Information processing device, information processing method, and information processing program

Abstract

This disclosure aims to propose tread specifications or cases predicted from data on the work environment of the work site where the vehicle operates, the work conditions of the vehicle at the work site, and the tires fitted to the vehicle. [Solution] The information processing device includes a processor, which acquires environmental data indicating the environment of a work site where multiple vehicles perform work, vehicle data including the work status of the multiple vehicles at the work site, and tire data relating to the tires mounted on each of the multiple vehicles. Using predictive logic capable of proposing tire tread specifications and cases suitable for at least one specific vehicle among the multiple vehicles, including at least two of gauge, rubber, and pattern, the processor proposes tread specifications or cases suitable for the specific vehicle from the acquired environmental data, vehicle data, and tire data.

Description

Technical Field

[0001] The present disclosure relates to an information processing apparatus, an information processing method, and an information processing program.

Background Art

[0002] Patent Document 1 discloses a method for evaluating tire performance, an evaluation apparatus, and an evaluation program.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] By the way, it is desirable to manufacture tires according to specifications such as the gauge, rubber, and pattern according to the customer's usage situation. However, it is difficult to continuously provide the optimal tires while the customer's usage situation fluctuates, and there is still room for improvement. [[ID=3…… (The text seems to be incomplete here. Please check and provide the full content if needed.)]] Therefore, an object of the present disclosure is to propose a tread part specification or case predicted from the environment of the work site where the vehicle performs work, the work situation of the vehicle at the work site, and the data of the tires mounted on the vehicle.

Means for Solving the Problems

[0006] The information processing device in the first embodiment includes a processor, which acquires environmental data indicating the environment of a work site where multiple vehicles perform work, vehicle data including the work status of the multiple vehicles at the work site, and tire data relating to the tires mounted on each of the multiple vehicles, and uses predictive logic capable of proposing tire tread specifications and cases suitable for the specific vehicle, including at least two of gauge, rubber, and pattern suitable for at least one specific vehicle among the multiple vehicles, to propose tread specifications or cases suitable for the specific vehicle from the acquired environmental data, vehicle data, and tire data.

[0007] In the second embodiment, the information processing device, in the first embodiment, uses the prediction logic to propose specifications for the tread portion suitable for the specific vehicle, and also proposes a case suitable for the specific vehicle from among a plurality of pre-prepared cases.

[0008] In the third embodiment, the information processing device, in the first or second embodiment, the processor proposes a gauge, rubber, and pattern suitable for the specific vehicle as the specifications of the tread portion.

[0009] In the fourth embodiment, the information processing device, in the second or third embodiment, transmits instruction data to a terminal of the first factory located near the work site, instructing the manufacture of a tire suitable for the specific vehicle based on the proposed tread specifications and case.

[0010] In the fifth embodiment of the information processing device, in any of the first to fourth embodiments, the processor updates the prediction logic based on the acquired data if the acquired data satisfies predetermined update conditions.

[0011] In the sixth embodiment, the information processing device, in any of the first to fifth embodiments, estimates the durability margin of a case, which indicates how much load the tire can withstand, based on the acquired environmental data, vehicle data, and tire data, and if the estimated durability margin is below a predetermined threshold, it transmits instruction data to a terminal at a second factory located further away from the work site than the first factory located near the work site where the tires are manufactured, instructing the manufacture of cases that can be used by the multiple vehicles. [Effects of the Invention]

[0012] As explained above, this disclosure makes it possible to propose tread specifications or cases predicted from data on the work environment of the work site where the vehicle is working, the working conditions of the vehicle at the work site, and the tires fitted to the vehicle. [Brief explanation of the drawing]

[0013] [Figure 1] This is a diagram illustrating the schematic configuration of an information processing system. [Figure 2] This is a block diagram showing the hardware configurations for servers, factory terminals, and customer terminals. [Figure 3] This is a block diagram showing the server's storage configuration. [Figure 4] This chart shows the flow of a specific process performed by the server. [Figure 5] This is an example of how the display will appear on the server's display panel. [Figure 6] This is an example of a display shown on the display unit of a factory terminal. [Modes for carrying out the invention]

[0014] The information processing system 10 according to this embodiment will be described below. Figure 1 is a diagram showing the schematic configuration of the information processing system 10.

