Failure prevention system

Abstract

To provide a failure prevention system capable of preventing in advance, on the basis of malfunction information on a part, machine down of a construction machine adopting the part from occurring.SOLUTION: A failure prevention system 1 comprises a server device 10 which provides information for preventing a failure of a construction machine to a terminal 20 via a communication line 30. The server device 10 determines whether or not there is any unusual order receiving in acquired order receiving information on a part, determines whether or not unusual order receiving is owing to a failure of the part when determining that there is unusual order receiving, and transmits information on the part relating to the unusual order receiving to the terminal 20 when determining that the unusual order receiving is owing to a failure of the part.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a failure prevention system for construction machinery. [Background technology]

[0002] In the field of such technology, for example, a parts procurement system is known, as described in Patent Document 1, which is capable of quickly responding to various breakdowns in construction machinery and shortening downtime. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2019-67044 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the parts procurement system described in Patent Document 1 is a system designed for post-maintenance, meaning that it is a system that can reduce downtime by quickly procuring and replacing parts related to a failure after a part in a construction machine fails, so there was a problem in that it could not prevent the machine from going down (in other words, the construction machine being in a state where it cannot be operated).

[0005] An object of the present invention is to provide a failure prevention system that can prevent a construction machine that uses a part from going down based on defect information about the part. [Means for solving the problem]

[0006] The failure prevention system of the present invention is a failure prevention system equipped with a server device that provides information to prevent failures in construction machinery to a terminal via a communication line, and is characterized in that the server device acquires order information for parts for the construction machinery, determines whether or not there are any abnormal orders based on the acquired order information for the parts, and if it determines that there is an abnormal order, determines whether or not the abnormal order is due to a parts failure, and if it determines that the abnormal order is due to a parts failure, sends information about the parts related to the abnormal order to the terminal.

[0007] In the failure prevention system according to the present invention, the server device determines whether or not there is an abnormal order from the acquired order information for construction machine parts. If it determines that there is an abnormal order, it further determines whether the abnormal order is due to a part failure. If it determines that the abnormal order is due to a part failure, it sends information about the part related to the abnormal order to the terminal. This makes it possible to detect part failures early and prevent machine downtime due to part failure. As a result, it is possible to prevent a construction machine using a part from downtime based on the part defect information. [Effects of the Invention]

[0008] According to the present invention, it is possible to prevent a construction machine using a part from coming down based on defect information about the part. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a schematic configuration diagram showing a failure prevention system according to an embodiment; [Figure 2] 4 is a flowchart showing a control process of the failure prevention system according to the embodiment. [Figure 3] FIG. 10 is a diagram illustrating an example of order information for parts. [Figure 4] FIG. 10 is a diagram illustrating an example of a determination result of an abnormal order or a normal order. [Figure 5] FIG. 10 is a diagram showing an example of part complaint information. [Figure 6]FIG. 10 is a diagram showing an example of part production number information. [Figure 7] FIG. 10 is a diagram illustrating an example of machine information. [Figure 8] FIG. 10 is a diagram showing an example of a failure information registration parts list. [Figure 9] FIG. 10 is a diagram illustrating an example of inventory information of parts. [Figure 10] FIG. 10 is a diagram illustrating an example of inventory information of alternative parts. [Figure 11] FIG. 10 is a diagram showing an example of serial number information relating to a countermeasure part or an alternative part. [Figure 12] FIG. 10 is a diagram illustrating an example of a recommendation. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, an embodiment of a failure prevention system according to the present invention will be described with reference to the drawings. In the following description, to avoid complication of explanation, "construction machine parts" may be abbreviated to "parts."

[0011] 1 is a schematic diagram showing a failure prevention system according to an embodiment. The failure prevention system 1 of this embodiment is a system for preventing failures in parts of construction machinery, and includes a server device 10 that provides information for preventing part failures, and a terminal 20 that is configured to be able to communicate with the server device 10 via a communication line 30. Examples of construction machinery include excavators, loaders, transport machines, cranes, loading machines, foundation construction machines, drilling machines, tunnel construction machines, motor graders, roadbed machines, compaction machines, concrete machines, paving machines, and road maintenance machines.

