Equipment monitoring method, electronic equipment and computer readable storage medium

Abstract

The invention provides an equipment monitoring method, electronic equipment and a computer readable storage medium, and the method comprises the steps: monitoring the production related data of to-be-monitored equipment; wherein the production related data comprises planned working time, actual starting time and invalid working time in the production process; determining effective starting time based on the actual starting time and the invalid working time; and based on the effective starting time, the planned working time and the actual starting time, determining the equipment comprehensive efficiency of the to-be-monitored equipment. Through the method, the determined comprehensive efficiency of the equipment can better represent the actual condition of the to-be-monitored equipment.

Description

Technical Field

[0001] This application relates to the field of production equipment monitoring technology, and more specifically, to an equipment monitoring method, electronic device, and computer-readable storage medium. Background Technology

[0002] Currently, existing technical solutions for overall equipment efficiency mainly fall into two categories: those that access a single device control system through simple serial communication and can only display the preset calculation results of overall equipment efficiency (such as a single value or basic text prompts), and those that rely on manual data entry for data collection, which limits the data sources and makes it impossible to accurately represent the actual situation of the equipment to be monitored. Summary of the Invention

[0003] The purpose of this application is to provide a device monitoring method, electronic device, and computer-readable storage medium that enable the determined overall device efficiency to better characterize the actual situation of the device under monitoring.

[0004] In a first aspect, the present invention provides an equipment monitoring method, comprising: monitoring production-related data of the equipment to be monitored; wherein the production-related data includes planned working time, actual operating time, and ineffective working time during production; determining effective operating time based on the actual operating time and the ineffective working time; and determining the overall equipment efficiency of the equipment to be monitored based on the effective operating time, the planned working time, and the actual operating time.

[0005] In the above implementation method, the overall efficiency of the equipment is not simply determined based on the start-up and shutdown time of the equipment. Instead, it combines the determined start-up time of the equipment with relevant production data to determine the ineffective working time. This allows the determined overall efficiency of the equipment to better represent the actual efficiency of the equipment under monitoring.

[0006] In an optional implementation, the invalid working time includes the fault loss time, performance loss time, and quality loss time of the monitored equipment; determining the effective working time based on the actual operating time and the invalid working time includes: determining the effective working time based on the actual operating time, the quality loss time, the fault loss time, and the performance loss time.

[0007] In the above implementation method, there may be a variety of reasons that cause the work to be ineffective in actual execution. The effective start-up time can be determined by combining various failure loss time, performance loss time, and quality loss time. This can reduce the situation where some actual equipment is started but does not form an effective working state.

[0008] In an optional implementation, the method further includes: determining a net uptime based on the actual uptime and the performance loss time; determining the overall equipment efficiency of the device under monitoring based on the effective uptime, the planned working time, and the actual uptime, including: determining a time utilization rate based on the planned working time and the actual uptime; determining the yield of the device under monitoring based on the effective uptime and the net uptime; determining the performance efficiency of the device under monitoring based on the net uptime and the actual uptime; and determining the overall equipment efficiency of the device under monitoring based on the time utilization rate, the yield, and the performance efficiency.

[0009] In the above implementation method, the time utilization rate, yield and performance efficiency can be determined by combining various types of start-up time, so as to realize the efficiency of the equipment from various dimensions, and also to gain a more comprehensive understanding of the status of the equipment under monitoring.

[0010] In an optional implementation, the production-related data includes shutdown fault status, non-shutdown status, effective production status, and ineffective production status; monitoring the production-related data of the equipment to be monitored includes: monitoring the status information of the equipment to be monitored, and the duration of each status; wherein, the status information includes pause status, fault status, and running status; determining shutdown fault status and non-shutdown status from the fault status; wherein, the duration corresponding to the shutdown fault status is determined as fault loss time; determining effective production status and ineffective production status from the running status; wherein, the duration corresponding to the ineffective production status is determined as performance loss time.

[0011] In an optional implementation, the method further includes: updating the overall efficiency of the device according to a set time pattern within a monitoring cycle; and determining the efficiency change trend of the device to be monitored based on the updated overall efficiency of the device according to the set time pattern.

[0012] In the above implementation method, the overall efficiency of the equipment and the changes of the monitored equipment according to the set time pattern can also be determined according to the set time pattern.

[0013] In an optional implementation, the method further includes: determining the equipment cycle time of the device to be monitored based on the efficiency change trend; and generating a performance report of the device to be monitored based on the efficiency change trend and the equipment cycle time.

