Inspection plan creation support device

Abstract

To provide an inspection plan creation support device that can automatically create a machine inspection plan with good inspection efficiency at the appropriate time, taking into account the impact of the load on the customer's machine usage.SOLUTION: A device calculates the standard value based on the cumulative number of parts replaced and the operation index, and calculates the load rate based on the ratio of the value calculated for each customer category based on the cumulative number of parts replaced and the standard value, estimates the future operating hours for each machine based on the operating history, calculates the maintenance timing of parts for each customer category based on the maintenance history and ratios, and estimates the maintenance timing based on the calculated maintenance timing of parts and the future operating hours, and creates an inspection schedule based on the estimated maintenance timing.SELECTED DRAWING: Figure 17

Description

[Technical field]

[0001] The present invention relates to an inspection plan creation support device. [Background technology]

[0002] 2. Description of the Related Art A known prior art technique for diagnosis and maintenance planning of various facilities such as production facilities in factories, social infrastructure facilities, auxiliary facilities in buildings, transportation facilities, and medical facilities is described in, for example, Patent Document 1.

[0003] Patent Document 1 discloses a composite diagnosis and maintenance plan support system which includes a target equipment, a sensor for measuring diagnostic basis data, a memory unit for storing the maintenance history and sensor measurement data of the target equipment and the sensor, and a diagnosis and maintenance plan support device, the diagnosis and maintenance plan support device including a life model estimation unit for estimating a life model with the desired maintenance history and sensor data as variable parameters, a risk diagnosis unit for calculating the failure risk and failure risk prediction value of the target equipment and the sensor using the life model, a composite risk calculation unit for calculating the composite risk and composite risk prediction value associated with abnormalities in the target equipment and the sensor from the failure risk and the failure risk prediction value, and a processing unit for comparing at least the failure risk prediction value and the composite risk prediction value with a threshold value and formulating a maintenance plan. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2009-251822 A Summary of the Invention [Problem to be solved by the invention]

[0005] In the above-mentioned conventional technology, a plan is made to carry out an inspection at a time when the risk of failure predicted by a life model using the operating time and the number of starts and stops exceeds a threshold.

[0006] However, the above-mentioned conventional technology has the following problems. That is, for example, when the method of using the machine or the environment of use fluctuates greatly, there is a concern that the accuracy of the prediction result will deteriorate. In addition, when the prediction accuracy is low, the inspection plan is predicted to deviate from the actual usage of the machine, which may cause problems such as lack of persuasiveness and time required to coordinate the inspection timing with the customer. Furthermore, since no consideration is given to the round-trip inspection of multiple machines that are geographically separated, the efficiency of the inspection may decrease.

[0007] The present invention has been made in consideration of the above, and aims to provide an inspection plan creation support device that can automatically and more accurately create an inspection plan for a machine that is efficient for inspection and that is appropriately timed taking into account the effect of the load on the machine due to how the customer uses it. [Means for solving the problem]

[0008] The present application includes a plurality of means for solving the above-mentioned problems. One example of such an inspection plan creation support device for determining the inspection timing of a machine includes an input device for inputting machine identification information including a customer category indicating how the machine to be inspected is used, an operation history in which an operation index including time-series data indicating the operating status of the machine is recorded, and a maintenance history in which the timing of part replacement and the cumulative number of part replacements is recorded, a storage device for storing the information inputted by the input unit, a calculation device for calculating an inspection plan for the machine based on the information in the storage device, and an output device for outputting the calculation result of the calculation device to a terminal device, The calculation device has a maintenance standard data calculation unit that calculates a standard value from the cumulative number of part replacements and an operation index, and calculates a load factor based on a ratio between a value calculated for each customer category from the cumulative number of part replacements and the operation index used to calculate the standard value and the standard value, and an inspection plan creation unit that estimates a future operation time for each machine from the operation history, calculates part maintenance timing for each customer category from the maintenance history and the ratio, estimates a maintenance time when the calculated part maintenance timing will arrive from the future operation time and the part maintenance timing, and creates an inspection timing based on the estimated maintenance timing. Effect of the Invention

