.
  • the system 288 includes a wide-area network 290 which inte ⁇ grates a maintenance database 292, an engineering database 294, and a human resources database 296 of an electric energy enterprise 298 (e.g., a nuclear power generating plant) with two external vendor databases 300,302 outside of the enterprise 298.
  • the databases 300,302 are main ⁇ tained by vendors 304,306, respectively, of the enterprise 298.
  • the system 288 also includes the inquiry mechanism 182 of Figure 3 associated with the database 292 for inputting inquiries.
  • the database 300 includes information such as, for example, data associated with the products and services of the vendor 304.
  • the database 302 includes a plurality of databases 302A (DB1) , 302B (DB2) , 302C (DB3) corresponding to the maintenance database 292, the engi- neering database 294, and the human resources database 296, respectively.
  • the vendor 306 maintains general industry data for other electric power generating enterprises (not shown) in the databases 302A-302C.
  • Figure 10 is a block diagram illustrating an alternative information system 308 which is similar to the information system 2' of Figure 2.
  • the system 308 includes the search mechanism 78' and the inquiry mechanism 134 of Figure 2 along with databases 310,312,314 of power plants 316,318,320, respectively, of an electric power generating enterprise 322.
  • the system 308 also includes two external industry databases 324,326 outside of the enterprise 322.
  • the system 308 further includes a wide-area network 328 for linking the individual power plant databases 310-314, external industry databases 324-326 and the search mecha ⁇ nism 78'.
  • the database 324 is maintained by a vendor 330 of the enterprise 322.
  • the inquiry mechanism 134 is similar to the inquiry mechanism 182 of Figure 3 and includes the inquiry mechanisms 186-192 thereof.
  • 2,2',2",230,240,258,288,308 disclosed herein may, for example, be utilized to diagnose the expected failure time of a selected component of an industrial process and, therefore, may further be used to schedule maintenance related activities for such component.
  • diagnosis may be performed using knowledge sets in one or more databases associated with the industrial process, with other databas ⁇ es associated with "competing" industrial processes and/or component vendors of such industrial process, and/or with other industry databases.
  • diagnosis may be repeated periodically using real-time and historical values related to characteristics of the industrial process or, alternatively, may be selected on demand using simulat ⁇ ed values related to such characteristics in order to plan for hypothetical scenarios related to the industrial process.
  • the exemplary information systems 2,2',2",230,240,258,288,308 may also be utilized to schedule manpower for expected maintenance of components using the most economical and/or timely source of such manpower from multiple "competing" industrial processes and/or multiple service vendors.
  • the exempla ⁇ ry information systems may be utilized to determine the availability of replacement components using the most economical and/or timely source for such components from multiple "competing" industrial processes and/or multiple component vendors. In this manner, for example, physical resources, human resources and/or capital resources are efficiently allocated and utilized by a plurality of industrial processes and/or industrial process vendors.
  • the exemplary local and external industrial processes may either be part of the same enterprise or else may be part of different "competing" enterprises.

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Abstract

Un système d'information (2) gère des unités fonctionnelles (12-20) remplissant une fonction relative aux opérations d'un processus industriel ou d'une entreprise de production d'électricité (6), comme par exemple une centrale nucléaire. Les unités fonctionnelles (12-20) conservent un ensenble de connaissances (26-34) représentatif de l'information concernant leur fonctionnement. Le système d'information (2) comprend une pluralité de premières bases de données (40-48) associées avec les unités fonctionnelles (12-20) pour enregistrer les ensembles de connaissances (26-34) conservés par celles-ci; plusieurs secondes bases de données (50-52) associées avec des entités (8-10) tels que des vendeurs (10) ou d'autres entreprises (8) externes à l'entreprise d'électricité (6), pour enregistrer les jeux d'informations (36-38) conservés par les entités (8-10); un réseau de communications à distance (4) pour relier chacune des premières et secondes bases de données (40-52); un mécanisme d'interrogation (66-76) pour entrer une demande de renseignements au niveau des premières et des secondes bases de données (40-52); et un mécanisme d'intelligence artificielle (78) pour effectuer des recherches dans les premières et secondes bases de données (40-52) en réponse à la demande de renseignements, pour déterminer si les ensembles de connaissances (26-38) des premières et secondes bases de données (40-52) contiennent une information pertinente par rapport à la demande de renseignements, et extraire cette information pertinente des premières et secondes bases de données (40-52).
PCT/US1996/007266 1995-06-05 1996-05-20 Systeme d'information integre pour un processus industriel et une entite externe WO1996039658A1 (fr)

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1990007152A1 (fr) * 1988-12-14 1990-06-28 Digital Equipment Corporation Systeme expert modulaire fonde sur une memoire auxiliaire
WO1992014207A1 (fr) * 1991-02-05 1992-08-20 Storage Technology Corporation Procedure d'entretien declenchee par la machine elle-meme, effectuee par un systeme expert a structure hierarchique
US5412756A (en) * 1992-12-22 1995-05-02 Mitsubishi Denki Kabushiki Kaisha Artificial intelligence software shell for plant operation simulation

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1990007152A1 (fr) * 1988-12-14 1990-06-28 Digital Equipment Corporation Systeme expert modulaire fonde sur une memoire auxiliaire
WO1992014207A1 (fr) * 1991-02-05 1992-08-20 Storage Technology Corporation Procedure d'entretien declenchee par la machine elle-meme, effectuee par un systeme expert a structure hierarchique
US5412756A (en) * 1992-12-22 1995-05-02 Mitsubishi Denki Kabushiki Kaisha Artificial intelligence software shell for plant operation simulation

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Title
BRANDIN B ET AL: "THE CONTROL AND SUPERVISION OF GROUPS OF ELEVATORS USING THE BLACKBOARD ARCHITECTURE APPROACH", PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS, CAMBRIDGE, MA., NOV. 14 - 17, 1989, vol. 1 OF 3, 14 November 1989 (1989-11-14), INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS, pages 99 - 104, XP000129755 *
KOJIMA Y ET AL: "THE DEVELOPMENT OF POWER SYSTEM RESTORATION METHOD FOR A BULK POWER SYSTEM BY APPLYING KNOWLEDGE ENGINEERING TECHNIQUES", IEEE TRANSACTIONS ON POWER SYSTEMS, vol. 4, no. 3, August 1989 (1989-08-01), pages 1228 - 1235, XP000045938 *

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