[0012] The terminal 20 may be a PC (Personal Computer), a tablet terminal, a smartphone, a mobile phone, a PDA (Personal Data Assistant), etc. Preferably, it is a tablet terminal or a smartphone that is easy for a service person to carry around. Also, although only one terminal 20 is shown in FIG. 1, multiple terminals may be used.

[0013] The server device 10 is the main computer that constitutes the failure prevention system 1, and acquires various information about construction machinery input by agents and service personnel around the world in real time or periodically, analyzes the acquired information, and transmits information to the terminal 20 to prevent failures in parts of construction machinery operating all over the world, thereby informing service personnel, etc.

[0014] This server device 10 is configured by a microcomputer that combines, for example, a CPU that performs calculations, a ROM (Read Only Memory) as a secondary storage device that stores programs for the calculations, and a RAM (Random Access Memory) as a temporary storage device that saves the calculation progress and temporary control variables, and performs processes such as learning and judgment by executing the stored programs.

[0015] 1, the server device 10 includes an information acquisition unit 11, a storage unit 12, and a determination unit 13. The information acquisition unit 11 acquires information such as order information, complaint information, and work history related to construction machine parts from other systems and servers via a communication line 30.

[0016] The storage unit 12 stores various pieces of information (e.g., parts order information, complaint information, work history, etc.) acquired by the information acquisition unit 11. The storage unit 12 also stores a parts master database for construction machines, a fault information registered parts list (described later), inventory information for countermeasure parts or replacement parts, etc.

[0017] The determination unit 13 determines whether or not there is an abnormal order for a part, and whether or not the abnormal order is due to a malfunction of the part.

[0018] The control process of the server device 10 will be described below with reference to Fig. 2. The control process shown in Fig. 2 is executed repeatedly, for example, at a predetermined cycle.

[0019] First, in step S101, the information acquisition unit 11 acquires order information for construction machine parts from, for example, the order information management system 40 connected via the communication line 30, and stores the acquired order information in the storage unit 12. The order information management system 40 is a system that collects and manages order information for parts entered via information registration terminals by, for example, agents and service personnel around the world. The order information for parts acquired by the information acquisition unit 11 is, for example, data such as that shown in FIG. 3.

[0020] 3, the order information of parts is managed by items such as "order part number," "part name," "part name," "model name," "order year and month," "number of orders in this month," "number of orders per year," and "number of orders in the past 10 years." When such order information of parts is acquired, it is stored in the storage unit 12.

[0021] In step S102 following step S101, the determination unit 13 determines whether or not there is an abnormal order for a part based on the order information for the parts acquired in step S101. At this time, it is preferable that the determination unit 13 determines whether or not there is an abnormal order for a part using a statistical method such as Bollinger bands based on the order volume of the part within a predetermined period. Specifically, the determination unit 13 draws a 12-month moving average line and lines indicating the fluctuation range (in other words, standard deviation) above and below the 12-month moving average line for the order information for each part over the past year (12 months), and determines that orders that fall within the fluctuation range above and below are normal orders, and orders that fall outside the fluctuation range are abnormal orders.

[0022] Fig. 4 is a diagram showing an example of the determination result of abnormal orders or normal orders. As shown in Fig. 4, the determination unit 13 calculates the "12-month moving average" and "standard deviation" for each piece of order information of each part shown in Fig. 3, and uses them to determine whether the order is normal or abnormal.

[0023] If it is determined in step S102 that there are no abnormal orders for all parts (in other words, that all parts are normal orders), the control process ends. On the other hand, if it is determined that there is an abnormal order for at least one part among the multiple parts, the control process proceeds to step S103.