[0009] According to the present invention, it is possible to automatically and more accurately create an inspection plan for a machine that is timed appropriately and has good inspection efficiency, taking into account the effect of the load caused by the customer's use of the machine. [Brief description of the drawings]

[0010] [Figure 1] FIG. 2 is a functional block diagram showing a configuration example of an inspection plan creation support device. [Diagram 2] 4 is a flowchart showing the process of the inspection plan creation support device. [Diagram 3] FIG. 4 illustrates an example of a data structure of an operation history. [Figure 4] 13 is a diagram illustrating an example of a data structure of an operation history after a new index is generated. FIG. [Diagram 5] FIG. 4 is a diagram illustrating an example of a data structure of machine identification information. [Figure 6] FIG. 13 illustrates an example of a data structure of a maintenance history. [Figure 7] 13 is a diagram illustrating an example of a data structure of a maintenance standard data creation table. FIG. [Figure 8] FIG. 4 is a diagram illustrating an example of a data structure of maintenance information. [Figure 9] FIG. 4 illustrates an example of a data structure of load data. [Figure 10] 11 is a flowchart showing the process of an inspection plan creation subroutine. [Figure 11] FIG. 13 is a diagram showing an example of a date estimation result. [Figure 12] FIG. 13 is a diagram illustrating an example of a data structure of a maintenance plan. [Figure 13] FIG. 1 is a diagram illustrating an example of an inspection plan creation method. [Figure 14] FIG. 11 is a diagram illustrating an example of a data structure of an inspection plan. [Figure 15] FIG. 13 is a diagram showing an example of an inspection plan screen. [Figure 16] FIG. 2 is a diagram illustrating an example of a data structure of used car information. [Figure 17] FIG. 13 is a diagram showing an example of an inspection time adjustment screen. [Figure 18] FIG. 2 is a diagram illustrating an example of a data structure of a construction plan. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. In the present embodiment, a work machine such as a hydraulic excavator is referred to as a "machine" and described as a subject for which an inspection plan is to be created, but the present invention is not limited to this and can be applied to other inspection subjects such as other work machines, vehicles, and power supply equipment.

[0012] FIG. 1 is a functional block diagram showing a configuration example of an inspection plan creation support device according to the present embodiment.

[0013] In FIG. 1, an inspection schedule creation support device 1 is connected, via a network 102, to a user terminal 103 (terminal device) used by a user, and a database 104 in which data is stored.

[0014] The user terminal 103 is an information processing device such as a PC (Personal Computer). A user issues a processing execution instruction to the inspection plan creation support device 1 through the user terminal 103. The user terminal 103 also has a function of displaying information output by the inspection plan creation support device 1 on a screen or the like and presenting it to the user.

[0015] The database 104 is, for example, a map system, a machine operation information system, an ERP (Enterprise Resources Planning) system, or a database that accumulates data equivalent to these, or a storage device.

[0016] The network 102 communicatively connects the user terminal 103, the database 104, and the inspection plan creation support device 1. The network 102 is, for example, any of a local area network (LAN), a wide area network (WAN), a virtual private network (VPN), and a communication network that uses a general public line such as the Internet in part or in whole.

[0017] The inspection schedule creation support device 1 is an information processing device such as a PC or a server computer, and includes a storage device 11, a calculation device 12, an input device 13 (input interface), and an output device 14 (output interface).

[0018] The storage device 11 stores various types of information, such as maintenance history 110, operation history 111, machine identification information 112, maintenance information 113 (maintenance history), load data 114, maintenance plan 115, inspection plan 116, used car information 117, and construction plan 118.

[0019] The calculation device 12 includes a maintenance standard data calculation unit 121 , a maintenance timing calculation unit 122 , an operation time prediction unit 123 , a maintenance time prediction unit 124 , a replacement time calculation unit 125 , and an inspection plan creation unit 126 .

[0020] Here, the flow of processing executed by the arithmetic unit 12 of the inspection plan creation support device 1 will be described.

[0021] FIG. 2 is a flowchart showing the process performed by the inspection plan creation support device.

