WO2021225575A1 - Création de profil de dispositif optimal - Google Patents

Création de profil de dispositif optimal Download PDF

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Publication number
WO2021225575A1
WO2021225575A1 PCT/US2020/031328 US2020031328W WO2021225575A1 WO 2021225575 A1 WO2021225575 A1 WO 2021225575A1 US 2020031328 W US2020031328 W US 2020031328W WO 2021225575 A1 WO2021225575 A1 WO 2021225575A1
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WIPO (PCT)
Prior art keywords
print
print job
user
optimal
metrics
Prior art date
Application number
PCT/US2020/031328
Other languages
English (en)
Inventor
Frederico Souza GERMANO BETTING
Pedro FURLANETTO
Ricardo RIBANI
Original Assignee
Hewlett-Packard Development Company, L.P.
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.)
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Publication date
Application filed by Hewlett-Packard Development Company, L.P. filed Critical Hewlett-Packard Development Company, L.P.
Priority to PCT/US2020/031328 priority Critical patent/WO2021225575A1/fr
Publication of WO2021225575A1 publication Critical patent/WO2021225575A1/fr

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/12—Digital output to print unit, e.g. line printer, chain printer
    • G06F3/1201—Dedicated interfaces to print systems
    • G06F3/1223—Dedicated interfaces to print systems specifically adapted to use a particular technique
    • G06F3/1237—Print job management
    • G06F3/126—Job scheduling, e.g. queuing, determine appropriate device
    • G06F3/1262—Job scheduling, e.g. queuing, determine appropriate device by grouping or ganging jobs
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/12—Digital output to print unit, e.g. line printer, chain printer
    • G06F3/1201—Dedicated interfaces to print systems
    • G06F3/1202—Dedicated interfaces to print systems specifically adapted to achieve a particular effect
    • G06F3/1211—Improving printing performance
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/12—Digital output to print unit, e.g. line printer, chain printer
    • G06F3/1201—Dedicated interfaces to print systems
    • G06F3/1278—Dedicated interfaces to print systems specifically adapted to adopt a particular infrastructure
    • G06F3/1285—Remote printer device, e.g. being remote from client or server
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
    • H04N1/00832—Recording use, e.g. counting number of pages copied
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
    • H04N1/23—Reproducing arrangements
    • H04N1/2307—Circuits or arrangements for the control thereof, e.g. using a programmed control device, according to a measured quantity
    • H04N1/2361—Selecting a particular reproducing device from amongst a plurality of devices, e.g. high or low resolution devices
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/12—Digital output to print unit, e.g. line printer, chain printer
    • G06F3/1201—Dedicated interfaces to print systems
    • G06F3/1202—Dedicated interfaces to print systems specifically adapted to achieve a particular effect
    • G06F3/1218—Reducing or saving of used resources, e.g. avoiding waste of consumables or improving usage of hardware resources
    • G06F3/1219—Reducing or saving of used resources, e.g. avoiding waste of consumables or improving usage of hardware resources with regard to consumables, e.g. ink, toner, paper

Definitions

  • Multi-function devices often combine different components such as a printer, scanner, and copier into a single device. Such devices frequently receive refills of consumables, such as print substances (e.g., ink, toner, and/or additive materials) and/or media (e.g., paper, vinyl, and/or other print substrates).
  • print substances e.g., ink, toner, and/or additive materials
  • media e.g., paper, vinyl, and/or other print substrates
  • FIG. 1 is a block diagram of an example computing device for providing optimal device profile creation.
  • FIG. 2 is a flowchart of an example method for providing optimal device profile creation.
  • FIG. 3 is a block diagram of an example system for providing optimal device profile creation.
  • MFPs multi-function-print devices
  • the scanning portion of an MFP may comprise an optical assembly located within a sealed enclosure.
  • the sealed enclosure may have a scan window through which the optical assembly can scan a document, which may be placed on a flatbed and/or delivered by a sheet feeder mechanism.