[0024] In step S103, the information acquisition unit 11 acquires complaint information, serial number information, and machine information for the part determined to be an abnormal order in step S102 (hereinafter referred to as "part related to the abnormal order"). At this time, the information acquisition unit 11 acquires the complaint information for the part from, for example, a complaint information management system 50 connected via the communication line 30, and stores the acquired complaint information in the storage unit 12. The complaint information management system 50 is a system that collects and manages complaint information entered, for example, by sales agents and service personnel around the world via their respective information registration terminals.

[0025] The part complaint information acquired by the information acquisition unit 11 is, for example, data as shown in Fig. 5. As shown in Fig. 5, the part complaint information is managed by items such as "date of receipt," "part number," "part name," "machine," "content of complaint," "country," "model name," "name of phenomenon," "hour meter," "year and month of new car delivery," "number of months elapsed," and "average operating time." Once such part complaint information is acquired, it is stored in the storage unit 12.

[0026] Furthermore, in step S103, the information acquisition unit 11 acquires part production number information from the production number information management system 60 connected via the communication line 30, for example, and stores the acquired production number information in the storage unit 12. The production number information management system 60 is a system that collects and manages production number information entered via information registration terminals by, for example, agents and service personnel around the world. Note that the production number information corresponds to the "work history" set forth in the claims, and is a general term for part order information and each work instruction information.

[0027] The part serial number information acquired by the information acquisition unit 11 is, for example, data as shown in Fig. 6. As shown in Fig. 6, the part serial number information is managed by items such as "received date," "business code," "business name," "work content," "production number," "production number category name," "part number," "part name," "machine," "new vehicle delivery date," "number of months elapsed," "hour meter," "average operating time," "measure name," "phenomenon name," "round trip time," "work instruction time," and "work completion date." Once such part serial number information is acquired, it is stored in the memory unit 12.

[0028] Furthermore, in step S103, the information acquisition unit 11 acquires information about the machine (i.e., construction machine) on which the part related to the abnormal order is installed, for example, from the machine information management server 70 connected via the communication line 30. The machine information acquired by the information acquisition unit 11 is, for example, data such as that shown in FIG. 7. As shown in FIG. 7, the machine information is managed by items such as "machine," "model name," "industry name in which the construction machine was used," "hour meter," and "average operating time." Once such machine information is acquired, it is stored in the memory unit 12.

[0029] In step S104 following step S103, the determination unit 13 determines whether or not the abnormal order is due to a component failure based on the information acquired in step S103. At this time, the determination unit 13 first constructs a failure model by performing machine learning (e.g., a decision tree) on past failure information recorded in the failure information registered parts list, and then determines whether or not the abnormal order is due to a component failure based on the constructed failure model and the information acquired in step S103. The failure information registered parts list is stored in the storage unit 12.

[0030] If it is determined that the abnormal order is not due to a malfunction, the control process ends. On the other hand, if it is determined that the abnormal order is due to a malfunction, the control process proceeds to step S105. In step S105, the server device 10 registers the malfunction information related to the determination in step S104 in the malfunction information registered parts list and updates the list. By updating the malfunction information registered parts list in this way and feeding it back to the database for machine learning, a malfunction model can be constructed with high accuracy, thereby improving the accuracy of the determination process in step S104.

[0031] An example of a failure information registration parts list is the data shown in Fig. 8. As shown in Fig. 8, the list is made up of items such as "failure registration part number," "failure registration part name," "response category," "number of days elapsed," "model name," "name of the accident part," "failure registration details," "occurrence area," "registration date," "response completion date," "response part number," and "response part name."

[0032] In step S106 following step S105, the determination unit 13 determines whether or not there are countermeasure parts for the parts involved in the abnormal order. The countermeasure parts referred to in this embodiment are the same parts as the parts involved in the abnormal order. At this time, the information acquisition unit 11 first acquires inventory information for parts of the construction machine from the parts inventory management system 80 connected, for example, via the communication line 30. The parts inventory information acquired by the information acquisition unit 11 is, for example, data such as that shown in FIG. 9. As shown in FIG. 9, the parts inventory information is managed by items such as "part number," "part name," "part name," and "inventory quantity." Once such parts inventory information is acquired, it is stored in the memory unit 12.

