Statistical analysis method and device for stop state of numerical control equipment

Abstract

The application provides a statistical analysis method and device for the downtime state of a numerical control equipment, and relates to the technical field of numerical control machining. The technical problem of how to realize accurate statistics and analysis of the downtime state of the numerical control equipment while saving personnel time is solved. The method comprises the following steps: obtaining at least one downtime duration of a target numerical control equipment within a target time period; determining the downtime reason corresponding to each downtime duration; and performing statistical analysis on all downtime durations and the downtime reasons corresponding to each downtime duration to obtain a statistical analysis result, wherein the statistical analysis result comprises work time loss corresponding to different downtime reasons. The above method does not require special personnel to observe the equipment, and can realize accurate recording of the downtime duration of the numerical control equipment and accurate matching of the downtime reason and the downtime duration, thereby saving labor costs and realizing accurate statistics and analysis of the downtime state of the numerical control equipment.

Description

Technical Field

[0001] This application belongs to the field of CNC machining technology, and in particular relates to a statistical analysis method and device for the shutdown status of CNC equipment. Background Technology

[0002] Numerical control (NC) machining refers to the process of machining parts on CNC equipment. Specifically, it involves the control system issuing commands to cause the cutting tools on the CNC equipment to perform various required movements, and machining is carried out using numbers and letters to represent the technical requirements and processing requirements such as the shape and size of the workpiece. NC machining has a wide range of applications in the field of mechanical processing, such as defense and aerospace, automotive industry, mold manufacturing, machining, and parts construction.

[0003] A complete CNC machining process or a CNC machining workshop often includes one or more CNC machines, each of which may experience different states such as running, stopped, and alarming. Downtime results in lost working hours; therefore, accurate statistical analysis of CNC machine downtime status is a crucial prerequisite for improving equipment operating efficiency.

[0004] Traditional statistical analysis methods involve manual statistical analysis to obtain statistical results. This model consumes a lot of people's time and the data accuracy is not high, resulting in inaccurate analysis results.

[0005] Therefore, how to accurately count and analyze the downtime status of CNC equipment while saving personnel time has become an urgent technical problem to be solved. Summary of the Invention

[0006] This application provides a statistical analysis method and apparatus for the shutdown status of CNC equipment, which can solve the technical problem in the prior art that the statistical analysis of the shutdown status of CNC equipment consumes a lot of personnel time and the data accuracy is not high, resulting in inaccurate analysis results.

[0007] In a first aspect, embodiments of this application provide a statistical analysis method for the shutdown status of CNC equipment, including:

[0008] Obtain at least one downtime of the target CNC equipment within the target time period;

[0009] Determine the cause of downtime for each downtime duration;

[0010] Statistical analysis is performed on all downtime durations and the corresponding downtime causes to obtain statistical analysis results, which include the time losses corresponding to different downtime causes.

[0011] In the above embodiments, by obtaining at least one downtime of the target CNC equipment within a target time period and determining the downtime cause corresponding to each downtime, and then performing statistical analysis on all downtimes and downtime causes, the time loss corresponding to different downtime causes can be obtained. Without the need for dedicated personnel to observe the equipment, accurate recording of the downtime of the CNC equipment and accurate matching of downtime causes and downtime can be achieved, thereby avoiding the consumption of a large amount of personnel time and achieving accurate statistics and analysis of the downtime status of the CNC equipment.

[0012] In one possible implementation of the first aspect, obtaining at least one downtime of the target CNC equipment within a target time period includes:

[0013] Obtain the device status of the target CNC equipment at multiple times within the target time period;

[0014] The at least one downtime duration is determined based on the multiple times and the corresponding device status at each time.

[0015] In one possible implementation of the first aspect, the device status of the target CNC device at multiple times is obtained through the communication port or a preset communication protocol on the target CNC device, or through an I / O signal acquisition device set on the target CNC device.

