WO2021202145A1 - Procédé optimal de traitement d'événements de fabrication par lots ayant une complexité de calcul linéaire - Google Patents

Procédé optimal de traitement d'événements de fabrication par lots ayant une complexité de calcul linéaire Download PDF

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Publication number
WO2021202145A1
WO2021202145A1 PCT/US2021/023472 US2021023472W WO2021202145A1 WO 2021202145 A1 WO2021202145 A1 WO 2021202145A1 US 2021023472 W US2021023472 W US 2021023472W WO 2021202145 A1 WO2021202145 A1 WO 2021202145A1
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WIPO (PCT)
Prior art keywords
event
data object
field
frame
batch
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PCT/US2021/023472
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English (en)
Inventor
Sunil GOLANI
Ramanuja Reddy PUASAPATI
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Honeywell International Inc.
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Publication of WO2021202145A1 publication Critical patent/WO2021202145A1/fr

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Definitions

  • Various embodiments of the present invention address technical challenges related to manufacturing batch event processing.
  • Various embodiments of the present invention address the shortcomings of existing manufacturing processing systems and disclose various techniques for efficiently and reliably performing manufacturing batch event processing.
  • embodiments of the present invention provide methods, apparatus, systems, computing devices, and/or the like for performing manufacturing batch event processing.
  • Certain embodiments utilize systems, methods, and computer program products that perform manufacturing batch event processing using at least one of event frame stack frame data objects, temporary event frame stack data objects, lexical normalizations of batch event data objects, and/or the like.
  • the method comprises identifying an batch event data object for the manufacturing process, wherein the batch event data object comprises one or more event fields, and wherein each event field of the one or more event fields is associated with an event value; generating an event frame stack data object based on the batch event data object, wherein generating the event frame stack data object comprises: (i) for each incoming start-type event field of the one or more event fields, adding a start event frame that corresponds to the incoming start-type event field to the event frame stack data object as a top event frame for the event frame stack data object; (ii) for each incoming end- type event field of the one or more event fields: (a) determining whether the event value of a top event field of the event frame stack data object corresponds to the event value of the incoming end-type event field; (b) in response to determining that the event value of the top event field fails to correspond to the event value of the incoming end-type event field, removing the top
  • a computer program product comprises at least one computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising executable portions configured to identify an batch event data object for the manufacturing process, wherein the batch event data object comprises one or more event fields, and wherein each event field of the one or more event fields is associated with an event value; generate an event frame stack data object based on the batch event data object, wherein generating the event frame stack data object comprises: (i) for each incoming start-type event field of the one or more event fields, adding a start event frame that corresponds to the incoming start-type event field to the event frame stack data object as a top event frame for the event frame stack data object; (ii) for each incoming end-type event field of the one or more event fields: (a) determining whether the event value of a top event field of the event frame stack data object corresponds to the event value of the incoming end-type event field; (b) in response to
  • an apparatus comprising at least one processor and at least one memory including computer program code.
  • at least one memory and the computer program code is configured to, with the processor, cause the apparatus to identify an batch event data object for the manufacturing process, wherein the batch event data object comprises one or more event fields, and wherein each event field of the one or more event fields is associated with an event value; generate an event frame stack data object based on the batch event data object, wherein generating the event frame stack data object comprises: (i) for each incoming start-type event field of the one or more event fields, adding a start event frame that corresponds to the incoming start-type event field to the event frame stack data object as a top event frame for the event frame stack data object; (ii) for each incoming end- type event field of the one or more event fields: (a) determining whether the event value of a top event field of the event frame stack data object corresponds to the event value of the incoming end-type event field; (b) in response to
  • FIG. 1 provides an exemplary overview of an architecture that can be used to practice embodiments of the present invention.
  • FIG. 2 provides an example batch event processing computing device in accordance with some embodiments discussed herein.
  • FIG. 3 provides an example batch event data source computing device in accordance with some embodiments discussed herein.
  • FIG. 4 provides an example distributed control system (DCS) server device in accordance with some embodiments discussed herein.
  • DCS distributed control system
  • FIG. 5 provides an example manufacturing execution system (MES) server device in accordance with some embodiments discussed herein.
  • MES manufacturing execution system
  • FIG. 6 is a data flow diagram of an example process for batch event processing with respect to a manufacturing process in accordance with some embodiments discussed herein.
  • FIG. 7 provides an operational example of an batch event data object in accordance with some embodiments discussed herein.
  • FIG. 8 provides an operational example of an event hierarchy data object in accordance with some embodiments discussed herein.
  • FIG. 9 provides an operational example of a lexical format conversion rule data object in accordance with some embodiments discussed herein.
  • FIG. 10 provides an operational example of an event frame stack data object in accordance with some embodiments discussed herein.
  • FIG. 11 is a flowchart diagram of an example process for processing a start-type event field within an batch event data object in relation to an event frame stack data object in accordance with some embodiments discussed herein.
  • FIG. 12 is a flowchart diagram of an example process for processing an end-type event field within an batch event data object in relation to an event frame stack data object in accordance with some embodiments discussed herein.
  • FIG. 13 provides an operational example of adding an end event frame to a temporary event frame stack data object in accordance with some embodiments discussed herein.
  • Various embodiments of the present invention provide techniques for modeling event batch data for manufacturing processes in a hierarchical manner, which in turns enables utilizing a stack data object that defines, via its top event frame, which event fields a computer system should look for during each iteration of a manufacturing process monitoring event.
  • various embodiments of the present invention avoid the need to analyze event fields that do not either begin a hierarchically-inferior event level or end the existing most- hierarchically-inferior event level for the stack data object.
  • various embodiments of the present invention reduce the computational complexity of searching within an event batch for appropriate event fields to a linear computational complexity. Accordingly, various embodiments of the present invention make substantial technical contributions to performing automated manufacturing batch event processing by improving efficiency of various existing automated manufacturing batch event processing solutions.
  • Embodiments of the present invention can be implemented in various ways, including as computer program products that comprise articles of manufacture.
  • Such computer program products include one or more software components including, for example, software objects, methods, data structures, or the like.
  • a software component is coded in any of a variety of programming languages.
  • An illustrative programming language can be a lower-level programming language such as an assembly language associated with a particular hardware architecture and/or operating system platform.
  • a software component comprising assembly language instructions can require conversion into executable machine code by an assembler prior to execution by the hardware architecture and/or platform.
  • Another example programming language can be a higher-level programming language that can be portable across multiple architectures.
  • a software component comprising higher-level programming language instructions can require conversion to an intermediate representation by an interpreter or a compiler prior to execution.
  • programming languages include, but are not limited to, a macro language, a shell or command language, a job control language, a script language, a database query or search language, and/or a report writing language.
  • a software component comprising instructions in one of the foregoing examples of programming languages can be executed directly by an operating system or other software component without having to be first transformed into another form.
  • a software component can be stored as a file or other data storage construct.
  • Software components of a similar type or functionally related can be stored together such as, for example, in a particular directory, folder, or library.
  • Software components can be static (e.g., pre-established or fixed) or dynamic (e.g., created or modified at the time of execution).
  • a computer program product includes a non-transitory computer-readable storage medium storing applications, programs, program modules, scripts, source code, program code, object code, byte code, compiled code, interpreted code, machine code, executable instructions, and/or the like (also referred to herein as executable instructions, instructions for execution, computer program products, program code, and/or similar terms used herein interchangeably).
  • Such non-transitory computer-readable storage media include all computer-readable media (including volatile and non-volatile media).
  • a non-volatile computer-readable storage medium can include a floppy disk, flexible disk, hard disk, solid-state storage (SSS) (e.g., a solid state drive (SSD), solid state card (SSC), solid state module (SSM), enterprise flash drive, magnetic tape, or any other non-transitory magnetic medium, and/or the like.