[0015] As shown in FIG. 1, the information processing system 10 includes a server 20, a factory terminal 40, a factory terminal 60, a customer terminal 80, and a plurality of vehicles 100. The server 20 is communicably connected to the factory terminal 40, the factory terminal 60, and the customer terminal 80. The customer terminal 80 is communicably connected to the plurality of vehicles 100.

[0016] The server 20 is a server computer that performs various processes related to the information processing system 10. As an example, the server 20 is managed by tire manufacturer X. The server 20 is an example of the "information processing device" and "computer" of the present disclosure.

[0017] The factory terminal 40 is a computer terminal managed by a small-scale factory F1 provided near a mine (e.g., in the same country) where the plurality of vehicles 100 perform work. The small-scale factory F1 manufactures tires in combination with a case where a tread portion suitable for at least one or more specific vehicles 100 among the plurality of vehicles 100 is manufactured and stored as inventory. The tires are manufactured by pattern pasting or grooving. In the present embodiment, the specific vehicle 100 is all the vehicles 100 that perform work at the target mine. The mine is an example of the "workplace" of the present disclosure, and the small-scale factory F1 is an example of the "first factory".

[0018] The factory terminal 60 is a computer terminal managed by a large-scale factory F2 provided farther from the mine than the small-scale factory F1 (e.g., in a different country). The large-scale factory F2 is a factory that manufactures cases that can be used by the plurality of vehicles 100 that perform work at the mine. The large-scale factory F2 is an example of the "second factory".

[0019] Here, in the present embodiment, the "tread portion" of the tire is defined as the "tread portion" shown in the following URL <https: / / tire.bridgestone.co.jp / about / knowledge / basic-structure / >, and the "case" is defined as the "shoulder portion, sidewall portion, bead portion, belt, and carcass" other than the "tread portion". However, the definitions of the "tread portion" and "case" in the present embodiment are not limited to the above. It is also possible to define the "tread portion and belt" shown in the above URL as the "tread portion", and the "shoulder portion, sidewall portion, bead portion, and carcass" other than the "tread portion and belt" as the "case".

[0020] The customer terminal 80 is a computer terminal managed by the customer C who uses the tire at the mine.

[0021] The plurality of vehicles 100 are mine vehicles that perform operations at the mine. In FIG. 1, as an example, vehicle 100A, vehicle 100B, and vehicle 100C are shown, but the number of the plurality of vehicles 100 is not particularly limited. Each vehicle 100 is equipped with various known sensors, and the detection results of the various sensors are output to the customer terminal 80. Thereby, the customer terminal 80 can acquire the loading weight, speed, TKPH (tons per kilometer per hour), internal pressure and temperature of each tire, and the temperature, rainfall, and snowfall amount of the mine, etc. of each vehicle 100. Note that the above loading weight can be the loading weight per trip, or the central value, median, maximum value, minimum value, or σ, etc. of the loading weight per multiple trips. Also, the above speed can be the average speed or maximum speed of one day, etc.

[0022] In the information processing system 10, the large-scale factory F2 regularly manufactures cases and transports them to the small-scale factory F1. As a result, the cases are always stored as inventory in the small-scale factory F1. Then, upon receiving the needs of the customer C through the customer terminal 80, the server 20 proposes the specifications of the tread portion and the case suitable for the customer C, and instructs the small-scale factory F1 to manufacture tires suitable for a specific vehicle 100 based on the specifications of the tread portion and the case.

[0023] Next, we will describe the hardware configuration of server 20, factory terminal 40, factory terminal 60, and customer terminal 80.

[0024] Figure 2 is a block diagram showing the hardware configuration of server 20, factory terminal 40, factory terminal 60, and customer terminal 80. Since server 20, factory terminal 40, factory terminal 60, and customer terminal 80 are basically typical computer configurations, server 20 will be used as a representative example for the explanation.

[0025] As shown in Figure 2, the server 20 comprises a CPU (Central Processing Unit) 21, ROM (Read Only Memory) 22, RAM (Random Access Memory) 23, storage 24, input unit 25, display unit 26, and communication unit 27. Each component is connected to the others via a bus 28 so that they can communicate with each other.

[0026] The CPU 21 is a central processing unit that executes various programs and controls various components. Specifically, the CPU 21 reads a program from the ROM 22 or storage 24 and executes the program using the RAM 23 as a working area. The CPU 21 controls each of the above components and performs various calculations according to the program stored in the ROM 22 or storage 24. The CPU 21 is an example of a "processor" in this disclosure.