[0014] In an optional implementation, the method further includes: outputting and displaying a device performance change graph based on the production-related data and the efficiency change trend; wherein the device performance change graph is presented in one or more ways, such as a bar chart or a pie chart.

[0015] The above implementation method can present the monitored equipment through performance reports or visual graphs, allowing users to understand the monitored equipment more intuitively.

[0016] In an optional implementation, the device is applied to a display device, and the device performance change graph includes one or more of the following: utilization rate analysis graph, device status analysis graph, comparison analysis graph with similar devices, cycle time analysis graph, fault detail analysis graph, abnormal data graph, and detail table; the output and display of the device performance change graph includes: displaying one or more of the following controls: utilization rate analysis control, device status analysis control, comparison analysis graph with similar devices, cycle time analysis control, fault detail analysis control, abnormal data control, and detail table control; in response to an operation on any one of the following controls: utilization rate analysis control, device status analysis control, comparison analysis graph with similar devices, cycle time analysis control, fault detail analysis control, abnormal data control, and detail table control, displaying the graph corresponding to the operation trigger.

[0017] In a second aspect, the present invention provides an electronic device, comprising: a processor and a memory, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the machine-readable instructions are executed by the processor to perform the steps of the method described in any of the foregoing embodiments.

[0018] Thirdly, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, performs the steps of the method described in any of the foregoing embodiments.

[0019] Fourthly, the present invention provides a computer program product, the computer program product comprising a computer program, which, when executed by a processor, implements the method described in any one of the foregoing embodiments. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1A block diagram illustrating an electronic device provided in an embodiment of this application; Figure 2 This is a schematic diagram of the device evaluation data model within a monitoring cycle provided in an embodiment of this application; Figure 3 A flowchart of the device monitoring method provided in the embodiments of this application; Figure 4 This is a schematic diagram illustrating the changing trend of the overall equipment efficiency provided in the embodiments of this application; Figure 5 A schematic diagram illustrating the time utilization rate of multiple monitoring devices provided in the embodiments of this application; Figure 6 A schematic diagram of a display panel for device performance provided in an embodiment of this application; Figure 7 This is a schematic diagram illustrating the device status details provided in an embodiment of this application. Detailed Implementation

[0022] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0023] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0024] With the deepening of intelligent manufacturing, the automation level and heterogeneity of production equipment have significantly improved, making enterprises increasingly demanding quantitative monitoring and performance optimization of Overall Equipment Efficiency (OEE). Existing technologies primarily build OEE monitoring and analysis systems around a three-tiered "edge-cloud" architecture, mainly addressing the issues of data collection, OEE calculation and analysis, and performance status visualization for production equipment. These systems are suitable for production line equipment management in various industries, including precision manufacturing, rubber and plastics production, and home appliance manufacturing. OEE dashboards are visualization tools used in industrial production scenarios to display real-time equipment operating efficiency, production progress, and related core indicators. They are widely used in manufacturing production lines and automated workshops, and their core value is helping relevant personnel quickly grasp the production status and optimize production processes. OEE dashboards are key tools in industrial production scenarios for displaying real-time equipment operating efficiency, production progress, and related core indicators, and are widely used in manufacturing production lines and automated workshops.

[0025] Existing OEE dashboard technical solutions mainly fall into two categories: traditional hardware dashboards and basic software visualization dashboards. Traditional hardware dashboards mostly use fixed display modules (such as LED dot matrix screens) and connect to a single device control system via serial communication. They can only display preset OEE calculation results (such as single numerical values ​​or basic text prompts), and data collection relies on manual input or access to a single device interface, limiting the data sources. Basic software visualization dashboards are mostly based on PCs or simple touch screens, with long data update cycles, lack of real-time performance, and inability to adapt to the personalized needs of different industries (such as automobile manufacturing, electronic component assembly, and food processing). The existing technology has the following core defects: (1) Weak data acquisition capability: It only supports a single device interface or manual input, which makes data input and upload troublesome, forming data silos and resulting in inaccurate OEE calculation base; (2) Insufficient real-time performance: Data processing relies on centralized calculation on cloud or local servers, resulting in high transmission and processing delays, making it impossible to achieve second-level data updates and affecting timely response to abnormal situations; (3) Poor adaptability: The OEE calculation rules (weights and statistical logic of the three core indicators of availability, performance, and quality) are fixed, there is no clear OEE calculation formula, and the calculation rules are not uniform across different fields. It is impossible to customize the configuration according to the process characteristics of different industries and production lines; (4) It can passively display the calculation results, but cannot perform trend analysis, fault prediction, or production bottleneck identification on historical data, and lacks the ability to actively optimize and guide; (5) Usually, the OEE dashboard is only a local dashboard, which cannot achieve synchronous viewing and remote control on mobile phones, computers, and tablets, and has limited adaptability.