  • SSD solid state drive
  • SSC solid state card
  • SSM solid state module
  • enterprise flash drive magnetic tape, or any other non-transitory magnetic medium, and/or the like.
  • a non-volatile computer-readable storage medium can also include a punch card, paper tape, optical mark sheet (or any other physical medium with patterns of holes or other optically recognizable indicia), compact disc read only memory (CD-ROM), compact disc-rewritable (CD-RW), digital versatile disc (DVD), Blu-ray disc (BD), any other non-transitory optical medium, and/or the like.
  • Such a non-volatile computer-readable storage medium can also include read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory (e.g., Serial, NAND,
  • a non volatile computer-readable storage medium can also include conductive-bridging random access memory (CBRAM), phase-change random access memory (PRAM), ferroelectric random-access memory (FeRAM), non-volatile random-access memory (NVRAM), magnetoresistive random- access memory (MRAM), resistive random-access memory (RRAM), Silicon-Oxide-Nitride- Oxide-Silicon memory (SONOS), floating junction gate random access memory (FJGRAM), Millipede memory, racetrack memory, and/or the like.
  • CBRAM conductive-bridging random access memory
  • PRAM phase-change random access memory
  • FeRAM ferroelectric random-access memory
  • NVRAM non-volatile random-access memory
  • MRAM magnetoresistive random- access memory
  • RRAM Silicon-Oxide-Nitride- Oxide-Silicon memory
  • FJGRAM floating junction gate random access memory
  • Millipede memory racetrack memory, and/or the like.
  • a volatile computer-readable storage medium can include random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), fast page mode dynamic random access memory (FPM DRAM), extended data-out dynamic random access memory (EDO DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), double data rate type two synchronous dynamic random access memory (DDR2 SDRAM), double data rate type three synchronous dynamic random access memory (DDR3 SDRAM), Rambus dynamic random access memory (RDRAM), Twin Transistor RAM (TTRAM), Thyristor RAM (T-RAM), Zero-capacitor (Z-RAM), Rambus in-line memory module (RIMM), dual in-line memory module (DIMM), single in-line memory module (SIMM), video random access memory (VRAM), cache memory (including various levels), flash memory, register memory, and/or the like.
  • RAM random access memory
  • DRAM dynamic random access memory
  • SRAM static random access memory
  • FPM DRAM fast page mode dynamic random access
  • embodiments of the present invention can also be implemented as methods, apparatus, systems, computing devices, computing devices, and/or the like. As such, embodiments of the present invention can take the form of an apparatus, system, computing device, computing device, and/or the like executing instructions stored on a computer-readable storage medium to perform certain steps or operations. Thus, embodiments of the present invention can also take the form of an entirely hardware embodiment, an entirely computer program product embodiment, and/or an embodiment that comprises combination of computer program products and hardware performing certain steps or operations.
  • retrieval, loading, and/or execution can be performed in parallel such that multiple instructions are retrieved, loaded, and/or executed together.
  • such embodiments can produce specifically-configured machines performing the steps or operations specified in the block diagrams and flowchart illustrations. Accordingly, the block diagrams and flowchart illustrations support various combinations of embodiments for performing the specified instructions, operations, or steps.
  • FIG. 1 is a schematic diagram of an example architecture 100 for performing batch event processing for a manufacturing process.
  • the architecture 100 includes a distributed control system (DCS) 111 that executes a manufacturing process, where the DCS 111 includes a DCS server device 121 that collects event data related to manufacturing process and provides the collected event data to one or more batch event data source computing devices 102.
  • the batch event data source computing devices 102 is configured to store the event data collected by the DCS server device 121 and provide the stored event data to a batch event processing computing device 106.
  • batch event data source computing devices 102 include cloud storage devices (e.g., data as a service cloud storage devices) as well as batch event data source computing devices 102 that are local to at least one of the batch event processing computing device 106 and/or the DCS server device 121.
  • cloud storage devices e.g., data as a service cloud storage devices
  • batch event data source computing devices 102 that are local to at least one of the batch event processing computing device 106 and/or the DCS server device 121.
  • the batch event processing computing device 106 is configured to process the event data in order to generate manufacturing process monitoring data, such as a tree data object determined based on an event frame stack data object that is in turn determined based on event frames within the event data.
  • the batch event processing computing device 106 is configured to transmit the generated manufacturing process monitoring data to a manufacturing execution system (MES) server device 122 of an MES system 112.
  • MES manufacturing execution system
  • the MES server device 122 is configured to process the manufacturing process monitoring data to generate configuration data that will cause the DCS server device 121 to modify the operation of manufacturing plants associated with the DCS 111 and/or to generate appropriate user interface data for presentation to an administrator user profile associated with the DCS server device 121.
  • the various computing devices discussed above can communicate with each other via bipartite and/or multi-partite communication channels by using one or more communication networks.
  • communication networks include any wired or wireless communication network including, for example, a wired or wireless local area network (LAN), personal area network (PAN), metropolitan area network (MAN), wide area network (WAN), or the like, as well as any hardware, software and/or firmware required to implement it (such as, e.g., network routers, and/or the like).
  • a storage system includes one or more storage units, such as multiple distributed storage units that are connected through a computer network.
  • Each storage unit in a storage subsystem stores at least one of one or more data assets and/or one or more data about the computed properties of one or more data assets.
  • each storage unit in a storage subsystem can include one or more non-volatile storage or memory media including but not limited to hard disks, ROM, PROM, EPROM, EEPROM, flash memory, MMCs, SD memory cards, Memory Sticks, CBRAM, PRAM, FeRAM, NVRAM, MRAM, RRAM, SONOS, FJG RAM, Millipede memory, racetrack memory, and/or the like.
  • non-volatile storage or memory media including but not limited to hard disks, ROM, PROM, EPROM, EEPROM, flash memory, MMCs, SD memory cards, Memory Sticks, CBRAM, PRAM, FeRAM, NVRAM, MRAM, RRAM, SONOS, FJG RAM, Millipede memory, racetrack memory, and/or the like.
  • FIG. 2 provides a schematic of an batch event processing computing device 106 according to one embodiment of the present invention.
  • computing device computer, entity, device, system, and/or similar words used herein interchangeably refers to, for example, one or more computers, computing devices, desktops, mobile phones, tablets, phablets, notebooks, laptops, distributed systems, kiosks, input terminals, servers or server networks, blades, gateways, switches, processing devices, processing entities, set-top boxes, relays, routers, network access points, base stations, the like, and/or any combination of devices or entities adapted to perform the functions, operations, and/or processes described herein.
  • Such functions, operations, and/or processes can include, for example, transmitting, receiving, operating on, processing, displaying, storing, determining, creating/generating, monitoring, evaluating, comparing, and/or similar terms used herein interchangeably. In one embodiment, these functions, operations, and/or processes can be performed on data, content, information, and/or similar terms used herein interchangeably.
  • the batch event processing computing device 106 includes one or more communications interfaces 220 for communicating with various computing devices, such as by communicating data, content, information, and/or similar terms used herein interchangeably that can be transmitted, received, operated on, processed, displayed, stored, and/or the like.
  • the batch event processing computing device 106 includes or is in communication with one or more processing elements 205 (also referred to as processors, processing circuitry, and/or similar terms used herein interchangeably) that communicate with other elements within the batch event processing computing device 106 via a bus, for example.
  • processing elements 205 also referred to as processors, processing circuitry, and/or similar terms used herein interchangeably
  • the processing element 205 can be embodied in a number of different ways.
  • the processing element 205 can be embodied as one or more complex programmable logic devices (CPLDs), microprocessors, multi-core processors, coprocessing entities, application-specific instruction-set processors (ASIPs), microcontrollers, and/or controllers. Further, the processing element 205 can be embodied as one or more other processing devices or circuitry.