[0016] In one possible implementation of the first aspect, the device state is a shutdown state, an operating state, or an alarm state;

[0017] Determining the at least one downtime duration based on the plurality of times and the corresponding device states at each time includes:

[0018] All first moments are determined from the plurality of moments, and the device state corresponding to the first moment is a shutdown state;

[0019] The total time length corresponding to the first moment of each consecutive group is defined as a downtime.

[0020] In one possible implementation of the first aspect, determining the downtime reason corresponding to each downtime duration includes:

[0021] Based on any downtime and the equipment type of the target CNC equipment, the downtime cause corresponding to the downtime is determined according to a preset matching rule; wherein the matching rule includes the relationship between downtime, downtime cause and equipment type.

[0022] In one possible implementation of the first aspect, the statistical analysis results are presented using a Pareto chart.

[0023] Secondly, embodiments of this application provide a statistical analysis device for the shutdown status of CNC equipment, the device comprising: a unit for performing the steps of the method described in any of the embodiments of the first aspect above.

[0024] Thirdly, embodiments of this application provide a computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method as described in any of the embodiments of the first aspect above.

[0025] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program or instructions that, when read and executed by a computer, cause the computer to perform the steps of the method as described in any of the embodiments of the first aspect above.

[0026] Fifthly, embodiments of this application provide a computer program product that, when run on a server, causes the server to perform the steps of the method described in any of the embodiments of the first aspect above.

[0027] In a sixth aspect, embodiments of this application provide a chip, including: a processor, configured to call and run a computer program from a memory, causing a computer device on which the chip is installed to perform the method described in any of the embodiments of the first aspect above.

[0028] It is understood that the beneficial effects of the second to sixth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0029] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0030] Figure 1 This is a flowchart of a statistical analysis method for the shutdown status of CNC equipment provided in an embodiment of this application;

[0031] Figure 2 This is a schematic diagram of statistical analysis results in one embodiment of this application;

[0032] Figure 3 This is a flowchart of a method for obtaining downtime according to an embodiment of this application;

[0033] Figure 4This is a schematic diagram of a portion of a data entry stored in a computer device according to an embodiment of this application;

[0034] Figure 5 This is a structural block diagram of a statistical analysis device for the shutdown status of CNC equipment provided in an embodiment of this application;

[0035] Figure 6 This is a schematic diagram of the internal structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0036] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0037] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0038] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0039] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0040] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0041] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0042] Statistical analysis of CNC equipment downtime typically includes various causes of downtime and the lost time resulting from each cause. Based on this analysis, the primary causes of downtime loss can be identified, allowing users to address these issues and increase the effective uptime of the CNC equipment. Therefore, accurate statistical analysis of CNC equipment downtime is a crucial prerequisite for improving equipment operating efficiency.

[0043] The current statistical analysis process for CNC equipment downtime status is as follows: First, dedicated personnel observe the CNC equipment, recording the duration of various equipment states (e.g., downtime corresponding to each downtime state) and the reasons for each downtime state. Then, the recorded data is statistically analyzed to obtain the lost working hours caused by each different downtime reason. However, this current statistical analysis method, relying on dedicated personnel for equipment observation, results in excessively high labor costs. Furthermore, the data recorded by human observation is prone to inaccuracies, such as errors in status and time recordings. Inaccurate data inevitably leads to low accuracy in the analysis results, making it difficult to provide effective directions for improving equipment operation.

[0044] To address the aforementioned technical problems, this application provides a statistical analysis method for the downtime status of CNC equipment. By acquiring multiple downtime durations of the target CNC equipment within a specific time period, the method determines the downtime cause corresponding to each downtime duration, and analyzes and statistically analyzes all downtime durations and causes to obtain a statistical result. The statistical result shows the time loss corresponding to different downtime causes. This statistical analysis method can obtain downtime without requiring dedicated personnel to observe the equipment, avoiding inaccurate data recording due to subjective factors and thus achieving accurate recording of CNC equipment downtime. Furthermore, this method can accurately match downtime durations with downtime causes, thereby reducing labor costs and ensuring the accuracy of downtime analysis results for CNC equipment.