[0022] 2 is premised on a predetermined number of maintenance histories 110, operation histories 111, machine identification information 112, used car information 117, and construction plans 118 being recorded in the database 104, and is started, for example, in response to a start command from a user to the user terminal 103. Note that steps S100 to S200 in FIG. 2 correspond to the processing related to the maintenance standard data calculation unit 121, and step S210 corresponds to the processing of calling the maintenance timing calculation unit 122, operation time prediction unit 123, maintenance time prediction unit 124, replacement time calculation unit 125, and inspection plan creation unit 126 as subroutines.

[0023] In FIG. 2, the computing device 12 first acquires the operation history 111 (step S100).

[0024] FIG. 3 is a diagram illustrating an example of a data structure of the operation history.

[0025] As shown in FIG. 3, the operation history 111 stores time-series data on the operation status of the machine, and is composed of the machine number, date, and operation indicators "hour meter, running time, ...". The machine number indicates number information that uniquely identifies the machine. The operation indicators include the hour meter, which is the cumulative engine operating time, and the running time, which is the cumulative running time of the machine, and indicate the operation status of the machine at the time of the "date" column. For example, the hour meter of 6.4 on 2022 / 2 / 11 means that the machine has been operated for a total of 6.4 hours since it was purchased new.

[0026] Next, one record of each column of the operation index in the operation history 111 is read (step S110), and a new index is generated by combining the products and ratios of the read indexes (step S120). In step S120, for example, "hour meter ÷ running time" is generated as a new index, which is a combination of the ratio of the hour meter and the running time.

[0027] Fig. 4 is a diagram showing an example of the data structure of the operation history after a new index is generated. Note that in Fig. 4, the value of "hour meter ÷ running time" on 2020 / 2 / 10 is N / A because the running time in the denominator is 0 (zero).

[0028] Next, it is determined whether the processing of steps S110 to S120 has been repeated for all records, i.e., whether steps S110 to S120 have been processed for all records (step S130). If the determination result is NO, the processing of steps S110 to S130 is repeated until the determination result becomes YES.

[0029] If the determination result in step S130 is YES, then the machine identification information 112 and the maintenance history 110 are read (step S140).

[0030] Fig. 5 is a diagram showing an example of the data structure of machine identification information, and Fig. 6 is a diagram showing an example of the data structure of maintenance history.

[0031] As shown in Fig. 5, the machine identification information 112 stores profile information for each machine number, which consists of the machine number, customer, customer category, location, and new machine purchase date. "Customer" is the customer name, customer category is information about how to use the machine, indicating what kind of work the customer will use the machine for, "location" is the coordinates (e.g., latitude and longitude) of the location where the machine is located, and "purchase date" indicates the date the machine was purchased. For example, machine number "001" means that it was purchased by "Company X" on 2 / 10 / 2020, the machine's usage is "civil engineering," and it is currently located at "x1, y1."

[0032] As shown in FIG. 6, the maintenance history 110 stores parts and prices of past maintenance targets, and is composed of the machine number, date, part, and price.

[0033] Next, the operation history 111, the machine identification information 112, and the maintenance history 110 are combined to generate a maintenance standard data creation table (step S150).

[0034] FIG. 7 is a diagram illustrating an example of a data structure of the maintenance standard data creation table.

[0035] As shown in Fig. 7, the maintenance standard data creation table records part replacement history by part, machine number, and number of times, and is composed of parts, machines, customer categories, number of times, and operation indexes. Note that "number of times" refers to the cumulative number of parts replacements.

[0036] Next, in order to calculate the standard failure period "Ti,j" for a target part "i" and operation index "j", a simple regression model is created in which the number of times in the maintenance standard data creation table is the objective variable "Ci" and the explanatory variable of the operation index is "xj" (step S160).

[0037] Since there are multiple types of operation indicators "hour meter, running time, ...", a number of operation indicators are created, such as a simple regression model with the hour meter as an explanatory variable and a simple regression model with the running time as an explanatory variable.

[0038] Next, an optimal model is selected from the candidates created in step S160, and a standard value of the failure period is calculated using the selected model, and output to the maintenance information (step S170).