[0027] ROM22 stores various programs and data. RAM23 temporarily stores programs or data as a working area.

[0028] Storage 24 consists of storage devices such as HDDs (Hard Disk Drives), SSDs (Solid State Drives), or flash memory, and stores various programs and data.

[0029] The input unit 25 includes, for example, a pointing device such as a mouse, various buttons, a keyboard, a microphone, and a camera, and is used for various types of input.

[0030] The display unit 26 is, for example, a liquid crystal display and displays various information. The display unit 26 may also function as an input unit 25 by employing a touch panel system.

[0031] The communication unit 27 is an interface for communicating with other devices. For such communication, a wired communication standard such as Ethernet® or FDDI, or a wireless communication standard such as 4G, 5G, or Wi-Fi® may be used.

[0032] Furthermore, the functions of the CPU 41, ROM 42, RAM 43, storage 44, input unit 45, display unit 46, communication unit 47, and bus 48 of the factory terminal 40, the CPU 61, ROM 62, RAM 63, storage 64, input unit 65, display unit 66, communication unit 67, and bus 68 of the factory terminal 60, and the CPU 81, ROM 82, RAM 83, storage 84, input unit 85, display unit 86, communication unit 87, and bus 88 of the customer terminal 80 are the same as the functions of the CPU 21, ROM 22, RAM 23, storage 24, input unit 25, display unit 26, communication unit 27, and bus 28 of the server 20 described above.

[0033] Next, we will describe the configuration of the storage 24 of server 20. Figure 3 is a block diagram showing the configuration of the storage 24 of server 20.

[0034] As shown in Figure 3, the storage 24 contains the information processing program 24A, the generative model 24B, the database 24C, and the prediction logic 24D.

[0035] The information processing program 24A is a program that causes the CPU 21 to perform various processes described later. When executing the information processing program 24A, the server 20 uses the hardware resources shown in Figure 2 to perform the processing based on the information processing program 24A. The information processing program 24A is an example of an "information processing program" in this disclosure.

[0036] Generative Model 24B is a form of so-called generative AI (Artificial Intelligence). One example of Generative Model 24B is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ) and Gemini (Internet search <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the above. The generative model 24B is constructed using various known generative AIs as appropriate. The generative model 24B is obtained by performing deep learning on a neural network. The generative model 24B is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The generative model 24B infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data, graph data, tabular data, image data, and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0037] Database 24C stores various types of data. These types of data include, for example, environmental data, vehicle data, tire data, and update requirement data.

[0038] Environmental data is data that describes the environment of the mine. For example, environmental data includes the temperature, rainfall, snowfall, and road surface conditions of the mine. The temperature, rainfall, and snowfall of the mine are accumulated from data transmitted periodically (e.g., daily) from the customer terminal 80. Road surface conditions indicate the material of the road surface of the mine, and specifically, it shows mineral data for the mine entered by a human (e.g., a representative of tire manufacturer X).

[0039] Vehicle data includes data on the working status of multiple vehicles 100 in the mine. For example, vehicle data consists of basic information, load capacity, and speed of each vehicle 100. Basic information includes the manufacturer, model, load capacity, and drive system of each vehicle 100. The basic information represents the above data entered by a human (e.g., a representative of tire manufacturer X). Load capacity and speed data are accumulated from data transmitted periodically (e.g., daily) from the customer terminal 80.

[0040] Tire data refers to data about the tires fitted to each vehicle 100. For example, tire data consists of tire condition data, which indicates the condition of the tires, and tire status data, which indicates the state of the tires.

[0041] Tire condition data includes specifications such as size, pattern, permissible load, rubber type, and tread gauge, as well as tread depth, internal pressure, and temperature.

[0042] The specifications listed above are based on the considerations made by a representative of tire manufacturer X, taking into account customer C's needs and vehicle data. The specification data in database 24C is updated, for example, when new needs are received from customer C, with the latest information reviewed by the representative of tire manufacturer X based on those needs.