  • the term circuitry can refer to an entirely hardware embodiment or a combination of hardware and computer program products.
  • the processing element 205 can be embodied as integrated circuits, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), hardware accelerators, other circuitry, and/or the like.
  • the processing element 205 can be configured for a particular use or configured to execute instructions stored in volatile or non-volatile media or otherwise accessible to the processing element 205. As such, whether configured by hardware or computer program products, or by a combination thereof, the processing element 205 can be capable of performing steps or operations according to embodiments of the present invention when configured accordingly.
  • the batch event processing computing device 106 further includes or is in communication with non-volatile media (also referred to as non-volatile storage, memory, memory storage, memory circuitry and/or similar terms used herein interchangeably).
  • non-volatile media also referred to as non-volatile storage, memory, memory storage, memory circuitry and/or similar terms used herein interchangeably.
  • the non-volatile storage or memory can include one or more non-volatile storage or memory media 210, including but not limited to hard disks, ROM, PROM, EPROM, EEPROM, flash memory, MMCs, SD memory cards, Memory Sticks, CBRAM, PRAM,
  • non-volatile storage or memory media 210 including but not limited to hard disks, ROM, PROM, EPROM, EEPROM, flash memory, MMCs, SD memory cards, Memory Sticks, CBRAM, PRAM,
  • FeRAM FeRAM
  • NVRAM NVRAM
  • MRAM MRAM
  • RRAM SONOS
  • FJGRAM Millipede memory
  • racetrack memory racetrack memory, and/or the like.
  • the non-volatile storage or memory media can store databases, database instances, database management systems, data, applications, programs, program modules, scripts, source code, object code, byte code, compiled code, interpreted code, machine code, executable instructions, and/or the like.
  • database, database instance, database management system, and/or similar terms used herein interchangeably can refer to a collection of records or data that is stored in a computer-readable storage medium using one or more database models, such as a hierarchical database model, network model, relational model, entity- relationship model, object model, document model, semantic model, graph model, and/or the like.
  • the batch event processing computing device 106 further includes or be in communication with volatile media (also referred to as volatile storage, memory, memory storage, memory circuitry and/or similar terms used herein interchangeably).
  • volatile storage or memory can also include one or more volatile storage or memory media 215, including but not limited to RAM, DRAM, SRAM, FPM DRAM, EDO DRAM, SDRAM, DDR SDRAM, DDR2 SDRAM, DDR3 SDRAM, RDRAM, TTRAM, T- RAM, Z-RAM, RIMM, DIMM, SIMM, VRAM, cache memory, register memory, and/or any other type of distributed memory/state management systems.
  • the volatile storage or memory media can be used to store at least portions of the databases, database instances, database management systems, data, applications, programs, program modules, scripts, source code, object code, byte code, compiled code, interpreted code, machine code, executable instructions, and/or the like being executed by, for example, the processing element 205.
  • the databases, database instances, database management systems, data, applications, programs, program modules, scripts, source code, object code, byte code, compiled code, interpreted code, machine code, executable instructions, and/or the like can be used to control certain aspects of the operation of the batch event processing computing device 106 with the assistance of the processing element 205 and operating system.
  • the batch event processing computing device 106 includes one or more communications interfaces 220 for communicating with various computing devices, such as by communicating data, content, information, and/or similar terms used herein interchangeably that can be transmitted, received, operated on, processed, displayed, stored, and/or the like.
  • Such communication can be executed using a wired data transmission protocol, such as fiber distributed data interface (FDDI), digital subscriber line (DSL), Ethernet, asynchronous transfer mode (ATM), frame relay, data over cable service interface specification (DOCSIS), or any other wired transmission protocol.
  • FDDI fiber distributed data interface
  • DSL digital subscriber line
  • Ethernet asynchronous transfer mode
  • ATM asynchronous transfer mode
  • frame relay frame relay
  • DOCSIS data over cable service interface specification
  • the batch event processing computing device 106 can be configured to communicate via wireless external communication networks using any of a variety of protocols, such as general packet radio service (GPRS), Universal Mobile Telecommunications System (UMTS), Code Division Multiple Access 2000 (CDMA2000), CDMA2000 IX (lxRTT), Wideband Code Division Multiple Access (WCDMA), Global System for Mobile Communications (GSM), Enhanced Data rates for GSM Evolution (EDGE), Time Division-Synchronous Code Division Multiple Access (TD-SCDMA), Long Term Evolution (LTE), Evolved Universal Terrestrial Radio Access Network (E-UTRAN), Evolution-Data Optimized (EVDO), High Speed Packet Access (HSPA), High-Speed Downlink Packet Access (HSDPA), IEEE 802.11 (Wi-Fi), Wi-Fi Direct, 802.16 (WiMAX), ultra-wideband (UWB), infrared (IR) protocols, near field communication (NFC) protocols, Wibree, Bluetooth protocols, wireless universal serial bus (USB) protocols, and/or any other wireless GP
  • FIG. 3 provides a schematic of an batch event data source computing device 102 according to one embodiment of the present invention.
  • computing device computer, entity, device, system, and/or similar words used herein interchangeably refers to, for example, one or more computers, computing devices, desktops, mobile phones, tablets, phablets, notebooks, laptops, distributed systems, kiosks, input terminals, servers or server networks, blades, gateways, switches, processing devices, processing entities, set-top boxes, relays, routers, network access points, base stations, the like, and/or any combination of devices or entities adapted to perform the functions, operations, and/or processes described herein.
  • Such functions, operations, and/or processes can include, for example, transmitting, receiving, operating on, processing, displaying, storing, determining, creating/generating, monitoring, evaluating, comparing, and/or similar terms used herein interchangeably. In one embodiment, these functions, operations, and/or processes can be performed on data, content, information, and/or similar terms used herein interchangeably.
  • the batch event data source computing device 102 includes one or more communications interfaces 320 for communicating with various computing devices, such as by communicating data, content, information, and/or similar terms used herein interchangeably that can be transmitted, received, operated on, processed, displayed, stored, and/or the like.
  • the batch event data source computing device 102 includes or is in communication with one or more processing elements 305 (also referred to as processors, processing circuitry, and/or similar terms used herein interchangeably) that communicate with other elements within the batch event data source computing device 102 via a bus, for example.
  • processing elements 305 also referred to as processors, processing circuitry, and/or similar terms used herein interchangeably
  • the processing element 305 can be embodied in a number of different ways.
  • the processing element 305 can be embodied as one or more complex programmable logic devices (CPLDs), microprocessors, multi-core processors, coprocessing entities, application-specific instruction-set processors (ASIPs), microcontrollers, and/or controllers. Further, the processing element 305 can be embodied as one or more other processing devices or circuitry.
  • the term circuitry can refer to an entirely hardware embodiment or a combination of hardware and computer program products.
  • the processing element 305 can be embodied as integrated circuits, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), hardware accelerators, other circuitry, and/or the like.
  • the processing element 305 can be configured for a particular use or configured to execute instructions stored in volatile or non-volatile media or otherwise accessible to the processing element 305. As such, whether configured by hardware or computer program products, or by a combination thereof, the processing element 305 can be capable of performing steps or operations according to embodiments of the present invention when configured accordingly.
  • the batch event data source computing device 102 can further include or be in communication with non-volatile media (also referred to as non-volatile storage, memory, memory storage, memory circuitry and/or similar terms used herein interchangeably).
  • non-volatile media also referred to as non-volatile storage, memory, memory storage, memory circuitry and/or similar terms used herein interchangeably.