[0039] That is, in step S170, first, when the regression coefficient of the regression model is calculated by a statistical method for the variables of the simple regression model, a simple regression model that maximizes the absolute value of the "t value" of the t-test statistic is selected, and the operation index and regression coefficient "Ti,j" (standard value of failure period) corresponding to the explanatory variable "xj" of the model are calculated (step S170). Here, the regression coefficient "Ti,j" can be calculated by the following (Equation 1).

[0040]

number

[0041] In the above (Equation 1), the subscript "n" corresponds to each record of the maintenance standard data creation table.

[0042] In addition, the calculated standard value of the failure period and the operation index are recorded in the maintenance information 113.

[0043] FIG. 8 is a diagram illustrating an example of a data structure of the maintenance information.

[0044] In FIG. 8, for example, the standard value of the failure period for "part 1" in the maintenance information 113 is "300 hours", which means that the "hour meter" is used as the operation index.

[0045] Next, when the customer category is "k", in order to calculate the failure period "Ti,k" for the target part "i" for each k, a simple regression model is created for each customer category, with the number of times in the maintenance standard data creation table as the objective variable "Ci,k" and the operation index selected in step S8 as the explanatory variable "x" (step S180).

[0046] Since there are multiple types of customer categories, such as "civil engineering, demolition, ...", a simple regression model for civil engineering, a simple regression model for demolition, and so on, are created for each customer category. Here, the regression coefficient "Ti,k" can be calculated using the following (Equation 2).

[0047]

number

[0048] In step S180, the load factor is calculated as the ratio of Equation 1 to Equation 2, “Ti,j÷Ti,k”, and stored in the load data 114.

[0049] FIG. 9 is a diagram illustrating an example of a data structure of the load data.

[0050] 9, the load data 114 is calculated for each customer category and each part. For example, in the first record, the load factor "0.8" of "Part 1" in the customer category "civil engineering" means that the failure period is 1.25 (=1÷0.8) times longer than the standard failure period.

[0051] Next, it is determined whether the processing of steps S160 to S190 has been repeated the number of times equal to the number of part types, i.e., whether steps S160 to S190 have been processed for all part types (step S200). If the determination result is NO, the processing of steps S160 to S190 is repeated until the determination result becomes YES.

[0052] If the determination result in step 200 is YES, then a subroutine for creating an inspection plan is called (step S210).

[0053] FIG. 10 is a flowchart showing the process of the inspection schedule creation subroutine.

[0054] 10, in the inspection plan creation subroutine (step S210 in FIG. 7), first, the operation history 111 is read (step S211), and then, using the date (current date) and the value of the operation index in the record corresponding to the latest date in the operation history 111, the date when the operation index will reach a predetermined value is estimated for each unit (step S212). The date estimation (calculation) in step S212 can be performed, for example, by the following (Equation 3).

[0055]

number

[0056] FIG. 11 is a diagram showing an example of a date estimation result.

[0057] Figure 11 shows the result of estimating the date when the hour meter of unit "001" at the current time, "2 / 1 / 2022", which is "2,800h", will reach "3,000h", which is "3 / 25 / 2022". By estimating the date in this way, it is possible to obtain the date when the operation index will reach a specified value for each unit.

[0058] Next, the maintenance timing for the part is calculated (step S213).

[0059] In step S213, first, in order to calculate the maintenance timing of the parts, the parts "part 1, part 2, ..." corresponding to the relevant machine number "001" are extracted from the maintenance information 113, and the load data 114 corresponding to the customer category "civil engineering" (machine identification information) of the relevant machine are extracted. The extracted part is defined as "i", the customer category as "k", and the load factor corresponding to the part "i" and the customer category "k" as "load factor i, k", and the standard value "Ti" of the failure period corresponding to the part "i" is extracted from the "period" column of the maintenance information 113. For example, in the case of part 1, "Ti" = "300h". By substituting the extracted Ti "300h" and load factor i "0.8" into the following (Equation 4), the failure period Ti,k "375h" of "part 1" in "civil engineering" can be calculated.

[0060]

number

[0061] Next, using the calculated failure period Ti,k "375 hours" and the current hour meter reading "2,800 hours", the next maintenance timing Mi,k "3,000 hours" for part 1 is calculated according to the following (Equation 5).

[0062]

number

[0063] Next, the maintenance timing of the part is calculated (step S214).