[0026] Based on the above research, embodiments of this application can provide a device monitoring method, electronic device, and computer-readable storage medium that can enable the determined overall device efficiency to better characterize the actual situation of the device under monitoring.

[0027] To facilitate understanding of this embodiment, the electronic device that performs the device monitoring method disclosed in this application will first be described in detail.

[0028] like Figure 1 The diagram shown is a block illustration of an electronic device. The electronic device 100 may include a memory 111, a processor 113, and a display unit 115. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the electronic device 100. For example, the electronic device 100 may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0029] The memory 111, processor 113, and display unit 115 described above are electrically connected to each other directly or indirectly to achieve data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines. The processor 113 is used to execute executable modules stored in the memory.

[0030] The memory 111 can be, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), etc. The memory 111 stores programs, and the processor 113 executes these programs upon receiving execution instructions. The methods executed by the electronic device 100 as defined in any embodiment of this application can be applied to the processor 113, or implemented by the processor 113.

[0031] The aforementioned processor 113 may be an integrated circuit chip with signal processing capabilities. The processor 113 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a digital signal processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor may be a microprocessor or any conventional processor.

[0032] The aforementioned display unit 116 provides an interactive interface (e.g., a user interface) between the electronic device 100 and the user, or displays image data for the user's reference. In this embodiment, the display unit can be a liquid crystal display (LCD) or a touch display. If it is a touch display, it can be a capacitive touchscreen or a resistive touchscreen that supports single-point and multi-point touch operations. Supporting single-point and multi-point touch operations means that the touch display can sense touch operations generated simultaneously from one or more locations on the touch display and pass the sensed touch operations to the processor for calculation and processing. In the device monitoring method provided in this application embodiment, the display unit 116 can be used to display data collected or calculated by the monitored device during the production process, such as production-related data and overall equipment efficiency.

[0033] The electronic device 100 in this embodiment can be used to execute various steps in the various methods provided in the embodiments of this application. The implementation process of the device monitoring method is described in detail below through several embodiments.

[0034] To better understand the implementation of the equipment monitoring method provided in the embodiments of this application, this application first constructs a relevant evaluation data model and a calculation model for the overall equipment efficiency for implementing the equipment monitoring method: Equipment overall efficiency reflects the actual production value of the equipment. This application's embodiments calculate and evaluate it from a time perspective. Equipment overall efficiency is determined based on the division of equipment operating time, establishing an evaluation data model that conforms to the objective reality of the equipment, and further subdividing the time elements. For example... Figure 2 The diagram shown illustrates a data model for device evaluation within a monitoring period. Figure 2 The evaluation data model shown can divide a monitoring cycle into multiple time periods based on the actual working conditions of the equipment.

[0035] exist Figure 2The diagram illustrates a monitoring cycle represented as Calendar Time (CT), Planned Operating Time (AWT), the time period within Calendar Time (CT) excluding Planned Operating Time (AWT) is Planned Downtime (SD), Equipment Load Time (SOT), the time period within Planned Operating Time (AWT) excluding Equipment Load Time (SOT) is Temporary Downtime (TD), Potential Start-up Time (LRT), the time period within Equipment Load Time (SOT) excluding Potential Start-up Time (LRT) is Connection Loss Time (CLT), Actual Start-up Time (ART), the time period within Potential Start-up Time (LRT) excluding Actual Start-up Time (ART) is Failure Loss Time (FLT), Net Start-up Time (NRT), the time period within Actual Start-up Time (ART) excluding Net Start-up Time (NRT) is Performance Loss Time (PLT), Effective Start-up Time (VRT), and the time period within Net Start-up Time (NRT) excluding Effective Start-up Time (VRT) is Quality Loss Time (QLT).

[0036] Planned downtime (SD) can include non-working periods such as annual equipment maintenance, scheduled repairs, holidays, and production line maintenance. Planned downtime (SD) can also include downtime caused by unforeseen circumstances such as earthquakes or municipal power outages. Planned downtime (SD) can also include periods when the production line is closed.

[0037] Temporary downtime (TD) can include periods such as production line audits, production line visits, production line training, first-piece inspections, and equipment quality checks during production. Of course, depending on the actual production line, temporary downtime can also include downtime caused by other reasons.