  • the non-volatile storage or memory can include one or more non-volatile storage or memory media 310, including but not limited to hard disks, ROM, PROM, EPROM, EEPROM, flash memory, MMCs, SD memory cards, Memory Sticks, CBRAM, PRAM,
  • non-volatile storage or memory media 310 including but not limited to hard disks, ROM, PROM, EPROM, EEPROM, flash memory, MMCs, SD memory cards, Memory Sticks, CBRAM, PRAM,
  • FeRAM FeRAM
  • NVRAM NVRAM
  • MRAM MRAM
  • RRAM SONOS
  • FJGRAM FJGRAM
  • Millipede memory racetrack memory, and/or any other type of distributed memory/state management systems.
  • the non-volatile storage or memory media can store databases, database instances, database management systems, data, applications, programs, program modules, scripts, source code, object code, byte code, compiled code, interpreted code, machine code, executable instructions, and/or the like.
  • database, database instance, database management system, and/or similar terms used herein interchangeably can refer to a collection of records or data that is stored in a computer-readable storage medium using one or more database models, such as a hierarchical database model, network model, relational model, entity- relationship model, object model, document model, semantic model, graph model, and/or the like.
  • the batch event data source computing device 102 can further include or be in communication with volatile media (also referred to as volatile storage, memory, memory storage, memory circuitry and/or similar terms used herein interchangeably).
  • volatile storage or memory can also include one or more volatile storage or memory media 315, including but not limited to RAM, DRAM, SRAM, FPM DRAM, EDO DRAM, SDRAM, DDR SDRAM, DDR2 SDRAM, DDR3 SDRAM, RDRAM, TTRAM, T- RAM, Z-RAM, RIMM, DIMM, SIMM, VRAM, cache memory, register memory, and/or the like.
  • the volatile storage or memory media can be used to store at least portions of the databases, database instances, database management systems, data, applications, programs, program modules, scripts, source code, object code, byte code, compiled code, interpreted code, machine code, executable instructions, and/or the like being executed by, for example, the processing element 305.
  • the databases, database instances, database management systems, data, applications, programs, program modules, scripts, source code, object code, byte code, compiled code, interpreted code, machine code, executable instructions, and/or the like can be used to control certain aspects of the operation of the batch event data source computing device 102 with the assistance of the processing element 305 and operating system.
  • the batch event data source computing device 102 includes one or more communications interfaces 320 for communicating with various computing devices, such as by communicating data, content, information, and/or similar terms used herein interchangeably that can be transmitted, received, operated on, processed, displayed, stored, and/or the like.
  • Such communication can be executed using a wired data transmission protocol, such as fiber distributed data interface (FDDI), digital subscriber line (DSL), Ethernet, asynchronous transfer mode (ATM), frame relay, data over cable service interface specification (DOCSIS), or any other wired transmission protocol.
  • FDDI fiber distributed data interface
  • DSL digital subscriber line
  • Ethernet asynchronous transfer mode
  • ATM asynchronous transfer mode
  • frame relay frame relay
  • DOCSIS data over cable service interface specification
  • the batch event data source computing device 102 can be configured to communicate via wireless external communication networks using any of a variety of protocols, such as general packet radio service (GPRS), Universal Mobile Telecommunications System (UMTS), Code Division Multiple Access 2000 (CDMA2000), CDMA2000 IX (lxRTT), Wideband Code Division Multiple Access (WCDMA), Global System for Mobile Communications (GSM), Enhanced Data rates for GSM Evolution (EDGE), Time Division-Synchronous Code Division Multiple Access (TD-SCDMA), Long Term Evolution (LTE), Evolved Universal Terrestrial Radio Access Network (E-UTRAN), Evolution-Data Optimized (EVDO), High Speed Packet Access (HSPA), High-Speed Downlink Packet Access (HSDPA), IEEE 802.11 (Wi-Fi), Wi-Fi Direct, 802.16 (WiMAX), ultra-wideband (UWB), infrared (IR) protocols, near field communication (NFC) protocols, Wibree, Bluetooth protocols, wireless universal serial bus (USB) protocols, and/or any other protocols
  • FIG. 4 provides a schematic of a DCS server device 121 according to one embodiment of the present invention.
  • the terms computing device, computer, entity, device, system, and/or similar words used herein interchangeably refer to, for example, one or more computers, computing devices, desktops, mobile phones, tablets, phablets, notebooks, laptops, distributed systems, kiosks, input terminals, servers or server networks, blades, gateways, switches, processing devices, processing entities, set-top boxes, relays, routers, network access points, base stations, the like, and/or any combination of devices or entities adapted to perform the functions, operations, and/or processes described herein.
  • Such functions, operations, and/or processes can include, for example, transmitting, receiving, operating on, processing, displaying, storing, determining, creating/generating, monitoring, evaluating, comparing, and/or similar terms used herein interchangeably. In one embodiment, these functions, operations, and/or processes can be performed on data, content, information, and/or similar terms used herein interchangeably.
  • the DCS server device 121 includes one or more communications interfaces 420 for communicating with various computing devices, such as by communicating data, content, information, and/or similar terms used herein interchangeably that can be transmitted, received, operated on, processed, displayed, stored, and/or the like.
  • the batch event data source computing device 102 includes or is in communication with one or more processing elements 405 (also referred to as processors, processing circuitry, and/or similar terms used herein interchangeably) that communicate with other elements within the DCS server device 121 via a bus, for example.
  • processing elements 405 also referred to as processors, processing circuitry, and/or similar terms used herein interchangeably
  • the processing element 405 can be embodied in a number of different ways.
  • the processing element 405 can be embodied as one or more complex programmable logic devices (CPLDs), microprocessors, multi-core processors, coprocessing entities, application-specific instruction-set processors (ASIPs), microcontrollers, and/or controllers. Further, the processing element 405 can be embodied as one or more other processing devices or circuitry.
  • the term circuitry can refer to an entirely hardware embodiment or a combination of hardware and computer program products.
  • the processing element 405 can be embodied as integrated circuits, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), hardware accelerators, other circuitry, and/or the like.
  • the processing element 405 can be configured for a particular use or configured to execute instructions stored in volatile or non-volatile media or otherwise accessible to the processing element 405. As such, whether configured by hardware or computer program products, or by a combination thereof, the processing element 405 can be capable of performing steps or operations according to embodiments of the present invention when configured accordingly.
  • the DCS server device 121 can further include or be in communication with non-volatile media (also referred to as non-volatile storage, memory, memory storage, memory circuitry and/or similar terms used herein interchangeably).
  • the non-volatile storage or memory can include one or more non-volatile storage or memory media 410, including but not limited to hard disks, ROM, PROM, EPROM, EEPROM, flash memory, MMCs, SD memory cards, Memory Sticks, CBRAM, PRAM, FeRAM, NVRAM, MRAM, RRAM, SONOS, FJGRAM, Millipede memory, racetrack memory, and/or any other type of distributed memory/state management systems.
  • the non-volatile storage or memory media can store databases, database instances, database management systems, data, applications, programs, program modules, scripts, source code, object code, byte code, compiled code, interpreted code, machine code, executable instructions, and/or the like.
  • database, database instance, database management system, and/or similar terms used herein interchangeably can refer to a collection of records or data that is stored in a computer-readable storage medium using one or more database models, such as a hierarchical database model, network model, relational model, entity- relationship model, object model, document model, semantic model, graph model, and/or the like.
  • the DCS server device 121 can further include or be in communication with volatile media (also referred to as volatile storage, memory, memory storage, memory circuitry and/or similar terms used herein interchangeably).
  • volatile storage or memory can also include one or more volatile storage or memory media 415, including but not limited to RAM, DRAM, SRAM, FPM DRAM, EDO DRAM, SDRAM, DDR SDRAM, DDR2 SDRAM, DDR3 SDRAM, RDRAM, TTRAM, T-RAM, Z-RAM, RIMM, DIMM, SIMM, VRAM, cache memory, register memory, and/or the like.