[0045] The statistical analysis method for CNC equipment downtime status in this application embodiment can be applied to various scenarios that require analysis of the causes of CNC equipment downtime. Specifically, this statistical analysis method can be applied to factories or production workshops with multiple CNC equipment, or it can also be applied to a section with one or more CNC equipment, etc., and this application embodiment does not impose any limitations.

[0046] Figure 1 The flowchart below illustrates a statistical analysis method for CNC equipment shutdown status according to an embodiment of this application. It should be understood that the executing entity of the statistical analysis method in this embodiment can be a computer device equipped with a CNC equipment management system, or other devices; for example, it can be a chip or a device with a program installed. The statistical analysis method in this application is executively described below using a computer device as the executing entity. Those skilled in the art will understand that this executing entity should not be construed as a limitation on the scope of protection of this application.

[0047] like Figure 1 As shown, the method may include S110 to S130. The following is in conjunction with... Figure 1 Each step is explained in detail.

[0048] Step S110: Obtain at least one downtime of the target CNC equipment within the target time period.

[0049] In some possible implementations, the target CNC machine is a monitored CNC machine. The target CNC machine can be a single, specific CNC machine or multiple CNC machines. When there are multiple target CNC machines, these machines can be of the same type or different types. Specifically, the target CNC machine can include all CNC machines in a workshop or all CNC machines in a factory.

[0050] In some implementations, the target time period can be the length of time between any two points in time for which data aggregation is required. Specifically, the target time period can be the length of time between any two points in history, such as a past month, quarter, or year; or the target time period can be the length of time from a certain point in history to the present time, such as a month, quarter, or year up to today.

[0051] In some embodiments, in order to prevent the amount of data for statistical analysis from being too large, an upper limit can be set for the length of the target time period, for example, the length of the target time period is less than or equal to 12 months.

[0052] In some implementations, a downtime specifically refers to the length of time between the start and end of a CNC machine's shutdown state. In other words, a downtime refers to the duration of a single shutdown of the CNC machine. For example, a downtime of 15 minutes indicates that the corresponding shutdown state lasted for 15 minutes.

[0053] Step S120: Determine the cause of downtime for each downtime duration.

[0054] In some embodiments, a corresponding downtime reason is determined for each downtime duration. Specifically, the downtime reason corresponding to any downtime duration can be determined according to a preset matching rule based on the equipment type of the target CNC equipment. Optionally, the matching rule can be generated based on historical production data.

[0055] For example, in one embodiment, the matching rules are shown in Table 1:

[0056] Table 1

[0057]

[0058]

[0059] The following uses different equipment types and different downtime durations as examples to illustrate Table 1:

[0060] (1) If the equipment type is CNC, the downtime is 25 minutes:

[0061] As shown in Table 1, the downtime for equipment type "CNC" and downtime of "25 minutes" is due to the reason for downtime: "CNC multi-axis electrode machining requires a long uptime".

[0062] (2) Electrical discharge machine tool, downtime is 25 minutes:

[0063] Table 1 shows that the equipment type is "EDM" and the downtime is "25 minutes". The corresponding downtime reason is "multiple workpieces in-machine edge finding (12)".

[0064] (3) When the downtime is greater than 60 minutes, the downtime reason for all equipment types is the same, which is the downtime reason corresponding to the "general scenario". For example, when the downtime is 70 minutes, the corresponding downtime reason is "the machine tools are completed at the same time and need to be installed one by one".

[0065] Step S130: Perform statistical analysis on all downtime durations and the downtime causes corresponding to each downtime duration, and obtain statistical analysis results, including the time loss corresponding to different downtime causes.