[0038] Connection loss time (CLT) can include the time periods for actions such as production line changeover, production line cleaning, and production line setup. Of course, depending on the actual production line, connection loss time can also include other elements.

[0039] Failure time (FLT) can include the time spent on equipment failure repairs, unplanned maintenance, and upkeep. Of course, depending on the actual production line, failure time can also include other failure scenarios.

[0040] Performance loss time (PLT) can include periods of insufficient production line cycle time and production line slowdown.

[0041] Quality loss time (QLT) can include the time that defective products occupy during the production process.

[0042] The monitoring cycle can be chosen differently in different use cases. Specifically, the appropriate monitoring cycle can be selected based on the actual use case. For example, the monitoring cycle can be a day, a week, a month, etc.

[0043] In this embodiment of the application, the overall equipment efficiency can be an indicator composed of the time utilization rate, performance efficiency and yield of the working unit, namely: OEE=Ava×PE×RQP; where Ava represents the time utilization rate; PE represents the performance efficiency; and RQP represents the yield.

[0044] The time utilization rate can be expressed as the ratio between actual operating time (ART) and planned working time (AWT), expressed as: Ava = ART / AWT, where ART represents actual operating time and AWT represents planned working time.

[0045] like Figure 2 As can be seen from the evaluation data model shown, AWT = CT – SD; CT represents calendar time; SD represents planned downtime.

[0046] For example, planned downtime can also refer to the planned downtime within a shift on the production line. Planned downtime within a shift can be maintained by relevant personnel, such as manufacturing staff within the production line.

[0047] The actual start-up time can be expressed as: ART = AWT - FLT - CLT - TD; where FLT represents the failure loss time; CLT represents the connection loss time; and TD represents the temporary downtime.

[0048] In actual production line monitoring, the actual operating time can be expressed as the running time minus the time when the equipment cannot operate normally, such as when there is no material, insufficient material, or full material. That is, the actual operating time equals the equipment running time minus the waiting time and material blockage time during operation.

[0049] Performance efficiency can be expressed as the relationship between the planned target cycle time and the actual cycle time. The formula for calculating performance efficiency is: PE = NRT / ART, where NRT represents net uptime. Performance efficiency can also be expressed as PQ / (PPM × ART); where PQ represents the production quantity and PPM represents the design cycle time.

[0050] Production quantities can be obtained from the Manufacturing Operations Management System (MOM). The production quantity includes the total number of finished products leaving the station (including defective products, and must include all input products for processing).

[0051] The design cycle time can be a pre-configured parameter, or a value designed based on relevant technical issues. The design cycle time can represent the planned quantity of products to be produced per unit of time.

[0052] Yield is the ratio of effective uptime (VRT) to net uptime (NRT), and also the ratio of qualified products (GQ) to production quantity (PQ), expressed as: RQP = VRT / NRT; where RQP represents yield; VRT represents effective uptime; and NRT represents net uptime.

[0053] Based on the calculation logic for the above-mentioned time uptime, performance efficiency, and yield, we can determine that: OEE = VRT / AWT. Overall equipment efficiency can also be expressed as the ratio of qualified products (GQ) to designed output. That is, OEE also represents the ratio of effective uptime (VRT) to planned working time (AWT) of a machine unit, and also represents the ratio of qualified products to designed output.

[0054] For different use cases, Figure 2 The actual content in the evaluation data model shown may differ. If the equipment monitoring method provided in the embodiments of this application is required, it can be configured based on the actual production line. Figure 2 The actual content in the evaluation data model shown.

[0055] The following is combined with Figure 3 This application introduces a device monitoring method provided by an embodiment. This device monitoring method can be applied to electronic devices, which then execute the steps of the device monitoring method. The implementation of the device monitoring method provided by this application utilizes the previously described evaluation data model and calculation model.

[0056] The following will be about Figure 3 The specific process shown will be explained in detail.

[0057] Step 210: Monitor the production-related data of the equipment to be monitored.

[0058] The production-related data includes planned working hours and actual start-up times. The planned working hours and actual start-up times in this data can be operational data related to the equipment being monitored, configured by relevant technical personnel. Examples include planned working hours and the actual start-up or shutdown times of the monitored equipment. Based on the planned working hours and actual start-up times, the start-up time of the monitored equipment can be determined.

[0059] Within a monitoring period, the time excluding planned working hours can be defined as planned downtime. Planned downtime can include: daily fixed shift handover downtime, equipment cleaning and inspection time, and temporary planned downtime. The planned working hours and planned downtime can be data input by the user.