[0043] The remaining tread depth mentioned above indicates the remaining groove depth of the tire as measured at a predetermined time. For example, the remaining tread depth is accumulated from data transmitted from the customer terminal 80 at predetermined times. The measurement of the remaining tread depth is performed by customer C or a tire management service provider contracted by customer C, but the person performing the measurement is not particularly limited. Furthermore, the predetermined time can be various, such as when rotating tires from front to rear, once a month, or once every few days, but is not particularly limited.

[0044] The above internal pressure and temperature data are accumulated from data transmitted periodically (e.g., daily) from the customer terminal 80.

[0045] The tire condition data includes tire performance indicators such as wear, uneven wear, durability (e.g., durability level against high-temperature use, resistance to external cuts), traction, fuel efficiency, mileage at low pressure, and mileage at high pressure. The tire performance data is registered based on the above considerations made by a representative of tire manufacturer X, taking into account the performance desired by customer C. The tire performance data in database 24C is updated, for example, when new needs are received from customer C, with the latest needs and other information reconsidered by a representative of tire manufacturer X.

[0046] Furthermore, the data included in environmental data, vehicle data, and tire data are not limited to those described above. It is clear to any person with ordinary skill in the art of this disclosure that various types of data can be added as appropriate within the scope of the technical idea described in the claims.

[0047] The update requirement data indicates whether or not the prediction logic 24D needs to be updated. Database 24C registers either "Update Required Data" indicating that an update is necessary, or "Update Not Required Data" indicating that an update is not necessary, as update requirement data.

[0048] For example, if a representative from tire manufacturer X, based on information from customer C, calculates using existing prediction logic 24D and predicts that durability will be fine, but then a tire fails unusually early, or if many tires are discarded because the tread depth reaches zero without any durability failure, the representative will register update data indicating the nature of the problem in database 24C. If no update data is registered, database 24C will register predetermined "update not required data" as update requirement data.

[0049] The prediction logic 24D is a predictive model that proposes tire tread specifications and cases, indicating gauge, rubber, and pattern suitable for a specific vehicle 100, based on environmental data, vehicle data, and tire data stored in the database 24C. This prediction logic 24D is pre-created using known methods.

[0050] Figure 4 is a flowchart showing the flow of a specific process executed by the server 20. The specific process is performed when the CPU 21 reads the information processing program 24A from the storage 24, loads it into the RAM 23, and executes it. As an example, the specific process is started when a representative of tire manufacturer X performs a specific operation on the server 20 after receiving the needs of customer C.

[0051] In step S10 shown in Figure 4, the CPU 21 retrieves various data from the database 24C. Then, the CPU 21 proceeds to step S11.

[0052] In step S11, the CPU 21 determines whether or not the prediction logic 24D needs to be updated based on the various data acquired in step S10. If the CPU 21 determines that the prediction logic 24D needs to be updated (step S11: YES), it proceeds to step S12. On the other hand, if the CPU 21 determines that the prediction logic 24D does not need to be updated (step S11: NO), it proceeds to step S13. As an example, the CPU 21 determines that the prediction logic 24D needs to be updated if the update requirement data included in the various data is "data that needs updating". Note that the case where the update requirement data is "data that needs updating" is an example of "when the acquired data satisfies the predetermined update conditions" in this disclosure.

[0053] In step S12, the CPU 21 updates the prediction logic 24D to solve the problem indicated in the data to be updated. The update of the prediction logic 24D may be performed as appropriate using known methods. Then, the CPU 21 proceeds to step S13.

[0054] In step S13, the CPU 21 generates prompts to suggest tire tread specifications and cases suitable for a specific vehicle 100, based on the various data acquired in step S10. Then, the CPU 21 proceeds to step S14.

[0055] As an example, CPU21 generates the following prompt. Note that, for the sake of explanation, the specific details of the various data are omitted in the following prompt.

[0056] "prompt" Based on the following data, please propose tire tread specifications that indicate the appropriate gauge, rubber, and pattern for a specific vehicle (100 units). Furthermore, based on the following data, please propose a case suitable for a specific vehicle (100) from among several pre-prepared cases. The tread specifications and case proposals should be made using the prediction logic 24D stored in storage 24. Various data →Environmental data... →Vehicle data... →Tire data...

[0057] In step S14, the CPU 21 inputs the prompt generated in step S13 to the generation model 24B and obtains the output result from the generation model 24B. Then, the CPU 21 proceeds to step S15.