  • the volatile storage or memory media can be used to store at least portions of the databases, database instances, database management systems, data, applications, programs, program modules, scripts, source code, object code, byte code, compiled code, interpreted code, machine code, executable instructions, and/or the like being executed by, for example, the processing element 405.
  • the databases, database instances, database management systems, data, applications, programs, program modules, scripts, source code, object code, byte code, compiled code, interpreted code, machine code, executable instructions, and/or the like can be used to control certain aspects of the operation of the DCS server device 121 with the assistance of the processing element 405 and operating system.
  • the DCS server device 121 includes one or more communications interfaces 420 for communicating with various computing devices, such as by communicating data, content, information, and/or similar terms used herein interchangeably that can be transmitted, received, operated on, processed, displayed, stored, and/or the like.
  • Such communication can be executed using a wired data transmission protocol, such as fiber distributed data interface (FDDI), digital subscriber line (DSL), Ethernet, asynchronous transfer mode (ATM), frame relay, data over cable service interface specification (DOCSIS), or any other wired transmission protocol.
  • FDDI fiber distributed data interface
  • DSL digital subscriber line
  • Ethernet asynchronous transfer mode
  • ATM asynchronous transfer mode
  • frame relay frame relay
  • DOCSIS data over cable service interface specification
  • the DCS server device 121 can be configured to communicate via wireless external communication networks using any of a variety of protocols, such as general packet radio service (GPRS), Universal Mobile Telecommunications System (UMTS), Code Division Multiple Access 2000 (CDMA2000), CDMA2000 IX (lxRTT), Wideband Code Division Multiple Access (WCDMA), Global System for Mobile Communications (GSM), Enhanced Data rates for GSM Evolution (EDGE), Time Division- Synchronous Code Division Multiple Access (TD-SCDMA), Long Term Evolution (LTE), Evolved Universal Terrestrial Radio Access Network (E-UTRAN), Evolution-Data Optimized (EVDO), High Speed Packet Access (HSPA), High-Speed Downlink Packet Access (HSDPA), IEEE 802.11 (Wi-Fi), Wi-Fi Direct, 802.16 (WiMAX), ultra-wideband (UWB), infrared (IR) protocols, near field communication (NFC) protocols, Wibree, Bluetooth protocols, wireless universal serial bus (USB) protocols, and/or any other wireless protocol.
  • FIG. 5 provides a schematic of a MES server device 122 according to one embodiment of the present invention.
  • the terms computing device, computer, entity, device, system, and/or similar words used herein interchangeably refer to, for example, one or more computers, computing devices, desktops, mobile phones, tablets, phablets, notebooks, laptops, distributed systems, kiosks, input terminals, servers or server networks, blades, gateways, switches, processing devices, processing entities, set-top boxes, relays, routers, network access points, base stations, the like, and/or any combination of devices or entities adapted to perform the functions, operations, and/or processes described herein.
  • Such functions, operations, and/or processes can include, for example, transmitting, receiving, operating on, processing, displaying, storing, determining, creating/generating, monitoring, evaluating, comparing, and/or similar terms used herein interchangeably. In one embodiment, these functions, operations, and/or processes can be performed on data, content, information, and/or similar terms used herein interchangeably.
  • the MES server device 122 include one or more communications interfaces 520 for communicating with various computing devices, such as by communicating data, content, information, and/or similar terms used herein interchangeably that can be transmitted, received, operated on, processed, displayed, stored, and/or the like.
  • the batch event data source computing device 122 includes or is in communication with one or more processing elements 505 (also referred to as processors, processing circuitry, and/or similar terms used herein interchangeably) that communicate with other elements within the MES server device 122 via a bus, for example.
  • processing elements 505 also referred to as processors, processing circuitry, and/or similar terms used herein interchangeably
  • the processing element 505 can be embodied in a number of different ways.
  • the processing element 505 can be embodied as one or more complex programmable logic devices (CPLDs), microprocessors, multi-core processors, coprocessing entities, application-specific instruction-set processors (ASIPs), microcontrollers, and/or controllers. Further, the processing element 505 can be embodied as one or more other processing devices or circuitry.
  • the term circuitry can refer to an entirely hardware embodiment or a combination of hardware and computer program products.
  • the processing element 505 can be embodied as integrated circuits, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), hardware accelerators, other circuitry, and/or the like.
  • the processing element 505 can be configured for a particular use or configured to execute instructions stored in volatile or non-volatile media or otherwise accessible to the processing element 505. As such, whether configured by hardware or computer program products, or by a combination thereof, the processing element 505 can be capable of performing steps or operations according to embodiments of the present invention when configured accordingly.
  • the MES server device 122 can further include or be in communication with non-volatile media (also referred to as non-volatile storage, memory, memory storage, memory circuitry and/or similar terms used herein interchangeably).
  • non-volatile storage or memory can include one or more non-volatile storage or memory media 510, including but not limited to hard disks, ROM, PROM, EPROM, EEPROM, flash memory, MMCs, SD memory cards, Memory Sticks, CBRAM, PRAM, FeRAM, NVRAM, MRAM, RRAM, SONOS, FJG RAM, Millipede memory, racetrack memory, and/or any other type of distributed memory/state management systems.
  • the non-volatile storage or memory media can store databases, database instances, database management systems, data, applications, programs, program modules, scripts, source code, object code, byte code, compiled code, interpreted code, machine code, executable instructions, and/or the like.
  • database, database instance, database management system, and/or similar terms used herein interchangeably can refer to a collection of records or data that is stored in a computer-readable storage medium using one or more database models, such as a hierarchical database model, network model, relational model, entity- relationship model, object model, document model, semantic model, graph model, and/or the like.
  • the MES server device 122 can further include or be in communication with volatile media (also referred to as volatile storage, memory, memory storage, memory circuitry and/or similar terms used herein interchangeably).
  • volatile storage or memory can also include one or more volatile storage or memory media 515, including but not limited to RAM, DRAM, SRAM, FPM DRAM, EDO DRAM, SDRAM, DDR SDRAM, DDR2 SDRAM, DDR3 SDRAM, RDRAM, TTRAM, T-RAM, Z-RAM, RIMM, DIMM, SIMM, VRAM, cache memory, register memory, and/or the like.
  • the volatile storage or memory media can be used to store at least portions of the databases, database instances, database management systems, data, applications, programs, program modules, scripts, source code, object code, byte code, compiled code, interpreted code, machine code, executable instructions, and/or the like being executed by, for example, the processing element 505.
  • the databases, database instances, database management systems, data, applications, programs, program modules, scripts, source code, object code, byte code, compiled code, interpreted code, machine code, executable instructions, and/or the like can be used to control certain aspects of the operation of the MES server device 122 with the assistance of the processing element 505 and operating system.
  • the MES server device 122 also includes one or more communications interfaces 520 for communicating with various computing devices, such as by communicating data, content, information, and/or similar terms used herein interchangeably that can be transmitted, received, operated on, processed, displayed, stored, and/or the like.
  • Such communication can be executed using a wired data transmission protocol, such as fiber distributed data interface (FDDI), digital subscriber line (DSL), Ethernet, asynchronous transfer mode (ATM), frame relay, data over cable service interface specification (DOCSIS), or any other wired transmission protocol.
  • FDDI fiber distributed data interface
  • DSL digital subscriber line
  • Ethernet asynchronous transfer mode
  • ATM asynchronous transfer mode
  • frame relay frame relay
  • DOCSIS data over cable service interface specification
  • the MES server device 122 can be configured to communicate via wireless external communication networks using any of a variety of protocols, such as general packet radio service (GPRS), Universal Mobile Telecommunications System (UMTS), Code Division Multiple Access 2000 (CDMA2000), CDMA2000 IX (lxRTT), Wideband Code Division Multiple Access (WCDMA), Global System for Mobile Communications (GSM), Enhanced Data rates for GSM Evolution (EDGE), Time Division- Synchronous Code Division Multiple Access (TD-SCDMA), Long Term Evolution (LTE), Evolved Universal Terrestrial Radio Access Network (E-UTRAN), Evolution-Data Optimized (EVDO), High Speed Packet Access (HSPA), High-Speed Downlink Packet Access (HSDPA), IEEE 802.11 (Wi-Fi), Wi-Fi Direct, 802.16 (WiMAX), ultra-wideband (UWB), infrared (IR) protocols, near field communication (NFC) protocols, Wibree, Bluetooth protocols, wireless universal serial bus (USB) protocols, and/or any other wireless protocol.