[0060] The device to be monitored can be one device or multiple devices. Multiple devices can belong to one production line or multiple production lines.

[0061] Production-related data includes ineffective working time during the production process. This data can be included within the production process itself. For example, sudden shutdowns or ineffective production states caused by unforeseen circumstances mean that even if the monitored equipment is running, it cannot generate actual effective production.

[0062] Step 230: Determine the effective operating time based on the actual operating time and the ineffective operating time.

[0063] For example, the effective operating time can be determined by directly subtracting the ineffective working time from the actual operating time.

[0064] Step 250: Determine the overall equipment efficiency of the equipment to be monitored based on the effective operating time, planned operating time, and actual operating time.

[0065] For example, the formula for calculating the overall equipment efficiency can be expressed as: effective operating time divided by planned working time. Alternatively, the formula can be expressed as: effective operating time divided by actual working time.

[0066] By calculating the effective operating time from multiple dimensions, and determining the actual planned working time and actual operating time, the overall efficiency of the equipment can be comprehensively calculated. This allows the determined overall efficiency of the equipment to better represent the actual situation of the equipment under monitoring, and also makes it easier for relevant personnel to understand the status of the equipment under monitoring more intuitively and clearly.

[0067] In this embodiment, the aforementioned invalid working time may include the time of failure loss, performance loss, and quality loss of the monitored equipment.

[0068] Step 230 above may include: determining the effective operating time based on the actual start-up time, quality loss time, failure loss time, and performance loss time.

[0069] Failure time loss can be based on monitoring production-related data during the production process of the equipment under monitoring, such as fault alarms and the repair time of the equipment under monitoring after a fault alarm.

[0070] For example, the time when the monitored device switches to non-automatic operation due to a fault alarm is recorded as the fault time.

[0071] In some cases, although the monitored equipment may trigger a fault alarm, if the alarm is a non-shutdown fault alarm, it can be removed from the fault time and not included in the fault loss time and fault statistics.

[0072] Optionally, a non-fault filter list can be pre-defined to remove some non-downtime faults, improving the accuracy of fault loss time recording. Faults that do not affect equipment operation, such as fan alarms and electrical cabinet temperature alarms, can be deleted.

[0073] In this embodiment, production-related data includes shutdown fault status, non-shutdown status, effective production status, and ineffective production status.

[0074] Step 210 above may include monitoring the status information of the equipment to be monitored, as well as the duration of each status; determining the shutdown fault status and the non-shutdown status from the fault status; and determining the effective production status and the ineffective production status from the operating status.

[0075] The status information includes paused status, fault status, and running status; the duration of the shutdown fault status is determined as the fault loss time; the duration of the non-effective production status is determined as the performance loss time.

[0076] Optionally, production-related data can be recorded by the equipment being monitored itself. Data such as operating status (shutdown / outlet blockage / no material stop / standby), production count, and runtime can be transmitted from the programmable logic controller (PLC) connected to the monitored equipment to the manufacturing operations management system.

[0077] After the data is uploaded to the manufacturing operations management system, the system can record and deduplicate the transmitted production-related data. Optionally, the manufacturing operations management system can also transmit the acquired data to a server, where the server will clean and verify the data.

[0078] The time data uploaded to the server can be divided into three categories: (1) planned downtime (that is, the time outside the planned working time in the monitoring cycle in the production-related data obtained in step 210); (2) waiting time and blockage time of the equipment to be monitored; (3) equipment status time. The server can process the obtained data as follows: Step 310: Obtain the planned downtime and deduplicate the planned downtime to obtain the updated planned downtime.

[0079] The processing of planned downtime includes: standardizing the format and verifying the validity of various manually entered planned downtime times to ensure that the time intervals are clear and there are no logical conflicts, and obtaining the processed planned downtime times.

[0080] Step 320: Obtain the waiting time and blockage time of the equipment to be monitored, and perform deduplication on the waiting time and blockage time to obtain the updated waiting time and updated blockage time.

[0081] The data source for the waiting time and blockage time of the monitored equipment can be the data transmitted from the programmable logic controller of the monitored equipment to the manufacturing operations management system. The waiting time and blockage time of the monitored equipment are determined as follows: First, determine the time of each state of the monitored equipment, and then determine the four equipment states of the monitored equipment—shutdown state, paused state, fault state, and running state—through production-related data.

[0082] Production-related data includes manual operation pause signals, which can also be recorded as pause or standby time.