[0058] In step S15, the CPU 21 sends instruction data to the factory terminal 40 instructing the manufacture of a tire suitable for a specific vehicle 100, based on the tread specifications and case obtained as the output result of the generated model 24B in step S14. Then, the CPU 21 terminates the specific processing.

[0059] Next, an example of the display in the information processing system 10 will be described. Figure 5 shows an example of the display shown on the display unit 26 of the server 20. As an example, Figure 5 shows a suggestion screen that proposes the specifications and case of the tread section.

[0060] The proposal screen shown in Figure 5 includes a proposal field 50, a modify button 51, an OK button 52, a proposal field 53, a modify button 54, an OK button 55, and a manufacturing instruction button 56.

[0061] The suggestion section 50 is where you propose the specifications for the tread. In Figure 5, for illustrative purposes, the specific contents of the suggestion section 50 are omitted, but in reality, the suggestion section 50 displays the gauge, rubber, and pattern that indicate the recommended specifications for the tread.

[0062] When the edit button 51 is pressed, a representative from tire manufacturer X can manually modify the specifications of the tread section. Then, when the OK button 52 is pressed, the contents entered in the suggestion field 50 are finalized.

[0063] The proposal section 53 is where you propose a case. In Figure 5, for the sake of explanation, the specific contents of proposal section 53 are omitted, but in reality, proposal section 53 displays a case selected from multiple cases (e.g., Case A, Case B, Case C, etc.). Note that the performance of each of the pre-prepared cases differs.

[0064] When the edit button 54 is pressed, a representative from tire manufacturer X can manually correct the case. Then, when the OK button 55 is pressed, the contents entered in the suggestion field 53 are finalized.

[0065] The manufacturing instruction button 56 is a button used to instruct the manufacturing of a tire based on the tread specifications shown in the proposal field 50 and the case shown in the proposal field 53. When the manufacturing instruction button 56 is operated, instruction data indicating the tread specifications shown in the proposal field 50 and the case shown in the proposal field 53 is transmitted to the factory terminal 40.

[0066] Figure 6 shows an example of a display shown on the display unit 46 of the factory terminal 40. As an example, Figure 6 shows an instruction screen that indicates the manufacturing details of a tire. The instruction screen shown in Figure 6 displays the instruction content 70 and the exit button 90.

[0067] Instruction 70 indicates the tread specifications and case contents included in the instruction data transmitted from server 20. Specifically, the instruction 70 shown in Figure 6 contains the text: "The tread specifications are... Use... for the case." Based on this, small factory F1 can begin manufacturing tires suitable for a specific vehicle 100 based on instruction 70. The exit button 90 is used to close the instruction screen.

[0068] As explained above, in the server 20, the CPU 21 uses the prediction logic 24D stored in the storage 24 to propose tread specifications suitable for a specific vehicle 100 from environmental data, vehicle data, and tire data in the database 24C. Thus, according to the server 20, it is possible to propose tread specifications predicted from the mine environment, the working conditions of multiple vehicles 100 in the mine, and the tire data attached to each vehicle 100.

[0069] Furthermore, in the server 20, the CPU 21 uses the prediction logic 24D stored in the storage 24 to propose a case suitable for a specific vehicle 100 from among several pre-prepared cases. Thus, according to the server 20, it is possible to propose a case predicted from the mine environment, the working conditions of multiple vehicles 100 in the mine, and data on the tires fitted to each vehicle 100.

[0070] Furthermore, the CPU 21 in the server 20 transmits instruction data to the factory terminal 40 of the small factory F1, instructing the small factory F1 to manufacture a tire suitable for a specific vehicle 100 based on the proposed tread section specifications and case. As a result, the server 20 can instruct the small factory F1 to manufacture a tire suitable for a specific vehicle 100 as soon as it receives the needs of customer C, and can provide customer C with a tire that meets their needs in a timely manner. As described above, since the cases are stored as inventory in the small factory F1, there is no waiting for the production of cases at the large factory F2 or for the transportation of cases from the large factory F2. In other words, according to the information processing system 10 of this embodiment, the only waiting time for customer C is the manufacturing of the tread section at the small factory F1, so that customer C can be provided with a tire that meets their needs in a timely manner.