[0064] That is, in step S214, the maintenance timing at which the machine's operation index value reaches the maintenance timing Mi,k "3,000 hours" is calculated using the above (Equation 3).

[0065] 11, the maintenance time when the maintenance timing Mi,k reaches “3,000 h” is “3 / 25 / 2022.” The calculated maintenance time is recorded in the maintenance plan 115.

[0066] FIG. 12 is a diagram illustrating an example of a data structure of a maintenance plan.

[0067] 12, the maintenance plan 115 is composed of a machine number, a customer category, a load factor, a part, a maintenance time, and an area. Note that the "area" column stores the execution result of the subsequent process (step S217), so "-" is registered at this point.

[0068] Next, it is determined whether or not the processing of steps S213 to S214 has been repeated the number of times equal to the number of component types, that is, whether or not steps S213 to S214 have been processed for all component types (step S215). If the determination result is NO, the processing of steps S213 to S215 is repeated until the determination result becomes YES.

[0069] Furthermore, if the judgment result in step 215 is YES, then it is judged whether or not the processing of steps S211 to S215 has been repeated for the number of machines, i.e., whether or not steps S211 to S215 have been processed for all machines (step S216). If the judgment result is NO, the processing of steps S211 to S216 is repeated until the judgment result becomes YES.

[0070] In this manner, by repeating the processes from step S211 to step S216 for each number of machines and each type of part, the maintenance timing for each part in all machines can be obtained.

[0071] If the determination result in step S216 is YES, then area generation is performed in which machines whose position data are geographically close are grouped by clustering (step S217).

[0072] In step S217, a clustering method using, for example, k-means is used to group geographically close machines into areas. Here, the position of the machine is "A", the group of the machine is "G", the number of groups is "q", and the center coordinate of the group is "u". For example, the position A of the machine is set as the "position" column of the machine identification information 112 as the initial value, the number of groups q is "1+log2 (number of machines)", and the center coordinate u of the group is set by randomly selecting q machines from the "position" column of the machine identification information 112. Next, the position of the machine is assigned to the group with the closest center coordinate u, and the center coordinate u of the solution that minimizes the objective function of Equation 6 is obtained. The machine is reassigned to the group with the closest center coordinate u obtained here, and this is repeated until the value of the objective function of the following (Equation 6) does not change, so that geographically close machines can be grouped into optimal areas. This area information is recorded in the "area" column of the maintenance plan 115.

[0073]

number

[0074] Next, an inspection plan is created based on the maintenance timing calculated in step S214 and the area of ​​the machine identification information 112 (step S218).

[0075] FIG. 13 is a diagram illustrating an example of a method for creating an inspection plan.

[0076] In FIG. 13, a method for creating an inspection plan for "Area 1" is taken as an example. First, records in which "Area 1" is registered in the area column of the maintenance plan 115 are extracted and piled up by maintenance period. For example, the record of part 1 of unit "001" in FIG. 12 is piled up as maintenance period "2022 / 3 / 25". Here, if the capacity constraint per day in "Area 1" is set to two units, the amount that exceeds the capacity constraint is brought forward by collapsing the pile backward from the future toward the present, and the inspection period is determined. The determination result is recorded in the inspection plan 116.

[0077] FIG. 14 is a diagram illustrating an example of a data structure of an inspection plan.

[0078] 14, item group A is the column recorded in step 218, and consists of customer, machine number, customer category, part, load factor, maintenance time, area, and inspection time. The inspection and maintenance times for each machine number and part are recorded as "machine number", "part", "maintenance time", "inspection time", and "area", and "customer", "customer category", and "load factor" are obtained from the machine identification information 112 and load data 114 as accompanying information and recorded together.

[0079] FIG. 15 is a diagram showing an example of the inspection schedule screen.

[0080] By selecting the display period of the inspection plan on the inspection plan screen 141 shown in FIG. 15, the "customer", "machine number", "customer category", "load factor", "parts", "maintenance time", "location", and "area" information of the machine to be inspected is extracted from the inspection plan 116 and displayed, and the geographical location of the machine and map information are also displayed. The map information is obtained, for example, from a database 104 linked to a map system. It can be ascertained by checking the load factor whether the displayed maintenance time is earlier or later than the standard usage. For example, if the load factor exceeds 1, it can be determined that the load is higher than the standard usage and therefore the maintenance time is set earlier.