[0083] Preprocessing for the waiting time and blockage time of the equipment to be monitored includes: initial deduplication (removing duplicate records) of the waiting time and blockage time collected from the equipment to be monitored, and timestamp calibration to remove records with duplicate times.

[0084] Step 330: Perform deduplication based on the update plan downtime, update waiting time, and update blockage time.

[0085] The preprocessing for waiting time and blockage time of the monitored equipment also includes removing waiting time and blockage time during downtime. Furthermore, logical operations are performed on the processed planned downtime, waiting time, and blockage time to identify and remove waiting time and blockage time occurring within the planned downtime, thus avoiding duplicate counting of ineffective running time, reducing subsequent computational load, and outputting the processed time dataset.

[0086] Step 340: Obtain the operating status of the equipment to be monitored, and determine the ineffective production time of the equipment under the operating status by processing the waiting time and blocking time of the equipment under the operating status.

[0087] For example, the time corresponding to the running state can be identified with the waiting time and the blocking time to determine the overlap time between the time corresponding to the running state and the waiting time, as well as the overlap time between the time corresponding to the running state and the blocking time.

[0088] For example, the server can perform separate aggregation processing according to time interval and device number to extract the ineffective production time in the running state.

[0089] Step 350: The server can determine the time records of four non-operational states from the production-related data: equipment failure, shutdown, manual stop, and pause, and merge them to determine the non-operational state time.

[0090] Step 360: Deduplicate the above-mentioned non-operational time and planned downtime to determine the updated non-operational time.

[0091] Overall equipment efficiency can be expressed as the ratio of effective production time during operation to the time within a monitoring cycle excluding downtime for update plans.

[0092] The above processing steps can make the determined data more effective and the calculated overall equipment efficiency more accurate.

[0093] The equipment monitoring method in this embodiment may further include: step 220, determining the net operating time based on the actual operating time and performance loss time.

[0094] For example, the actual start-up time can represent the time period during which the monitored device is in the start-up state.

[0095] Step 250 above may include: Step 271, determining the time utilization rate based on the planned working time and the actual start-up time.

[0096] For example, the time utilization rate of the monitored equipment can be expressed as the ratio of actual operating time to planned operating time.

[0097] Step 272: Determine the yield of the equipment to be monitored based on the effective operating time and net operating time.

[0098] For example, the yield of the device to be monitored can be expressed as the ratio of effective uptime to net uptime.

[0099] Step 273: Determine the performance efficiency of the equipment to be monitored based on the net operating time and the actual operating time.

[0100] For example, the performance efficiency of the device under monitoring can be expressed as the ratio of net uptime to actual uptime.

[0101] Step 274: Determine the overall equipment efficiency of the equipment to be monitored based on time utilization rate, yield rate, and performance efficiency.

[0102] For example, the overall equipment efficiency of the device to be monitored can be determined by multiplying the time utilization rate, yield rate, and performance efficiency.

[0103] The device monitoring method in this application embodiment may include steps 261 and 262.

[0104] Step 261: Within a monitoring cycle, update the overall efficiency of the equipment according to the set time pattern.

[0105] A monitoring cycle can be a pre-set time period. For example, the monitoring cycle can be determined according to the operating patterns of the equipment being monitored. For instance, it can be the total time required to complete a batch of production. Alternatively, the monitoring cycle can be determined according to the operating patterns of the production line where the equipment is located; for example, a monitoring cycle can be a day, a week, or other durations.

[0106] Setting a time pattern can be a pre-set time pattern for updating the overall efficiency of the equipment, such as updating every five minutes or every hour on the hour.

[0107] Step 262: Based on the overall equipment efficiency updated according to a set time pattern, determine the efficiency change trend of the equipment to be monitored.

[0108] Efficiency change trends include the overall change trend of equipment efficiency within a monitoring cycle.

[0109] Optionally, this efficiency trend can be presented as a two-dimensional curve or as a data table.

[0110] The device monitoring method in this application embodiment may include steps 271 and 272.

[0111] Step 271: Determine the equipment cycle time of the equipment to be monitored based on the efficiency change trend.

[0112] For example, the equipment cycle time can represent the number of products produced by the monitored equipment per unit of time.

[0113] Step 272: Based on the efficiency change trend and equipment cycle time, generate a performance report for the equipment to be monitored.

[0114] Performance reports can include changes in efficiency at different points in time during the monitoring period.

[0115] For example, the performance report may also include the distribution of the acquired production-related data.