[0071] Furthermore, in server 20, if the data in the acquired data indicating whether an update is necessary is "data that needs updating," the CPU 21 updates the prediction logic 24D stored in storage 24 based on that "data that needs updating." As a result, server 20 can update the prediction logic 24D to solve problems arising from the tire usage in the mine.

[0072] Furthermore, in server 20, the CPU 21 estimates the case's durability margin, which indicates how well the tire can withstand a load, based on environmental data, vehicle data, and tire data in database 24C. If the estimated durability margin is below a predetermined threshold, the CPU 21 sends instruction data to the factory terminal 60 of the large-scale factory F2, instructing the manufacture of cases that can be used by multiple vehicles 100.

[0073] For example, the estimated durability of a case is performed as follows: The CPU 21 generates prompts for calculating at least one of the following: the tire's durability level in an indoor drum test, the rubber-to-rubber peel strength, and the rubber-to-steel peel strength, along with environmental data, vehicle data, and tire data from the database 24C. The CPU 21 inputs the generated prompts into the generation model 24B and obtains the output result from the generation model 24B. The CPU 21 then estimates the case's durability margin as the difference between the output result from the generation model 24B and a predetermined threshold leading to failure.

[0074] Furthermore, it is not limited to the immediate instruction to manufacture a case at the large-scale factory F2 if the estimated durability margin falls below a predetermined threshold. For example, the fact that the durability margin falls below a predetermined threshold may trigger a consideration by a representative of tire manufacturer X to determine whether other cases can withstand the load, whether other negative factors will occur, etc., and then instruction data may be sent to the factory terminal 60 based on the instructions of that representative.

[0075] As described above, in the information processing system 10 according to this embodiment, when a new case is needed at the mine, the manufacturing of the case is instructed to the large-scale factory F2, and the manufactured case is transported to the small-scale factory F1. According to the information processing system 10, since only the case is manufactured at the large-scale factory F2, the waiting time for customer C can be reduced compared to when tires are manufactured at the large-scale factory F2 and transported to customer C. Furthermore, according to the information processing system 10, since only the case is transported from the large-scale factory F2 to the small-scale factory F1, transportation costs and CO2 emissions can be reduced compared to when tires are transported.

[0076] (others) While embodiments of the present disclosure have been described in detail above with reference to the attached drawings, the technical scope of the present disclosure is not limited to these examples. It is clear that a person with ordinary skill in the art of the present disclosure may conceive of various modifications or alterations within the scope of the technical idea set forth in the claims, and these modifications or alterations are also understood to fall within the technical scope of the present disclosure.

[0077] Furthermore, the effects described in the above embodiments are descriptive or illustrative, and are not limited to those described in the above embodiments. In other words, the technology relating to this disclosure may produce other effects that would be obvious to a person of ordinary skill in the art of this disclosure from the descriptions in the above embodiments, in addition to or in lieu of the effects described in the above embodiments.

[0078] The processing described in the above embodiment can also be implemented using dedicated hardware circuits. In this case, it may be executed on one piece of hardware or on multiple pieces of hardware.

[0079] In the above embodiment, the specific vehicle 100 for which the optimal tread section specifications and case are proposed is all the vehicles 100 that work in the target mine. However, the vehicles 100 that constitute the specific vehicle 100 are not limited to these. For example, if the tires used in the target mine are divided into arbitrary groups, the specific vehicle 100 may be the vehicle 100 belonging to each group. In this case, the optimal tread section specifications and case will be proposed for each vehicle 100 belonging to each group.

[0080] In the above embodiment, if the equipment of the small-scale factory F1 is capable of handling both pattern application and grooving, the tire manufacturing method may be changed according to the customer C's request. In this case, the CPU 21 of the server 20 includes the tire manufacturing method and manufacturing details based on the customer C's request in the instruction data transmitted to the factory terminal 40 of the small-scale factory F1.

[0081] In the above embodiment, CPU 21 proposed specifications and a case for the tire tread portion suitable for a specific vehicle 100, but is not limited thereto. For example, CPU 21 may propose either specifications or a case for the tire tread portion suitable for a specific vehicle 100. Furthermore, the specifications for the tread portion are not limited to those indicating the gauge, rubber, and pattern. The specifications for the tread portion only need to include at least two of the gauge, rubber, and pattern, and may include the gauge and pattern, or the rubber and pattern, etc.