  • FIG. 6 is a data flow diagram of an example process 600 for batch event processing with respect to a manufacturing process.
  • the batch event processing computing device 106 can utilize batch event data objects provided by batch event data source computing devices 102 in order to perform batch event processing for manufacturing processes that are being coordinated and executed using the DCS 111 and/or MES 112.
  • a batch event data object is a data object that includes one or more event fields, where each event field describes recorded contextual information about performance of an event that is a component of performing the manufacturing process.
  • an batch event data object can include an event field that describes creation of a manufacturing batch corresponding to the manufacturing process, an event field that describes beginning of a manufacturing procedure that corresponds to a stage of the manufacturing process, an event field that describes end of the manufacturing procedure noted above, and an event field that describes of end the manufacturing batch noted above.
  • the event fields in the batch event data object are recorded based on a linear temporal order of timestamps associated with recording of the event fields, such as a linear temporal order according to which the earliest-recorded event fields can be at the top of the batch event data object.
  • Examples of contextual information for an event field that are described by an batch event data object include an event time of an event corresponding to the event field, an execution identifier of the event corresponding to the event field, the batch identifier of the event corresponding to the event field, the hierarchical event identifier of the event corresponding to the event field, the event name of the event corresponding to the event field, the event value of the event corresponding to the event field, the area designation of the event corresponding to the event field, the unit designation of the event corresponding to the event field, and/or the like.
  • the set of contextual information item types described by each event field are described in accordance with a batch processing protocol, such as the Open Batch Protocol.
  • each event field in the batch event data object 700 (e.g., such as the event fields 711-713) is associated with an event time 701, an execution identifier 702, a batch identifier 703, a hierarchical event identifier 704, an event name 705, an event type 706.
  • the event field 711 is associated with the event time 701 “2019-10-22 15:28:31.000”, the execution identifier 702 “15925313126808765275”, the batch identifier 703 “DD0213E9B44D435B”, a hierarchical event identifier 704 “ ⁇ 10/22/2019 15:28:3 l ⁇ ebm ⁇ 15925313126808765275 ⁇ 04Y_4_YOGURT:1”, the event name 705 “Batch Creation”, and the event type 706 “Create”.
  • the event field 712 is associated with the event time 701 “2019-10-22 15:28:31.000”, the execution identifier 702 “15925313126808765275”, the batch identifier 703 “04Y_4_YOGURT”, a hierarchical event identifier 704 “ ⁇ 10/22/2019 15:28:31 ⁇ ebm ⁇ 15925313126808765275 ⁇ 04Y_4_YOGURT:l”, the event name 705 “Procedure Started”, and the event type 706 “Start”.
  • the event field 713 is associated with the event time 701 “2019-10-22 15:29:18.000”, the execution identifier 702 “15925313126808765275”, the batch identifier 703 “$dd0213e9b44d435b-000e”, a hierarchical event identifier 704 ⁇ 10/22/2019
  • the event time 701 of an event field describes a time associated with occurrence and/or with recording of the occurrence of the event corresponding to the event field.
  • the event time 701 of the event field 711 indicates that the event corresponding to the event field 711 has begun at 31 st second of the time 15:28 on October 22, 2019.
  • the event time 701 of the event field 712 indicates that the event corresponding to the event field 712 has begun at 31 st second of the time 15:28 on October 22, 2019.
  • the event time 701 of the event field 712 indicates that the event corresponding to the event field 713 has begun at 18 th second of the time 15:29 on October 22, 2019.
  • the execution identifier 702 of an event field uniquely identifies a manufacturing process associated with the event field. Accordingly, the execution identifier 702 of various event fields that collectively relate to a common manufacturing process can have a common event field. For example, as depicted in FIG. 7, each of the event fields 711-713 is associated with the common execution identifier 702 “15925313126808765275”. Indeed, all of the event fields depicted in FIG. 7 have the common execution identifier 702 “15925313126808765275”. [0078] The batch identifier 703 of an event field uniquely identifies a manufacturing process stage associated with the event field.
  • event fields that are associated with the same hierarchical level of events are associated with a common batch identifier 703.
  • the event field 711 which is associated with a most-superior hierarchical level of events is associated with the batch identifier 703 “DD0213E9B44D435B.
  • the event field 712 which is associated with a second-most-superior hierarchical level of events is associated with the batch identifier 703 “04Y 4 YOGURT”.
  • the event field 713 which is associated with a third-most-superior hierarchical level of events is associated with the batch identifier 703 “$dd0213e9b44d435b-000e”.
  • the hierarchical event identifier 704 of an event field describes the event time 701 of the event field, the execution identifier 702 of the event field, a non-hierarchical event identifier of the event field, and each non-hierarchical event identifier of a parent of the event field (whether or not the parent event field is an immediate parent or an indirect event field) in a hierarchical manner.
  • the hierarchical event identifier 704 of the event field 711 describes that the event field 711 is associated with the event time 701 “10/22/2019 15:28:31”, is associated with the execution identifier 702 “15925313126808765275”, and is associated with the non-hierarchical event identifier “04Y 4 YOGURT”.
  • the hierarchical event identifier 704 of the event field 712 describes that the event field 711 is associated with the event time 701 “10/22/2019 15:28:31”, is associated with the execution identifier 702 “15925313126808765275”, and is associated with Othe non-hierarchical event identifier “04Y 4 YOGURT”.
  • the hierarchical event identifier 704 of the event field 713 describes that the event field 711 is associated with the event time 701 “15:29:18.000”, is associated with the execution identifier 702 “15925313126808765275”, is associated with the non-hierarchical event identifier “$dd0213e9b44d435b-000e,” and is an immediate child of the event fields related to the manufacturing processing stage “04Y 4 YOGURT”.
  • the event name 705 of an event field describes a textual identifier of the event associated with the event field.
  • the event field 711 is associated with the event name 705 “Batch Creation” which describes that the event field 711 relates to creating a manufacturing processing batch.
  • the event field 712 is associated with the event name 705 “Procedure Started” which describes that the event field 712 relates to starting a manufacturing process within the manufacturing processing batch (e.g., starting a process of milk pasteurization as part of a milk pasteurization batch).
  • a manufacturing process within the manufacturing processing batch e.g., starting a process of milk pasteurization as part of a milk pasteurization batch.
  • the event field 713 is associated with the event name 705 “Procedure Unit Started” which describes that the event field 713 relates to performing a manufacturing process for a unit of product within the manufacturing processing batch (e.g., starting a process of milk pasteurization for a unit of milk as part of a milk pasteurization batch).
  • the event type 706 of an event field describes a cross-hierarchical-level description of the event field that groups similar events across hierarchical levels. For example, despite being performed at the hierarchically distinct procedure level and unit procedure level respectively, the event field 712 and the event field 713 have both the event type 706 “Start”, as they both relate to starting actions related to their respective hierarchical levels. As another example, as depicted in FIG. 7, the event field 711 which relates to batch creation is associated with the event type 706 “Create”. In some embodiments, the batch event processing computing device 106 can be configured to utilize configuration rules to recognize that the event fields having the event type 706 “Create” are start-type event fields similar to the event fields having the event type 706 “Start”.