  • a device such as a printing device, that offers a suboptimal set of capabilities.
  • Such sub-optimal devices may not have necessary features, such as photograph quality color, connectivity, finishing options (e.g., stapling, binding, duplexing, etc.), and/or job type support (e.g., scanning, faxing, emailing, copying, etc.).
  • sub-optimal devices may offer more features than a user needs, resulting in a higher cost to print, own, and/or maintain the device.
  • an optimal device profile may be created.
  • Such a device profile may identify most-used features, such a job types and/or quality, as well as take account of outlying metrics to create an optimal device profile for the user(s).
  • An optimal device profile may also account for other devices accessible to a user(s), including third party services.
  • a user who regularly prints short office documents in black & white may find a printing device capable of photo-quality color to be cost-inefficient, even if they do occasionally print a picture.
  • the user may be recommended to utilize a lower-cost print device model for the majority of their printing and recommended to use another, higher-cost device only for specific jobs that need the additional features provided by the higher-cost device.
  • the user may be recommended to use a third party print service, such as a web-based photo ordering service and/or a print shop in order to provide services for which the regular print device is not as well suited,
  • users' profiles of past job metrics may be used to create an optimal device profile in order to recommend which of a set of available print device models best meets their needs at time of purchase- For example, a user who has already has and/or has access to a photo printer, but who regularly prints black and white text documents, may be provided with a recommendation of a mono laser printer as the optimal device profile,
  • Optimal characteristics may differ from user to user and may be based on analysis of the print job metrics associated with the user and/or specific inputs solicited from the user. For example, a user may be asked whether speed or cost is more important to their decision making, and the answer may be used to weigh criteria of available print models when creating an optimal device profile for that user. In some situations, however, a users behavior, as demonstrated by their print job metrics, may indicate that their actual preference may differ from their response to such a question. For example, a user may respond to such a question that cost efficiency is more important, but may also regularly override a shared print queue to prioritize the speed with which their own jobs are printed relative to other users, thus indicating that speed is of relatively high importance.
  • Deep learning is a specialized area of machine learning and/or artificial intelligence that may be used in different areas, such as computer vision, speech recognition, behavior prediction, text translation, etc.
  • a deep learning model refers to or includes a trained machine learning model that has undergone a training process and may make inferences from received data.
  • Example deep learning models include neural networks, such as convolution neural networks and deep neural networks. Such a model may be trained, for example, on a training corpus of other users’ job metrics, device profiles used by those users, and satisfaction surveys associated with those users.
  • a non-transitory machine-readable medium may store instructions executable by a processor to log a plurality of print job metrics for each of a plurality of print jobs, create an optimal device profile according to the plurality of print job metrics, identify an available print device model according to the optimal device profile, and provide a recommendation of the available print device model to a user.
  • methods for providing optimal device profile creation may comprise fogging a plurality of print job metrics for each of a plurality of print jobs, wherein each of the plurality of print job metrics comprise at least one job setting and at least one device feature used, creating an optimal device profile according to the plurality of print job metrics, identifying an available print device model according to the optimal device profile, and providing a recommendation of the available print device model to a user.
  • systems for providing optimal device profile creation may comprise a log engine to log a plurality of print job metrics for each of a plurality of print jobs associated with a user, a profile engine to create an optimal device profile according to the plurality of print job metrics and identify an available print device model according to the optimal device profile, and a recommendation engine to provide a recommendation of the available print device model to a user.
  • FIG. 1 is a block diagram of an example computing device 110 for providing optimal device profile creation.
  • Computing device 110 may comprise a processor 112 and a non-transitory, machine-readable storage medium 114, Storage medium 114 may comprise a plurality of processor-executable instructions, such as log print job metric instructions 120, create optimal device profile instructions 125, identify available print model instructions 130, and provide recommendation instructions 135.
  • instructions 120, 125, 130, 135 may be associated with a single computing device 110 and/or may be communicatively coupled among different computing devices such as via a direct connection, bus, or network.