[0116] For example, the performance report may also include changes in time utilization, yield, and performance efficiency over the monitoring period.

[0117] For example, the performance report may also include analysis results on efficiency change trends. The analysis results may include specific time periods such as peak points and low points of overall equipment efficiency. The analysis results may also include stable periods of overall equipment efficiency. Stable periods can represent periods where overall equipment efficiency changes relatively little.

[0118] For example, the performance report may also include the difference between the equipment cycle time and the preset design cycle time. The difference between the equipment cycle time and the preset design cycle time can be represented by the number of products per unit time, or by the difference in the number of products over the entire monitoring period.

[0119] The equipment monitoring method in this application embodiment may include: step 273, outputting and displaying a graph of equipment performance changes based on production-related data and efficiency change trends.

[0120] The presentation of equipment performance change graphs includes one or more of the following: bar charts and pie charts.

[0121] Equipment performance change graphs can include trend graphs of changes in overall equipment efficiency. For example... Figure 4 As shown, this diagram illustrates the trend of overall equipment efficiency from December 3rd to December 11th. Filtering by time reveals a trend chart of the overall equipment efficiency for the monitored equipment. This trend chart more accurately reflects the overall efficiency of the monitored equipment, allowing for comparison of data across different time periods and identification of efficiency change patterns. By comparing this trend chart with the overall equipment efficiency trend chart, it becomes clear that the overall equipment efficiency can quickly reflect inefficient production conditions.

[0122] Equipment performance variation graphs can include time utilization rate variation graphs, such as... Figure 5 As shown, it illustrates the time utilization rate of multiple monitoring devices. Figure 5 The diagram shows the time utilization rate presented by production line, which allows for the identification of efficiency differences between various production lines, enabling further cross-sectional comparisons to identify problems, pinpoint root causes, and facilitate solutions. Figure 5 The example shown illustrates the time utilization rates of six production lines (such as C1-1, C1-2, C2-1, C2-2, C3-1, and C3-2).

[0123] For example, the device performance variation graph can be displayed using a dedicated display device. This dedicated display device can be an OEE dashboard. The OEE dashboard can be equipped with multiple buttons for switching between different displayed content.

[0124] This display device can communicate with a server and display device performance change graphs according to a preset format. It can also display data obtained from the server, specifically data calculated by the server based on production-related data of the monitored equipment.

[0125] The display interface of the display device can include production line information and time information. For example... Figure 6 As shown, equipment performance change charts can include various content. These include one or more of the following: utilization rate analysis chart, equipment status analysis chart, comparative analysis chart with similar equipment, cycle time analysis chart, fault detail analysis chart, abnormal data chart, and detail table.

[0126] The OEE dashboard can display controls for utilization rate analysis, equipment status analysis, comparison analysis with similar equipment, cycle time analysis, fault details analysis, abnormal data, and detail tables. For example, each control can be a touch button. Figure 6 The system displays touch buttons for utilization rate analysis, equipment status analysis, comparative analysis of similar equipment, cycle time analysis, fault details analysis, abnormal data, and detailed tables. When a switch button is triggered, the corresponding content can be displayed in the display area Vp.

[0127] In this embodiment, the OEE dashboard can also include filter menus. Filtering conditions can include: equipment model, production line, time, and viewable data content. For example, when only the model is filtered, detailed data for all monitored equipment of that model can be displayed. Viewable data content can include data obtainable from the OEE dashboard, such as: production-related data, overall equipment efficiency, time utilization rate, yield, and performance efficiency. Viewable data content can also include data extracted during processing, such as material shortage time, material waste time, full material time, and fault data.

[0128] Utilization rate analysis can include the utilization rate of each monitoring device and the utilization rate of each production line. The utilization rate of each monitoring device can be displayed in a preset manner, such as displaying it as a numerical value or as a bar chart. The utilization rate of each production line can also be displayed in a preset manner.

[0129] Equipment status analysis can include presenting a detailed equipment status diagram, in Figure 6 In the example shown, after the device status analysis button is touched, the following can be displayed: Figure 7The interface shown uses different colors to represent different states. Specific states include manual shutdown (orange box), outlet blockage (yellow box), standby (dark blue box), material shortage shutdown (blue-green box), planned shutdown (gray box), equipment malfunction (red box), running status (green box), and inlet waiting for material (cyan box). Figure 7 As shown, it illustrates a schematic diagram of the status time details of various devices in the same production line in an example, where the horizontal axis is the time axis and the vertical axis represents each monitoring device.