[0066] In this embodiment, time loss refers to the sum of all downtime caused by a certain type of downtime. The time loss for different downtime causes is statistically analyzed; a larger time loss indicates a greater impact of the corresponding downtime cause on the production efficiency of the CNC equipment. By statistically analyzing the time loss corresponding to different downtime causes, users can gain a more intuitive understanding of the factors affecting production efficiency.

[0067] In some possible implementations, the statistical analysis results are presented using Pareto charts.

[0068] Figure 2 This is a schematic diagram of the statistical analysis results in one embodiment of this application. Figure 2 The chart used is a Pareto chart, where the vertical axis represents the total lost time (i.e., lost labor hours), the horizontal axis represents the causes of downtime, and the points on the line represent the cumulative percentage. For example... Figure 2 As shown, the reasons for downtime are arranged according to the magnitude of the corresponding time loss, with the time loss corresponding to the downtime reasons on the left being greater than that corresponding to the downtime reasons on the right.

[0069] like Figure 2 As shown, the cumulative percentage corresponding to the first downtime reason, "insufficient operators leading to machine tool downtime," is 35.31%. This cumulative percentage represents the proportion of working hours lost due to the first downtime reason. Figure 2 The percentage of total lost working hours corresponding to all downtime reasons; the cumulative percentage corresponding to the second downtime reason, "no night shift personnel, machine tool downtime," is 64.24%. This cumulative percentage refers to the percentage of total lost working hours corresponding to the first and second downtime reasons combined. Figure 2 The percentage of total lost working hours corresponding to all causes of downtime. Figure 2 The other parts can be deduced by analogy according to the above rules, and will not be elaborated here.

[0070] Depend on Figure 2 As can be seen in the Pareto chart, the time lost due to downtime decreases gradually from left to right, meaning the importance of the downtime cause decreases from left to right. This arrangement allows users to identify the main downtime causes affecting work efficiency, thus guiding them to select the appropriate corrective measures. For example, Figure 2 The reason for the shutdown on the far left is "insufficient operators causing machine downtime". Therefore, users can prioritize equipping themselves with sufficient operators to reduce working hours and thus improve production efficiency.

[0071] The above-mentioned statistical analysis method for CNC equipment downtime does not require dedicated personnel to observe the equipment, and can accurately record the downtime of CNC equipment and accurately match the downtime cause with the downtime, thereby reducing labor costs and achieving accurate statistics and analysis of the downtime status of CNC equipment.

[0072] To ensure that the methods in this application can be clearly understood, the method for obtaining the downtime in step S120 is described below by way of example.

[0073] It should be understood that the execution subject of the downtime acquisition method in this application embodiment is the same as the execution subject of the statistical analysis method. The following description uses a computer device as the execution subject to illustrate the downtime acquisition method in this application. As an example and not a limitation, the execution subject of the downtime acquisition method can also be other devices, such as a chip or a device with a program installed.

[0074] like Figure 3 As shown, the methods for obtaining the downtime can include S310 to S320, which are described below in conjunction with... Figure 3 Each step is explained in detail.

[0075] Step S310: Obtain the equipment status of the target CNC equipment at multiple times within the target time period.

[0076] In some embodiments, a time refers to the moment when the device state is acquired; among multiple times, each time corresponds to a device state, and the device states corresponding to different times can be the same or different.

[0077] In some implementations, the device status can be stopped, running, or alarmed. In other implementations, the device status can also be offline, stopped, running, or alarmed.

[0078] In some possible implementations, after acquiring the device state and the corresponding time, the computer device stores the acquired device state and the corresponding time. Optionally, when storing the time and the corresponding device state, each time and the device state corresponding to that time can be recorded as a single data entry.

[0079] Figure 4 This is a schematic diagram illustrating a portion of a data entry stored in a computer device according to an embodiment of this application. Figure 4 In the embodiments shown, the device status is represented by device status numbers. Specifically, device status number "0" indicates offline status, device status number "10" indicates shutdown status, device status number "20" indicates running status, and device status number "30" indicates alarm status.