[0033] Next, the determination unit 13 determines whether or not there is a countermeasure part in the inventory information of parts acquired by the information acquisition unit 11. If it is determined that there is a countermeasure part, the control process proceeds to step S108, where a parts list is created. At this time, the server device 10 creates the list of countermeasure parts. On the other hand, if it is determined that there is no countermeasure part, the control process proceeds to step S107.

[0034] In step S107, the determination unit 13 determines whether or not there is a substitute part for the part involved in the abnormal order. In this embodiment, a substitute part refers to a part that is the same part and of the same item as the part involved in the abnormal order, and that is compatible and similar. At this time, the information acquisition unit 11 first acquires inventory information for the substitute part from the substitute part inventory management system 90 connected via, for example, the communication line 30. The inventory information for the substitute part acquired by the information acquisition unit 11 is, for example, data such as that shown in FIG. 10. As shown in FIG. 10, the inventory information for the substitute part includes, in addition to the "part number," "part name," and "part name," the number of the substitute part corresponding to each part ("substitute part number"), the "part name," "item name," and "inventory quantity."

[0035] Next, the determination unit 13 determines whether or not there are any substitute parts for the part involved in the abnormal order in the substitute parts inventory information acquired by the information acquisition unit 11. If it is determined that there are no substitute parts, the control process ends. On the other hand, if it is determined that there are substitute parts, the control process proceeds to step S108, where a list of substitute parts is created.

[0036] In step S109, following step S108, the server device 10 creates a recommendation. At this time, the server device 10 first extracts serial number information related to the countermeasure part or replacement part from the serial number information of the part related to the abnormal order acquired in step S103. The extracted serial number information related to the countermeasure part or replacement part is, for example, data such as that shown in FIG. 11. As shown in FIG. 11, the extracted serial number information includes the "part number," "received date," "business code," "business name," "work content," "serial number," "serial number category name," "machine," "new vehicle delivery date," "number of elapsed months," "hour meter," "average operating time," "countermeasure name," "phenomenon name," "round trip time," "work instruction time," and "work completion date," as well as the "category" and "person in charge" indicating the countermeasure part or replacement part. The "person in charge" here refers to the name of the service technician who performed the work. By including service technician information in the serial number information, it is possible to identify the target person (recommended person) to whom a recommendation should be made using machine learning, as described below. When such production number information is extracted, it is stored in the storage unit 12.

[0037] Next, the server device 10 performs machine learning on the extracted production number information related to the countermeasure parts or alternative parts to create recommendations for the countermeasure parts or alternative parts. The created recommendations are, for example, as shown in FIG. 12. As shown in FIG. 12, the recommendations are created to propose multiple parts (countermeasure parts or alternative parts) for each recommendation target (i.e., person in charge), and each proposed part is given a number indicating its priority. Here, the larger the number, the higher the priority of the proposal.

[0038] In step S110 following step S109, the server device 10 transmits information about the part related to the abnormal order (for example, the part number and its failure information), a list of countermeasure parts or a list of substitute parts, and a recommendation to the terminal 20, thereby notifying the service person. This completes the series of control processes.

[0039] The service personnel (i.e., the person in charge) can obtain the part numbers of the construction machinery, their fault information, a list of countermeasure parts or a list of replacement parts, and recommendations via terminal 20, making it possible to suggest replacement of countermeasure parts or replacement parts to the user or owner of the construction machinery in a timely manner.

[0040] In the failure prevention system 1 of this embodiment, the server device 10 determines whether the acquired part order information contains an abnormal order. If it determines that an abnormal order exists, it further determines whether the abnormal order is due to a part failure. If it determines that the abnormal order is due to a part failure, it transmits information about the part related to the abnormal order and information about a replacement part or a substitute part for the part related to the abnormal order to the terminal 20. This allows construction machinery service personnel and others to grasp the status of the parts via the terminal, thereby enabling early detection of part failure and preventing machine downtime due to part failure. As a result, based on part defect information, it is possible to prevent a construction machine that uses the part from downtime. Furthermore, if a replacement part for the part related to the abnormal order is not available, a replacement part for the part related to the abnormal order can be suggested, thereby maintaining stable operation of the construction machine until the replacement part is obtained. Furthermore, this also improves the work efficiency of service personnel.