  • Processor 112 may comprise a central processing unit (CPU), a semiconductor-based microprocessor, a programmable component such as a complex programmable logic device (CPLD) and/or field-programmable gate array (FPGA), or any other hardware device suitable for retrieval and execution of instructions stored in machine-readable storage medium 114,
  • processor 112 may fetch, decode, and execute instructions 120, 125, 130, 135,
  • Executable instructions 120, 125, 130, 135 may comprise logic stored in any portion and/or component of machine-readable storage medium 114 and executable by processor 112.
  • the machine-readable storage medium 114 may comprise both volatile and/or nonvolatile memory and data storage components. Volatile components are those that do not retain data values upon toss of power. Nonvolatile components are those that retain data upon a loss of power.
  • the machine-readable storage medium 114 may comprise, for example, random access memory (RAM), read-only memory (ROM), hard disk drives, solid-state drives, USB flash drives, memory cards accessed via a memory card reader, floppy disks accessed via an associated floppy disk drive, optical discs accessed via an optical disc drive, magnetic tapes accessed via an appropriate tape drive, and/or other memory components, and/or a combination of any two and/or more of these memory components.
  • the RAM may comprise, for example, static random access memory (SRAM), dynamic random access memory (DRAM), and/or magnetic random access memory ( MRAM) and other such devices.
  • the ROM may comprise, for example, a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), and/or other like memory device.
  • PROM programmable read-only memory
  • EPROM erasable programmable read-only memory
  • EEPROM electrically erasable programmable read-only memory
  • Log print job metric instructions 120 may log a plurality of print job metrics for each of a plurality of print jobs.
  • Print job metrics may comprise, for example, details about the print jobs such as a print job setting, a print job size, a print job type, a print device component used, and a print device capability used.
  • Print job settings for example, may comprise color settings, resolution settings, finishing settings, page layouts, paper sizes, and the like.
  • print job types may comprise any operation capable of being performed by a print device, such as scanning, copying, faxing, transmitting, error correction, image enhancement, publishing and finishing operations, etc.
  • device components may comprise a scanner assembly, media handling components such as offset output trays, paper selections, and duplexing, facsimile components, and/or network components such as wireless and/or wired networks, Bluetooth, radio frequency, cellular, etc.
  • Device capabilities may include image manipulation and/or enhancement, color and/or resolution quality , speed, usable paper sizes, etc.
  • Print job metrics may, for example, be anonymized to remove actual data (e.g., the actual text, images, and/or other content of the print job) to protect user privacy.
  • the plurality of print jobs may be completed at a single print device and/or at a plurality of print devices.
  • the metrics logged may be associated with print jobs completed at multiple print devices associated with a user and/or plurality of users, such as print jobs completed at different devices within a fleet of printers owned by a person and/or organization.
  • the plurality of print job metrics may be stored on the single print device and/or on a network device.
  • the print job metrics may be stored in an on-board memory of the single print device.
  • the user may comprise an originating user for the plurality of print jobs.
  • the plurality of print jobs may be associated with a plurality of users.
  • Print job metrics may, for example, be anonymously aggregated across multiple users and multiple devices, such as when an optimal print device profile for a group of users is desired to be created,
  • Create optimal device profile instructions 125 may create an optimal device profile according to the plurality of print job metrics. Various factors learned from the logged print job metrics may be synthesized to create the optimal device profile, such as in a deep learning model. The model may take into account frequency of use of the device(s) and various features. The optimal device profile may offer a balance between features used, cost, and efficiency based on an analysis of the needs of the user(s).
  • a user who prints 90% of the time in duplexed black and white may receive an optimal device profile comprising a monochrome print device with a duplexer when an available color model may add an unacceptable, to the user(s), cost.
  • Identify available print model instructions 130 may identify an available print device model according to the optimal device profile.
  • the optimal device profile may comprise an alignment between a first plurality of print device features associated with the available print device model and a second plurality of print device features as logged in the plurality of print job metrics.