[0080] like Figure 4 As shown, the time corresponding to this data is "22-08-24 08:40:22", where "22-08-24" indicates that the time is August 24, 2022, and "08:40:22" indicates that the specific time is "08:40:22".

[0081] like Figure 4 The data shown includes the equipment status of three CNC machines at the time "22-08-24 08:40:22". Specifically, the equipment status number of CNC machine "CNC05" is "10", meaning CNC05 is stopped at that time; the equipment status number of CNC machine "CNC06" is "0", meaning CNC06 is offline at that time; and the equipment status number of CNC machine "CMM02" is also "0", meaning CMM02 is offline at that time.

[0082] In some embodiments, a computer device can acquire the device status of a target CNC device through an I / O signal acquisition device; wherein the I / O signal acquisition device may also be referred to as a network I / O module, an Ethernet I / O module, etc.

[0083] For example, the I / O signal acquisition unit can be installed in the control cabinet of the CNC equipment. In this case, the I / O signal acquisition unit is connected to the operating status indicator light of the target CNC equipment, and the computer equipment obtains the equipment status of the target CNC equipment by communicating with the I / O signal acquisition unit.

[0084] In some embodiments, to ensure communication between the I / O signal acquisition device and the computer device, the I / O signal acquisition device and the computer device can be connected to the same local area network. It is understood that the I / O signal acquisition device and the computer device can communicate in any possible manner; by way of example and not limitation, the I / O signal acquisition device and the computer device can communicate via a cellular network.

[0085] For example, the operating status indicator lights of the target CNC equipment can be three-color indicator lights, with the equipment status corresponding to the three different colored indicator lights being lit being running, stopped, and alarm, respectively. Optionally, the operating status indicator lights of the target CNC equipment can also be four-color indicator lights, with the equipment status corresponding to the four different colored indicator lights being lit being running, stopped, alarm, and offline, respectively.

[0086] In other embodiments, when the target CNC equipment has an open communication port or a preset communication protocol, the computer equipment can obtain the equipment status through the communication port on the target CNC equipment or the preset communication protocol. Specifically, the communication protocol can be the Transmission Control Protocol (TCP).

[0087] For example, computer equipment and target CNC equipment can be connected to the same local area network.

[0088] It is understood that computer equipment and target CNC equipment can communicate in any possible way. By way of example and not limitation, computer equipment and target CNC equipment can also communicate via cellular networks.

[0089] Step S320: Determine at least one downtime based on multiple time points and the corresponding equipment status at each time point.

[0090] In some embodiments, the downtime is determined by multiple moments and the corresponding device states at each moment, specifically by determining the duration of each downtime state in multiple downtime states.

[0091] For example, a method for determining downtime based on device status at multiple moments can be as follows: First, determine the first moment when all devices are in a downtime state from the multiple moments; then, determine the duration corresponding to consecutive first moments among all the first moments as a single downtime. If there are no device status records between adjacent first moments, the multiple first moments are considered consecutive. By grouping all the first moments according to their continuity, a group of consecutive first moments corresponds to a single downtime, allowing for accurate determination of the start and end times of a downtime state, thus providing an accurate downtime.

[0092] It is understandable that, among N consecutive first moments, the time difference between the earliest and latest first moment in time is the downtime corresponding to the N consecutive first moments.

[0093] In some possible implementations, the computer device periodically acquires the device status of the target CNC machine. Specifically, the computer device acquires the device status at preset time intervals. For example, the computer device acquires the device status at 5-second or 10-second intervals. In this case, the time difference between adjacent moments is 5-second or 10-second.

[0094] When a computer periodically acquires the status of a target CNC machine, if the difference between adjacent moments is equal to a preset duration, then the multiple moments are considered continuous. Similarly, for multiple first moments, if the difference between adjacent first moments is equal to a preset duration, then the multiple first moments are considered continuous.