[0041] The present invention is not limited to the above embodiment. For example, when determining whether an abnormal order is due to a part failure, the server device 10 may assign a countermeasure priority to the part based on the complaint information and work history of the part related to the abnormal order, and determine whether the abnormal order is due to a part failure in accordance with the countermeasure priority.

[0042] Specifically, the server device 10 first comprehensively considers the number of complaints included in the complaint information, the length of the part ordering period included in the work history, etc., and assigns a priority order of countermeasures (for example, a score) to the parts. Next, the server device 10 sets a reference value for each category by having AI (Artificial Intelligence) learn parts with past failure information registration and expert know-how, and then uses the set reference values ​​to determine whether the abnormal order is due to a part failure, starting from the one with the highest countermeasure priority.

[0043] In the above-described embodiment, information on countermeasure parts or alternative parts for parts involved in abnormal orders may be obtained from, for example, the parts procurement system disclosed in the above-described Japanese Patent Application Laid-Open No. 2019-67044.

[0044] Although the embodiments of the present invention have been described in detail above, the present invention is not limited to the above-described embodiments, and various design modifications can be made without departing from the spirit of the present invention as set forth in the claims. [Explanation of symbols]

[0045] 1. Failure prevention system 10 Server device 11 Information acquisition department 12 Storage section 13 Judgment section 20 terminals 30 Communication Lines 40 Order Information Management System 50 Complaint Information Management System 60 Production number information management system 70 Machine information management server 80 Parts inventory management system 90 Replacement Parts Inventory Management System

Claims

1. A failure prevention system including a server device that provides information for preventing failures in construction machines to a terminal via a communication line, The server device Acquire order information for the construction machine parts; determining whether or not there is an abnormal order based on the quantity of orders for the parts received within a predetermined period of time for the acquired order information for the parts; When it is determined that an abnormal order has been received, it is determined whether the abnormal order is due to a breakdown of a part based on the complaint information and work history of the part related to the abnormal order. A failure prevention system characterized in that, when it is determined that the abnormal order is caused by a part failure, information on the part related to the abnormal order is transmitted to the terminal.

2. A failure prevention system having a server device that provides information to prevent failures of construction machinery to a terminal via a communication line, The server device Acquire order information for the construction machine parts; determining whether or not there is an abnormal order based on the quantity of orders for the parts received within a predetermined period of time for the acquired order information for the parts; When it is determined that an abnormal order has been received, a priority order for countermeasures is assigned to the part based on the complaint information and work history of the part related to the abnormal order, and whether or not the abnormal order is due to a failure of the part is determined in accordance with the priority order for countermeasures. A failure prevention system characterized in that, when it is determined that the abnormal order is caused by a part failure, information on the part related to the abnormal order is transmitted to the terminal.

3. 3. The failure prevention system according to claim 1, wherein the server device transmits to the terminal information on the part involved in the abnormal order, as well as information on a countermeasure part or a substitute part for the part involved in the abnormal order.

4. 4. The failure prevention system according to claim 3, wherein, when it is determined that the abnormal order is caused by a part failure, the server device determines whether or not a countermeasure part for the part involved in the abnormal order is available, and if it is determined that a countermeasure part is available, transmits information about the countermeasure part to the terminal; when it is determined that a countermeasure part is not available, the server device further determines whether or not a substitute part for the part involved in the abnormal order is available, and if it is determined that a substitute part is available, transmits information about the substitute part to the terminal.

5. 5. The failure prevention system according to claim 3, wherein the server device performs machine learning on the work history of the parts involved in the abnormal order to create recommendations for the countermeasure parts or the alternative parts, and transmits the created recommendations to the terminal.

6. 6. The failure prevention system according to claim 5, wherein the work history includes information about the service personnel who performed the work.

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