  • a plurality of available print models may comprise several lines such as home/small office, large office, and enterprise that are categorized based on their capacity for printing for a certain range and/or number of users that will use the print device.
  • device 110 may maintain and update a list of device models, their capabilities, and, in some implementations, a ranking score for each capability.
  • the capability lists may be compared to the optimal device profile to find an alignment where the optimal device profile matches as many of the capabilities of an available device model as possible.
  • the characteristics may comprise a ranked list in order of priority.
  • an optimal device profile may comprise characteristics such as:
  • Such an optimal device profile may, for example, be matched to a small office line, color laser-based multi-function printer with WiFi networking.
  • Such an available device may not comprise the low priority fax capability of the optimal device profile if, for example, the cost difference between a model with fax and without exceeds a configurable cost difference threshold.
  • Provide recommendation instructions 135 may provide a recommendation of the available print device model to a user, Once the available print device model has been identified, device 110 may provide that model as a recommendation to a user, for example, at a point of purchase to suggest which model the user should buy. For example, a service may be run on an e-commerce site to direct the user (e.g., by displaying or otherwise sending a link) to the recommended model's page on that site.
  • FIG. 2 is a flowchart of an example method 200 for optimal device profile creation. Although execution of method 200 is described below with reference to computing device 110, other suitable components for execution of method 200 may be used,
  • Method 200 may begin at stage 205 and advance to stage 210 where device 110 may log a plurality of print job metrics for each of a plurality of print jobs, wherein each of the plurality of print job metrics comprise at least one job setting and at least one device feature used.
  • device 110 may execute log print job metric instructions 120 to log a plurality of print job metrics for each of a plurality of print jobs.
  • Print job metrics may comprise, for example, details about the print jobs such as a print job seting, a print job size, a print job type, a print device component used, and a print device capability used.
  • Print job settings for example, may comprise color settings, resolution settings, finishing settings, page layouts, paper sizes, and the like.
  • print job types may comprise any operation capable of being performed by a print device, such as scanning, copying, faxing, transmitting, error correction, Image enhancement, publishing and finishing operations, etc.
  • device components may comprise a scanner assembly, media handling components such as offset output trays, paper selections, and duplexing, facsimile components, and/or network components such as wireless and/or wired networks, Bluetooth, radio frequency, cellular, etc.
  • Device capabilities may include image manipulation and/or enhancement, color and/or resolution quality, speed, usable paper sizes, etc.
  • Print job metrics may, for example, be anonymized to remove actual data (e.g. the actual text, images, and/or other content of the print job) to protect user privacy.
  • the plurality of print jobs may be completed at a single print device and/or at a plurality of print devices.
  • the metrics logged may be associated with print jobs completed at multiple print devices associated with a user and/or plurality of users, such as print jobs completed at different devices within a fleet of printers owned by a person and/or organization.
  • the plurality of print job metrics may be stored on the single print device and/or on a network device.
  • the print job metrics may be stored in an on-board memory of the single print device.
  • the user may comprise an originating user for the plurality of print jobs.
  • the plurality of print jobs may be associated with a plurality of users.
  • Print job metrics may, for example, be anonymously aggregated across multiple users and multiple devices, such as when an optimal print device profile for a group of users is desired to be created.
  • Method 200 may then advance to stage 220 where computing device 110 may create an optimal device profile according to the plurality of print job metrics.
  • device 110 may execute create optimal device profile instructions 125 to create an optimal device profile according to the plurality of print job metrics.
  • Various factors learned from the logged print job metrics may be synthesized to create the optimal device profile, such as in a deep learning model.
  • the model may take into account frequency of use of the device(s) and various features.
  • the optimal device profile may offer a balance between features used, cost, and efficiency based on an analysis of the needs of the user(s). For example, a user who prints 90% of the time In duplexed black and white may receive an optimal device profile comprising a monochrome print device with a duplexer when an available color model may add an unacceptable, to the user(s), cost,
  • Method 200 may then advance to stage 230 where computing device 110 may identify an available print device model according to the optimal device profile.