  • At least some of the event fields described in an batch event data object have a hierarchical structure to them, such that a first set of hierarchically inferior event fields are performed as part of a second set of hierarchically superior event fields.
  • This hierarchical structure can indicate to the batch event processing computing device 106 that a hierarchically superior manufacturing stage cannot end before a hierarchically inferior manufacturing stage, and that a hierarchically inferior manufacturing stage must end before a hierarchically superior manufacturing stage.
  • the hierarchical structure of event fields can be described by an event hierarchy data object, such as the event hierarchy data object 800 of FIG.
  • a “Batch Created” event field 801 (e.g., the event field 711 in the batch event data object 700 of FIG. 7) is hierarchically superior to a “Procedure Started” event field 802 (e.g., the event field 712 in the batch event data object 700 of FIG. 7), while a “Procedure Started” event field 802 (e.g., the event field 712 in the batch event data object 700 of FIG. 7) is hierarchically superior to a “Unit Procedure Started” event field 803 (e.g., the event field 713 in the batch event data object 700 of FIG.
  • a “Unit Procedure Started” event field 803 (e.g., the event field 713 in the batch event data object 700 of FIG. 7) is hierarchically superior to a “Unit Operation Started” event field 804, and a “Unit Operation Started” event field 804 is hierarchically superior to a “Phase” event field.
  • the process 600 continues when a data normalization engine 602 of the batch event processing computing device 106 updates each event field of the batch event data object by converting an existing lexical format of the event field to an expected lexical format based on one or more lexical format conversion rules.
  • the existing lexical format of an batch event data object is a data object that describes: (i) the textual identifier for each contextual information field described by the batch event data object (i.e., the existing schema of the batch event data object), and (ii) for each enumerated contextual information field of the contextual information field described by the batch event data object, the textual identifier for each contextual information value in the range of contextual information values for the enumerated contextual information field.
  • the existing lexical format of the batch event data object 700 of FIG. 7 can describe, among other things: (i) that the batch event data object 700 describes the event type 706 of an event field using an EventType contextual information field, and (ii) that possible values for the EventType contextual information field within the batch event data object 700 include “Header”, “Create”, “Start”, “End”, “Complete”, “Recipe”, and “Report”.
  • the existing lexical format of a second batch event data object can describe, among other things, (i) that the second batch event data object describes the event type 706 of an event field using an Type of Event contextual information field, and (ii) that possible values for the Type of Event field within the second batch event data object include “Header”, “Create”, “Begin”, “Terminate”, “Fully Completed”, “Recipe Extracted”, and “Report Generated”.
  • the expected lexical format of is a data object that describes: (i) the textual identifier expected by the batch event processing computing device 106 for each contextual information field described by the batch event data object (i.e., the expected schema of the batch event data object), and (ii) for each enumerated contextual information field of the contextual information field described by the batch event data object, the textual identifier expected by the batch event processing computing device 106 for each contextual information value in the range of contextual information values for the enumerated contextual information field.
  • the expected format an batch event data object can describe, among other things: (i) that the batch event data object should describe the event type 706 of an event field using an EventType contextual information field, and (ii) that possible values for the EventType contextual information field within the batch event data object should include “Header”, “Create”, “Start”, “End”, “Complete”, “Recipe”, and “Report”.
  • the expected lexical format can describe, among other things, (i) that the batch event data object should describe the event type 706 of an event field using an Type of Event contextual information field, and (ii) that possible values for the Type of Event field within the second batch event data object should include “Header”, “Create”, “Begin”, “Terminate”, “Fully Completed”, “Recipe Extracted”, and “Report Generated”.
  • the lexical format conversion rules refer to a data object that describes one or more rules for converting a corresponding existing lexical format of a batch event data object to an expected lexical format of the batch event processing computing device 106.
  • the data object describing the lexical format conversion rules can be a lexical format conversion rule data object having a structured file format, such as an Extensible Markup Language (XML) file format and/or a JavaScript Object Notation (JSON) file format.
  • XML Extensible Markup Language
  • JSON JavaScript Object Notation
  • the lexical format conversion rule data object 900 describes, in the data object segment 901, conversion rules for contextual information field names.
  • the “EventTime” contextual information field name for the event time 701 contextual information field within a batch event data object having a corresponding existing lexical format should be maintained as such.
  • the “EU” contextual information field name within a batch event data object having a corresponding existing lexical format should be converted to an “UOM” contextual information field name.
  • the lexical format conversion rule data object 900 describes, in the data object segment 902, conversion rules for the range of values of the EventType contextual information field name. For example, as instructed by the data object segment 902, the “Header” value for an EventType contextual information field within a batch event data object having a corresponding existing lexical format should be maintained as such. Indeed, the exemplary the data object segment 902 does not require any conversion of values corresponding to the EventType contextual information field between the corresponding existing lexical format and the corresponding expected lexical format. However, a person of ordinary skill in the relevant technology will recognize that, in some embodiments, lexical format conversion rule data objects can define one or more recommended value conversions for potential values of an EventType contextual information field.
  • the lexical format conversion rule data object 900 describes, in the data object segment 903, conversion rules for the range of values of the EventName contextual information field name. For example, as instructed by the data object segment 903, the “Material” value for an EventType contextual information field within a batch event data object having a corresponding existing lexical format should be converted to “MATERIAL”. As another example, as further instructed by the data object segment 903, the “Batch Creation” value for an EventType contextual information field within a batch event data object having a corresponding existing lexical format should be converted to “BatchCreation.”
  • the “Unit Procedure Started” value for an EventType contextual information field within a batch event data object having a corresponding existing lexical format should be converted to “UnitPrcoedureStarted”.
  • the “ACTUAL AMOUNT” value for an EventType contextual information field within a batch event data object having a corresponding existing lexical format should be converted to “Actual Amount” .
  • the process 600 continues when an event processing engine 603 of the batch event processing computing device 106 processes the updated batch event data object to generate an event frame stack data object.
  • the event frame stack data object is a data object that includes a set of event frames, where the set of event frames correspond to event fields within the batch event data object that correspond to beginning or end of hierarchical levels of the event fields within the batch event data object, and where the set of event frames are stacked based on are stacked based on the hierarchical structure of the event fields within the batch event data object.
  • the event frame stack data object 1000 includes, at the bottom of the stack, a BatchCreated event frame 1001, which is covered on top by a ProcedureStarted event frame 1002, which is covered on top by a UnitProcedureStarted event frame 1003, which is covered on top by a UnitOperationStarted event frame 1004, which is covered on top by a PhaseStarted event frame 1005, which is covered on top by a PhaseEnded event frame 1006, which is covered on top by UnitOperationEnded event frame 1007, which is covered on top by a UnitProcedureEnded event frame 1008, which is covered on top by a UnitPorcedureEnded event frame 1009, which is covered on top by a BatchCompleted event frame 1010.
  • hierarchically inferior event frames begin after and end before hierarchically superior event frames.
  • the event processing engine 603 generates the event frame stack data object in accordance with the processes depicted in FIGS. 11-12.
  • FIG. 11 is a flowchart diagram of an example process for processing a start-type event field within a batch event data object in relation to an event frame stack data object. The process depicted in FIG. 12 starts at operation 1101 when the event processing engine 603 identifies a start-type event field. Examples of start-type event fields include create-type event fields, begin-type event fields, start- type event fields, and/or the like.
  • the event processing engine 603 generates a start event frame that corresponds to the start-type event field.