[0081] Next, the life cycle cost is calculated, and the replacement timing is extracted using the break-even point with the used car price as a key (step S219), and the process ends.

[0082] The inspection timing on the inspection plan screen 141 is a recommended value in the inspection plan creation support device 1, and the actual inspection timing requires coordination with the customer. In order to create cost information required for this coordination with the customer, in step S219, the life cycle cost is calculated and the used car information 117 is read. Specifically, first, in order to calculate the life cycle cost, the value of the "maintenance cost" column in the inspection plan 116 is obtained from the "price" column of the maintenance information 113 and recorded. In addition, the used car information 117 is read, and the turning point where the life cycle cost intersects with the used car price is extracted, and the time of sudden increase in costs just before the turning point is set as the recommended time for machine replacement.

[0083] FIG. 16 is a diagram illustrating an example of a data structure of used car information.

[0084] Used car information 117 shown in FIG. 16 stores price information of used cars according to the number of years that have passed since the new car was purchased.

[0085] FIG. 17 is a diagram showing an example of the inspection time adjustment screen.

[0086] 17, by selecting a unit from the menu, a construction plan 142A, an inspection plan 142B, and a life cycle cost and recommended replacement time 142C for that unit are displayed. The construction plan 142A can be edited by period (start-end) and event attributes (construction, rainy season, ...), and the editing results are recorded in the construction plan 118.

[0087] FIG. 18 is a diagram illustrating an example of a data structure of a construction plan.

[0088] 18 includes a period, a unit number, and an event attribute. In the event attribute, matters that a customer takes into consideration when deciding an inspection date (for example, wanting to inspect before construction or after the end of the rainy season) are registered.

[0089] Inspection plan 142B in the screen in FIG. 17 displays data registered in inspection plan 116. Note that "inspection time (recommended)" in the screen corresponds to the "inspection time" column of inspection plan 116, and the result of coordination with the customer is registered in the "confirmed inspection time" column of inspection plan 116. If the dates of the "inspection time (recommended)" and the "confirmed inspection time" are different, the inspection plan creation support device 1 asks the user the reason and records it in the "reason for changing inspection time" column. As another form of the inspection plan creation method, for example, a priority for determining the inspection time (for example, performing inspection before construction) may be extracted for each customer from statistics on the adoption rate of the recorded "reason for changing inspection time" and "inspection time (recommended)", and an inspection plan that satisfies the priority may be created.

[0090] In addition, the life cycle cost and recommended replacement timing 142C displays the estimated future life cycle cost of the relevant unit, the market price of used cars, and the recommended replacement timing. Since replacement of expensive parts occurs in the latter half of the life cycle, it is possible to propose the replacement timing to customers who wish to replace their units.

[0091] In the present embodiment configured as described above, an inspection plan creation support device for determining the inspection timing of a machine includes an input device for inputting machine identification information including a customer category indicating how the machine to be inspected is used, an operation history in which an operation index including time-series data indicating the operating status of the machine is recorded, and a maintenance history in which the timing of part replacement and the accumulated number of part replacements are recorded, a storage device for storing the information input by the input device, a calculation device for calculating an inspection plan for the machine based on the information in the storage device, and an output device for outputting the calculation result of the calculation device to a terminal device, and the calculation device calculates a standard value from the accumulated number of part replacements and the operation index, and outputs the cumulative number of part replacements and the calculation of the standard value to a terminal device. and an inspection plan creation unit that estimates future operation times for each machine from the operation history, calculates part maintenance timing for each customer category from the maintenance history and the ratio, estimates the maintenance time when the calculated part maintenance timing will arrive from the future operation times and the part maintenance timing, and creates an inspection timing based on the estimated maintenance timing.This makes it possible to automatically and more accurately create inspection plans for machines that are appropriate in timing taking into account the effect of load due to how the customer uses the machine and have good inspection efficiency.