[0082] In the above embodiment, the term "processor" refers to a broad type of processor, including general-purpose processors (e.g., CPUs) and specialized processors (e.g., GPUs: Graphics Processing Units, ASICs: Application Specific Integrated Circuits, FPGAs: Field Programmable Gate Arrays, programmable logic devices, etc.).

[0083] Furthermore, the processor operations in the above embodiment may not be performed by a single processor, but may also be performed by multiple processors located in physically separate locations working together. Alternatively, some or all of the operations performed by specific multiple processors in the above embodiment may be integrated and performed by a single processor. In addition, the order of the processor operations is not limited to the order described in the above embodiment, but may be changed as appropriate.

[0084] Furthermore, although the above embodiment describes an embodiment in which the information processing program 24A is pre-stored (installed) in the storage 24, the invention is not limited thereto. The information processing program 24A may be provided in the form of a recording medium such as a CD-ROM (Compact Disk Read Only Memory), DVD-ROM (Digital Versatile Disk Read Only Memory), and USB (Universal Serial Bus) memory. Alternatively, the information processing program 24A may be provided in the form of a download from an external device via a network. The technology disclosed herein can also be applied to programs and program products.

[0085] [Contribution to the United Nations-led Sustainable Development Goals (SDGs)] The SDGs have been proposed to realize a sustainable society. One embodiment of this invention is considered to be a technology that can contribute to "No. 9 - Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation," among others. [Explanation of Symbols]

[0086] 10 Information Processing Systems 20. Servers (information processing equipment and computers) 21 CPU (Processor) 24A Information Processing Program< / url:>

Claims

1. Equipped with a processor, The aforementioned processor, The system acquires environmental data indicating the environment of a work site where multiple vehicles are working, vehicle data including the work status of the multiple vehicles at the work site, and tire data relating to the tires fitted to each of the multiple vehicles. Using a predictive logic capable of proposing tire tread specifications and cases suitable for at least one specific vehicle among the plurality of vehicles, including at least two gauges, rubbers, and patterns, the system proposes tread specifications or cases suitable for the specific vehicle based on the acquired environmental data, vehicle data, and tire data. Information processing device.

2. The aforementioned processor, Using the aforementioned prediction logic, the system proposes specifications for the tread section suitable for the specific vehicle, and also proposes a case suitable for the specific vehicle from among a number of pre-prepared cases. The information processing apparatus according to claim 1.

3. The processor proposes a gauge, rubber, and pattern suitable for the specific vehicle as the specifications for the tread portion. The information processing apparatus according to claim 1.

4. The aforementioned processor, Instruction data for manufacturing a tire suitable for the specific vehicle based on the proposed tread section specifications and case is transmitted to a terminal at the first factory located near the work site. The information processing apparatus according to claim 2.

5. The aforementioned processor, If the acquired data meets the predetermined update conditions, the prediction logic is updated based on that data. The information processing apparatus according to claim 1.

6. The aforementioned processor, Based on the acquired environmental data, vehicle data, and tire data, the case's durability margin, which indicates how much the tire can withstand under load, is estimated. If the estimated remaining durability is below a predetermined threshold, instruction data to manufacture a case usable by the multiple vehicles is transmitted to a terminal at a second factory located further away from the work site than the first factory located near the work site where the tires are manufactured. The information processing apparatus according to claim 1.

7. The system acquires environmental data indicating the environment of a work site where multiple vehicles are working, vehicle data including the work status of the multiple vehicles at the work site, and tire data relating to the tires fitted to each of the multiple vehicles. Using a predictive logic capable of proposing tire tread specifications and cases suitable for at least one specific vehicle among the plurality of vehicles, including at least two gauges, rubbers, and patterns, the system proposes tread specifications or cases suitable for the specific vehicle based on the acquired environmental data, vehicle data, and tire data. An information processing method in which a computer performs the processing.

8. The system acquires environmental data indicating the environment of a work site where multiple vehicles are working, vehicle data including the work status of the multiple vehicles at the work site, and tire data relating to the tires fitted to each of the multiple vehicles. Using a predictive logic capable of proposing tire tread specifications and cases suitable for at least one specific vehicle among the plurality of vehicles, including at least two gauges, rubbers, and patterns, the system proposes tread specifications or cases suitable for the specific vehicle based on the acquired environmental data, vehicle data, and tire data. An information processing program that causes a computer to perform a task.

Images