[0095] For example, Table 2 records all the equipment statuses of CNC equipment CMM01 between "22-07-12 01:20:10" and "22-07-12 01:23:40". As shown in Table 2, a total of 23 equipment statuses of CNC equipment CMM01 were recorded during this time period. In Table 2, equipment status number "20" corresponds to the running status, and equipment status number "10" corresponds to the stopped status.

[0096] Table 2

[0097]

[0098]

[0099] As shown in Table 2, the equipment status at each time point between "22-07-12 01:20:20" and "22-07-12 01:23:10" is all in a shutdown state. Therefore, each time point between "22-07-12 01:20:20" and "22-07-12 01:23:10" is a first time point. That is, there are a total of 18 first times points in Table 2, and these 18 first times points are consecutive. Therefore, Table 2 corresponds to a shutdown duration, which is equal to the time difference between "22-07-12 01:20:20" and "22-07-12 01:23:10", that is, a shutdown duration of 170 seconds (i.e., 2 minutes and 50 seconds).

[0100] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0101] Corresponding to the statistical analysis method for the shutdown status of CNC equipment described in the above embodiments, Figure 5 This diagram illustrates the structural block diagram of a statistical analysis device for the shutdown status of CNC equipment provided in an embodiment of this application. For ease of explanation, only the parts relevant to the embodiment of this application are shown. (Refer to...) Figure 5 The statistical analysis device 500 for the shutdown state of the CNC equipment includes: an acquisition unit 501, a determination unit 502, and a statistical analysis unit 503.

[0102] The acquisition unit 501 is used to acquire at least one downtime of the target CNC equipment within a target time period;

[0103] The determination unit 502 is used to determine the shutdown reason corresponding to each downtime duration;

[0104] The statistical analysis unit 503 is used to perform statistical analysis on all downtime and the downtime causes corresponding to each downtime, and obtain statistical analysis results, including the time loss corresponding to different downtime causes.

[0105] Optionally, the acquisition unit 501 is used to acquire at least one downtime of the target CNC equipment within a target time period, specifically including:

[0106] Obtain the device status of the target CNC equipment at multiple moments within a target time period;

[0107] Determine at least one downtime based on multiple time points and the corresponding equipment status at each time point.

[0108] Optionally, the acquisition unit 501 is used to acquire the device status of the target CNC device at multiple times through the communication port on the target CNC device or a preset communication protocol, or through an I / O signal acquisition device connected to the target CNC device.

[0109] Optionally, the equipment status is either stopped, running, or alarmed; the acquisition unit 501 is used to determine at least one downtime based on multiple times and the corresponding equipment status at each time, specifically including:

[0110] All first moments are determined from multiple moments, and the equipment state corresponding to the first moment is the shutdown state;

[0111] The total time length corresponding to consecutive first moments is defined as a downtime.

[0112] Optionally, the determining unit 502 is used to determine the downtime cause corresponding to each downtime duration, specifically including: determining the downtime cause corresponding to any downtime duration and the equipment type of the target CNC equipment according to a preset matching rule; wherein the matching rule includes the relationship between downtime duration, downtime cause and equipment type.

[0113] Optionally, the statistical analysis results can be presented using a Pareto chart.

[0114] It should be understood that the specific process of each unit in the statistical analysis device 500 for the CNC equipment shutdown status performing the above-mentioned corresponding steps is described in the previous text regarding the statistical analysis method for the CNC equipment shutdown status. For the sake of brevity, it will not be repeated here.