[0092] <Additional Notes> The present invention is not limited to the above-described embodiments, and includes various modifications and combinations within the scope of the gist of the present invention. The present invention is not limited to those having all the configurations described in the above-described embodiments, and includes those in which some of the configurations are deleted. The above-described configurations, functions, etc. may be realized by designing some or all of them as an integrated circuit, for example. The above-described configurations, functions, etc. may be realized by software, in which a processor interprets and executes a program that realizes each function. [Explanation of symbols]

[0093] 1...inspection plan creation support device, 11...storage device, 12...arithmetic device, 13...input device (input interface), 14...output device (output interface), 102...network, 103...user terminal, 104...database, 110...maintenance history, 111...operation history, 112...machine identification information, 113...maintenance information, 114...load data, 115...maintenance plan, 116...inspection plan, 117...used car information, 118...construction plan, 121...maintenance standard data calculation unit, 122...maintenance timing calculation unit, 123...operation time prediction unit, 124...maintenance timing prediction unit, 125...replacement timing calculation unit, 126...inspection plan creation unit, 141...inspection plan screen, 142...inspection timing adjustment screen, 142A...construction plan, 142B...inspection plan, 142C...recommended replacement timing

Claims

1. An inspection plan creation support device that determines a timing for machine inspection, an input device for inputting machine identification information including a customer category indicating how the machine to be inspected is used, an operation history including an operation index including time-series data indicating the operation status of the machine, and a maintenance history including the timing of part replacement and the cumulative number of part replacements; a storage device that stores information input by the input device; a computing device that computes an inspection plan for the machine based on information in the storage device; an output device that outputs a calculation result of the calculation device to a terminal device, The computing device includes: a maintenance standard data calculation unit that calculates a standard value from the cumulative number of parts replaced and an operation index, and calculates a load factor based on a ratio between a value calculated for each customer category from the cumulative number of parts replaced and the operation index used to calculate the standard value and the standard value; an inspection plan creation unit that estimates future operation time for each machine from the operation history, calculates part maintenance timing for each customer category from the maintenance history and the ratio, estimates a maintenance time when the calculated part maintenance timing will arrive from the future operation time and the part maintenance timing, and creates an inspection timing based on the estimated maintenance timing.

2. 2. The inspection schedule creation support device according to claim 1, The inspection plan creation unit Estimating future operation time for each machine from the operation history; Calculating the timing of part maintenance for each customer category based on the maintenance history and the ratio; The maintenance timing when the calculated part maintenance timing is reached is the future operating time, Estimated from the maintenance timing of the parts, The estimated maintenance period, Create inspection times based on area information labeled by geographical proximity from the location data of the machine identification information, An inspection plan creation support device characterized by:

3. 2. The inspection schedule creation support device according to claim 1, The maintenance standard data calculation unit A standard value of the failure period is calculated from the regression equation having the maximum coefficient of determination among a plurality of regression equations created from combinations of the cumulative number of parts replaced and one or more operation indicators; Calculating a load factor from a ratio of a failure period calculated for each customer category from the cumulative number of parts replaced and the operation index used to calculate the standard value to the standard value; An inspection plan creation support device characterized by:

4. 2. The inspection schedule creation support device according to claim 1, The maintenance standard data calculation unit When all of the coefficients of determination of a plurality of regression equations created from the combination of the cumulative number of parts replaced and one or more operation indexes are less than a specified value, a standard value of the failure period is calculated using an average value. An inspection plan creation support device characterized by:

5. 2. The inspection schedule creation support device according to claim 1, The storage device includes: having second-hand information indicating the second-hand price of the machine by age; The computing device includes: A replacement timing calculation unit detects a point at which the life cycle cost suddenly decreases backward from a branch point where the price of the maintenance history, the life cycle cost obtained by accumulating the estimated maintenance cost for each inspection period, and the used car price for each age intersect, and sets the point as a replacement timing recommendation value. An inspection plan creation support device characterized by:

6. 6. The inspection plan creation support device according to claim 5, The output device outputs, as a result of the calculation by the calculation device, An inspection plan creation support device characterized in that at least the customer category, the inspection time, and the replacement time are output to the terminal device and displayed on the same screen of the terminal device.

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