  • device 110 may execute identify available print model instructions 130 to identify an available print device model according to the optimal device profile.
  • the optimal device profile may comprise an alignment between a first plurality of print device features associated with the available print device model and a second plurality of print device features as logged in the plurality of print job metrics.
  • a plurality of available print models may comprise several lines such as home/small office, large office, and enterprise that are categorized based on their capacity for printing for a certain range and/or number of users that will use the print device.
  • different devices may offer different features and/or capabilities, such as finishing options, resolutions, color options, components (e.g., fax, scan, etc.), and/or communications.
  • device 110 may maintain and update a list of device models, their capabilities, and, in some implementations, a ranking score for each capability.
  • the capability lists may be compared to the optimal device profile to find an alignment where the optimal device profile matches as many of the capabilities of an available device model as possible.
  • the characteristics may comprise a ranked list in order of priority.
  • an optimal device profile may comprise characteristics such as:
  • Such an optimal device profile may, for example, be matched to a small office line, color laser-based multi-function printer with WiFi networking.
  • Such an available device may not comprise the tow priority fax capability of the optimal device profile if, for example, the cost difference between a model with fax and without exceeds a configurable cost difference threshold.
  • Method 200 may then advance to stage 240 where computing device 110 may provide a recommendation of the available print device model to a user.
  • device 110 may execute provide recommendation instructions 135 to provide a recommendation of the available print device model to a user.
  • device 110 may provide that model as a recommendation to a user, for example, at a point of purchase to suggest which model the user should buy.
  • a service may be run on an e-commerce site to direct the user (e.g., by displaying or otherwise sending a link) to the recommended model’s page on that site.
  • the recommendation of the available print device model comprises a recommended replacement for the at least one print device owned by the user.
  • Method 200 may then end at stage 250.
  • FIG. 3 is a block diagram of an example apparatus 300 for providing optimal device profile creation.
  • Apparatus 300 may comprise a multi-function printer device 302 comprising a storage medium 310, and a processor 312.
  • Device 302 may comprise and/or be associated with, for example, a general and/or special purpose computer, server, mainframe, desktop, laptop, tablet, smart phone, game console, printer, multi-function device, and/or any other system capable of providing computing capability consistent with providing the implementations described herein.
  • Device 302 may store, in storage medium 310, a log engine 320, a profile engine 325, and a recommendation engine 330.
  • Each of engines 320, 325, 330 may comprise any combination of hardware and programming to implement the functionalities of the respective engine, in examples described herein, such combinations of hardware and programming may be implemented in a number of different ways.
  • the programming for the engines may be processor executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the engines may include a processing resource to execute those instructions
  • the machine-readable storage medium may store instructions that, when executed by the processing resource, implement engines 320, 325, 330.
  • device 302 may comprise the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to apparatus 300 and the processing resource
  • Log engine 320 may log a plu rality of print job metrics for each of a plurality of print jobs associated with a user.
  • log engine 320 may execute log print job metric instructions 120 to log a plurality of print job metrics for each of a plurality of print jobs.
  • Print job metrics may comprise, for example, details about the print jobs such as a print job setting, a print job size, a print job type, a print device component used, and a print device capability used.
  • Print job settings for example, may comprise color settings, resolution settings, finishing settings, page layouts, paper sizes, and the like.
  • print job types may comprise any operation capable of being performed by a print device, such as scanning, copying, faxing, transmitting, error correction, image enhancement, publishing and finishing operations, etc.
  • device components may comprise a scanner assembly, media handling components such as offset output trays, paper selections, and duplexing, facsimile components, and/or network components such as wireless and/or wired networks, Bluetooth, radio frequency, cellular, etc.
  • Device capabilities may include image manipulation and/or enhancement, color and/or resolution quality, speed, usable paper sizes, etc.
  • Print job metrics may, for example, be anonymized to remove actual data (e.g., the actual text, images, and/or other content of the print job) to protect user privacy.