[0115] One embodiment of this application also provides a computer device 600. For example... Figure 6 As shown, the computer device 600 of this embodiment includes: a processor 601, a memory 602, and a computer program 604 stored in the memory 602 and executable on the processor 601. The computer program 604 can be executed by the processor 601 to generate instructions 603, which the processor 601 can use to implement the steps in the various delivery address confirmation method embodiments described above. Alternatively, when the processor 601 executes the computer program 604, it implements the functions of each module / unit in the various device embodiments described above, for example... Figure 5 The functions of the acquisition unit 501 to the statistical analysis unit 503 are shown.

[0116] For example, computer program 604 may be divided into one or more modules / units, one or more of which are stored in memory 602 and executed by processor 601 to complete this application. One or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of computer program 604 in computer device 600.

[0117] Those skilled in the art will understand that Figure 6 This is merely an example of computer device 600 and does not constitute a limitation on computer device 600. Computer device 600 may include more or fewer components than shown, or combine certain components, or different components. For example, computer device 600 may also include input / output devices, network access devices, buses, etc.

[0118] Processor 601 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0119] The memory 602 can be an internal storage unit of the computer device 600, such as a hard disk or RAM of the computer device 600. The memory 602 can also be an external storage device of the computer device 600, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the computer device 600. Furthermore, the memory 602 can include both internal and external storage units of the computer device 600. The memory 602 is used to store computer programs and other programs and data required by the computer device 600. The memory 602 can also be used to temporarily store data that has been output or will be output.

[0120] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0121] This application also provides a computer-readable storage medium storing a computer program or instructions, which, when read and executed by a computer, causes the computer to perform the steps in the above-described method embodiments.

[0122] This application provides a computer program product that, when run on a server, enables the server to implement the steps described in the various method embodiments above.

[0123] This application also provides a chip, including: a processor, configured to call and run a computer program from a memory, causing a computer device on which the chip is installed to perform the steps as described in the various method embodiments above.

[0124] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0125] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0126] In the embodiments provided in this application, it should be understood that the disclosed apparatus / devices and methods can be implemented in other ways. For example, the apparatus / device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0127] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0128] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0129] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a device / server, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0130] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A statistical analysis method for the shutdown status of CNC equipment, characterized in that, include: Obtain at least one downtime of the target CNC equipment within the target time period; Determine the cause of downtime for each downtime duration; Statistical analysis is performed on all downtime durations and the downtime causes corresponding to each downtime duration to obtain statistical analysis results, including the time losses corresponding to different downtime causes. The step of obtaining at least one downtime of the target CNC equipment within a target time period includes: obtaining the equipment status of the target CNC equipment at multiple times within the target time period, wherein the equipment status is a downtime status, a running status, or an alarm status; and determining the at least one downtime based on the multiple times and the corresponding equipment status at each time period. The step of determining the at least one downtime based on the plurality of times and the corresponding device status at each time includes: determining all first times from the plurality of times, wherein the device status corresponding to the first time is a downtime state; determining the total time length corresponding to consecutive first times as a downtime, wherein the consecutive first times include a plurality of first times, and there is no record of any device status between adjacent first times in the plurality of first times; The step of determining the downtime cause corresponding to each downtime duration includes: determining the downtime cause corresponding to any downtime duration and the equipment type of the target CNC equipment according to a preset matching rule; wherein the matching rule includes the correlation between downtime duration, downtime cause and equipment type.

2. The method according to claim 1, characterized in that, The device status of the target CNC device at multiple times can be obtained through the communication port on the target CNC device or a preset communication protocol, or through an I / O signal acquisition device connected to the target CNC device.

3. The method according to claim 1 or 2, characterized in that, The statistical analysis results are presented using Pareto charts.

4. A statistical analysis device for the shutdown status of CNC equipment, characterized in that, The apparatus includes units for performing the various steps of the method as described in any one of claims 1 to 3.

5. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program or instructions that, when read and executed by a computer, cause the computer to perform the method as described in any one of claims 1 to 3.

7. A chip, characterized in that, include: A processor for retrieving and running a computer program from memory, causing a computer device on which the chip is installed to perform the method as described in any one of claims 1 to 3.

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