  • the event processing engine 603 determines a start time of the start event frame based on the event time field of the event record having a start-type event (e.g., a create field, a begin field, a start field, etc.), determines a batch name of the start event frame based on the event value of start-type event field, determines a non-hierarchical frame identifier of the start event frame based on a most-hierarchically-inferior portion of the hierarchical event identifier of the start-type event field, determines a non-hierarchical parent frame identifier of the start event frame based on a second-most-hierarchically-inferior portion of the hierarchical event identifier of the start-type event field, and generates the start event frame to include the start time,
  • a start-type event e.g., a create field, a begin field, a start
  • the event processing engine 603 can determine: (i) based on the event time 701 of the start-type event field 711, a start time of “15:28:31.000”; (ii) based on the last Vseparated segment of the hierarchical event identifier 704 of the start-type event field 711, the non-hierarchical frame identifier of “04Y_4_YOGURT:1”; and (iii) a missing non-hierarchical parent frame identifier.
  • the event processing engine 603 can determine: (i) based on the event time 701 of the start-type event field 713, a start time of “15:29:18.000”; (ii) based on the last Vseparated segment of the hierarchical event identifier 704 of the start-type event field 713; (iii) the non-hierarchical frame identifier of “04YM_3_MAKING2@$dd0213e9b44d435b-000e”; and (iv) and the non-hierarchical parent frame identifier of “15:29:18.000:1”.
  • the event processing engine 603 adds the start event frame to the event frame stack data object as the top event frame for the event frame stack data object.
  • the top event frame is a value described by the event frame stack data object that describes the last event frame added to the event frame stack data object.
  • the top event frame describes the event frame for an event field that is associated with the most hierarchically-inferior event field of all the event fields that have been analyzed and whose corresponding event frames have not been closed, where an event frame is deemed closed if: (i) t is an end event frame whose corresponding start event frame is present in the event frame stack; or (ii) it is an end event frame whose virtual start event frame was added to stack based on attribute events like “Recipe”, “Report”, “Actual Amount”, etc.
  • FIG. 12 is a flowchart diagram of an example process for processing an end-type event field within an batch event data object in relation to an event frame stack data object.
  • the process depicted in FIG. 12 starts at operation 1201 when the event processing engine 603 identifies an end-type event field.
  • Examples of end-type event fields include end-type event fields, terminate-type event fields, complete-type event fields, and/or the like.
  • the event processing engine 603 determines whether the event value of a top event field of the event frame stack data object corresponds to the event value of the end-type event field.
  • the top event frame is a value described by the event frame stack data object that describes the last event frame added to the event frame stack data object.
  • the event processing engine 603 peaks the stack to ensure that the event frames corresponding to all children event frames of an end-type event field have been closed before adding the end event frame for the end-type event field to the event frame stack data object as the top event frame for the event frame stack data obj ect.
  • a temporary event frame stack data object is a data object that includes (e.g., in a hierarchical order of event fields that correspond to the temporarily-stacked event frames) all event frames that have been generated but not added to the event frame stack data object because they correspond to event fields whose children event fields relate to event frames that have not been closed in the event frame stack data object.
  • the event processing engine 603 moves the top event field of the event frame stack data object and deletes the noted top event field from the event frame stack data object.
  • FIG. 13 An operational example of performing operation 1203 is depicted in FIG. 13.
  • the event frame stack data object 1301 includes a UnitOperationStarted event frame 1311 but no UnionOperationEnded event frame. Therefore, when a UnionProcedureEnded event frame 1312 is received, the event processing engine 603 adds a UnionProcedureEnded event frame 1312 to the temporary event frame stack data object 1302.
  • the event processing engine 603 In response to determining that the event value of the top event field of the event frame stack data object corresponds to the event value of the end-type event field, the event processing engine 603 (at operation 1204) adds an end event frame that corresponds to the end- type event field to the event frame stack data object as the top event frame for the event frame stack data object and (at operation 1205) transfers the temporary event frame stack data object to the event frame stack data object. In some embodiments, to generate the event frame that corresponds to the end-type event field, the event processing engine 603 determines an end time of the end event frame based on an event time of the incoming start-type event field, and generates the end event frame based on the end time.
  • the event processing engine 603 determines an end time of the end event frame based on an event time of the end-type event field, determines a batch name of the end event frame based on the event value of end-type event field, determines a non-hierarchical frame identifier of the end event frame based on a most- hierarchically-inferior portion of the hierarchical event identifier of the end-type event field, determines a non-hierarchical parent frame identifier of the end event frame based on a second- most-hierarchically-inferior portion of the hierarchical event identifier of the end-type event field, and generates the end event frame to include the end time, the batch name, the non- hierarchical frame identifier, and the non-hierarchical parent frame identifier.
  • the process 600 when a transmitter engine 604 of the batch event processing computing device 106 generates a manufacturing process monitoring data object based on the event frame stack data object and transmits the manufacturing process monitoring data object to the MES server device 122.
  • the manufacturing process monitoring data object is a tree data object, where each node of the tree data object corresponds to an event frame of one or more event frames of the event frame stack data object, and further where each edge of the tree data object corresponds to a parent relationship between the one or more event frames.
  • the MES server device 122 is configured to set configuration parameters for the manufacturing process based on the manufacturing process monitoring data object.
  • setting the configuration parameters for the manufacturing process is configured to cause the DCS server device 121 to modify a recipe for the manufacturing process.
  • setting the configuration parameters for the manufacturing process is configured to cause the DCS server device 121 to display a user interface that shows an operational status of performing the manufacturing process.
  • setting the configuration parameters for the manufacturing process is configured to cause the DCS server device 121 to generate one or more anomalous activity notifications and/or generate one or more anomalous activity operations.
  • setting the configuration parameters for the manufacturing process is configured to cause the DCS server device 121 to perform one or more operational load balancing actions.

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  • Engineering & Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
  • Manufacturing & Machinery (AREA)
  • Quality & Reliability (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Debugging And Monitoring (AREA)

Abstract

Selon la présente invention, il existe un besoin d'un traitement d'événement de lot de fabrication plus efficace et plus efficient. Ce besoin peut être adressé, par exemple, à des solutions pour effectuer/exécuter un traitement d'événement de lot de fabrication à l'aide d'objets de données d'empilement de trames d'événement. Dans un exemple, un procédé consiste à identifier un premier objet de données identifiant un ou plusieurs champs d'événements associés à une unité de fabrication; à générer un objet de données d'empilement de trames d'événements sur la base du premier objet de données, l'objet de données d'empilement de trames d'événements décrivant un ordonnancement hiérarchique du ou des champs d'événements; à générer des données de configuration de fabrication sur la base de l'objet de données d'empilement de trames d'événement; et à transmettre les données de configuration de fabrication à un serveur de fabrication.
PCT/US2021/023472 2020-04-01 2021-03-22 Procédé optimal de traitement d'événements de fabrication par lots ayant une complexité de calcul linéaire WO2021202145A1 (fr)

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1998036335A2 (fr) * 1997-02-14 1998-08-20 Fisher-Rosemount Systems, Inc. Systeme de gestion de processus industriels utilisant une strategie de gestion a hierarchie en couches repartie dans des dispositifs de commande multiples
WO2009135224A1 (fr) * 2008-05-02 2009-11-05 Invensys Systems, Inc. Système destiné à maintenir un accès unifié à des informations scada et de système d'exécution de la fabrication (mes)
US20160132043A1 (en) * 2014-11-07 2016-05-12 Honeywell International Inc. Method and apparatus for retrieving time-based event data into unified activity hierarchy across process clusters

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1998036335A2 (fr) * 1997-02-14 1998-08-20 Fisher-Rosemount Systems, Inc. Systeme de gestion de processus industriels utilisant une strategie de gestion a hierarchie en couches repartie dans des dispositifs de commande multiples
WO2009135224A1 (fr) * 2008-05-02 2009-11-05 Invensys Systems, Inc. Système destiné à maintenir un accès unifié à des informations scada et de système d'exécution de la fabrication (mes)
US20160132043A1 (en) * 2014-11-07 2016-05-12 Honeywell International Inc. Method and apparatus for retrieving time-based event data into unified activity hierarchy across process clusters

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