  • the plurality of print jobs may be completed at a single print device and/or at a plurality of print devices.
  • the metrics logged may be associated with print jobs completed at multiple print devices associated with a user and/or plurality of users, such as print jobs completed at different devices within a fleet of printers owned by a person and/or organization.
  • the plurality of print job metrics may be stored on the single print device and/or on a network device.
  • the print job metrics may be stored in an on-board memory of the single print device. In some situations, it may be more efficient to store the print job metrics by uploading them to a server, web service, and/or other network connected application for storage on a different device’s memory.
  • the user may comprise an originating user for the plurality of print jobs
  • the plurality of print jobs may be associated with a plurality of users.
  • Print job metrics may, for example, be anonymously aggregated across multiple users and multiple devices, such as when an optimal print device profile for a group of users is desired to be created.
  • Profile engine 325 may create an optimal device profile according to the plurality of print job metrics and identify an available print device model according to the optimal device profile. For example, profile engine 325 may execute create optimal device profile instructions 125 to create an optimal device profile according to the plurality of print job metrics. Various factors learned from the logged pri nt Job metrics may be synthesized to create the optimal device profile, such as in a deep learning model The model may take into account frequency of use of the device(s) and various features. The optimal device profile may offer a balance between features used, cost, and efficiency based on an analysis of the needs of the user(s). For example, a user who prints 90% of the time in duplexed black and white may receive an optimal device profile comprising a monochrome print device with a duplexer when an available color model may add an unacceptable, to the user(s), cost.
  • Profile engine 325 may further execute identify available print model instructions 130 to identify an available print device model according to the optimal device profile.
  • the optimal device profile may comprise an alignment between a first plurality of print device features associated with the available print device model and a second plurality of print device features as logged in the plurality of print job metrics.
  • a plurality of available print models may comprise several lines such as home/small office, large office, and enterprise that are categorized based on their capacity for printing for a certain range and/or number of users that will use the print device.
  • different devices may offer different features and/or capabilities, such as finishing options, resolutions, color options, components (e.g., fax, scan, etc. ⁇ , and/or communications.
  • device 110 may maintain and update a list of device models, their capabilities, and, in some implementations, a ranking score for each capability.
  • the capability lists may be compared to the optimal device profile to find an alignment where the optimal device profile matches as many of the capabilities of an available device model as possible.
  • the characteristics may comprise a ranked list in order of priority.
  • an optimal device profile may comprise characteristics such as:
  • Such an optimal device profile may, for example, be matched to a small office line, color laser-based multi-function printer with WiFi networking.
  • Such an available device may not comprise the tow priority fax capability of the optimal device profile if, for example, the cost difference between a model with fax and without exceeds a configurable cost difference threshold.
  • Recommendation engine 330 may provide a recommendation of the available print device model to a user.
  • recommendation engine 330 may execute provide recommendation instructions 135 to provide a recommendation of the available print device model to a user.
  • device 110 may provide that model as a recommendation to a user, for example, at a point of purchase to suggest which model the user should buy.
  • a service may be run on an e-commerce site to direct the user (e.g., by displaying or otherwise sending a link) to the recommended model’s page on that site.
  • the optimal device profile may comprise an alignment between a first plurality of print device features associated with the available print device model and a second plurality of print device features as logged in the plurality of print job metrics,

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Abstract

Des exemples selon l'invention se rapportent à la consignation d'une pluralité de mesures de tâche d'impression pour chaque tâche d'une pluralité de tâches d'impression, à la création d'un profil de dispositif optimal en fonction de la pluralité de mesures de tâche d'impression, à l'identification d'un modèle de dispositif d'impression disponible en fonction du profil de dispositif optimal, et à la fourniture d'une recommandation du modèle de dispositif d'impression disponible à un utilisateur.
PCT/US2020/031328 2020-05-04 2020-05-04 Création de profil de dispositif optimal WO2021225575A1 (fr)

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