[0130] Comparative analysis of similar equipment can include changes in various data points for the same type of equipment. Equipment performance change graphs can also include graphs showing differences in overall equipment efficiency, time utilization rate, yield rate, and performance efficiency for similar equipment.

[0131] Cycle analysis can include the results of a comparative analysis of the design cycle time and the equipment cycle time. It can be presented in a preset manner.

[0132] Fault details analysis can include specific information about the fault, such as the fault type, the time of the fault, and the downtime caused by the fault.

[0133] Abnormal data can include relevant information about anomalies in the monitored equipment. This data may include the time, details, and duration of the anomaly. Anomalies can be those that cause downtime or those that do not.

[0134] The detailed list can include all data from the device to be monitored.

[0135] Optionally, the data presentation can be made more comprehensive, or more selective. The OEE dashboard can also be set with a filter menu, which can summarize various types of data based on shift, day, or month.

[0136] In this embodiment, not only the output... Figure 6 The form shown also includes a manually filled-out downtime cause management form. The dashboard can also categorize and summarize downtime, making it easier to identify the cause of low uptime.

[0137] The issue management table can be determined based on downtime data input by the user. This downtime data can include information such as the downtime reason, downtime, affected device, frequency of occurrence, issue severity, and associated personnel. Of course, the content of this issue management table can vary depending on the actual usage scenario, and should be set according to the specific information needed. For example, the issue management table can also include corresponding solutions, the reasons that triggered the problem, and chain reactions. Chain reactions indicate whether a particular problem will trigger other problems.

[0138] Of course, depending on the actual needs, the equipment performance variation chart can include more information.

[0139] In this embodiment, the OEE dashboard can synchronize the time periods of the various states of the equipment and the production count and good product quantity data required for calculation, and then calculate and display the utilization rate, performance efficiency, yield rate and final overall equipment efficiency according to the pre-configured OEE calculation model and the production-related data of the equipment to be monitored. At the same time, the types of unplanned downtime are broken down in detail during data statistics (such as fault downtime, changeover downtime, and material waiting downtime), and the proportion of each type is statistically analyzed, so that the data presented on the OEE dashboard can be more comprehensive.

[0140] With comprehensive data presentation, relevant personnel can more easily improve overall equipment efficiency based on the defects displayed in the OEE dashboard. By analyzing the evaluation results obtained from the OEE dashboard through different dimensions and methods, shortcomings can be accurately identified, and effective improvement measures can be formulated, continuously improving equipment operating efficiency and management level. The OEE algorithm is continuously updated and optimized based on actual conditions to ensure that OEE evaluation results accurately reflect the actual production situation on the production line, guiding effective improvement activities.

[0141] Based on the data output from the OEE dashboard, a multi-dimensional analysis model encompassing "time, product, organization, region, and equipment" is constructed. This model not only supports changes in time and equipment but also presents basic combinations such as changes in time, production line, shift, region, equipment, and status, quickly extracting core data for the required monitoring scenarios. Furthermore, it enables multi-perspective cross-analysis through "vertical trends + horizontal comparisons," uncovering efficiency bottlenecks and optimization opportunities from different dimensions, overcoming the limitations of existing technologies' "single-dimensional display." Vertical comparisons generate historical OEE trend curves for equipment, comparing data from different time periods to identify patterns in efficiency changes (such as the monthly OEE trend of a specific piece of equipment or the time trend of a fault cause). Horizontal comparisons are also supported, allowing for time-based comparisons of the status of similar equipment across multiple production lines and efficiency comparisons of different equipment on the same production line, quickly pinpointing production bottlenecks.

[0142] Filtering by time allows us to see the OEE trend chart for a specific piece of equipment. This OEE trend chart better reflects the overall efficiency of the equipment, generating a historical OEE trend curve. By comparing data from different time periods, we can identify patterns in efficiency changes. Comparing the OEE trend chart with the historical OEE trend chart clearly shows that OEE can quickly reflect inefficient production situations.

[0143] Furthermore, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the device monitoring method described in the above method embodiments.

[0144] The computer program product of the device monitoring method provided in this application includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the steps of the device monitoring method described in the above method embodiments. For details, please refer to the above method embodiments, which will not be repeated here.

[0145] In the several embodiments provided in this application, it should be understood that the disclosed methods can also be implemented in other ways. The method embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of methods and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0146] In addition, the method steps in the various embodiments of this application can be integrated together to form an independent part for execution, or each method step can be executed by a separate module, or two or more steps can be formed into an independent part for execution.

[0147] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks. It should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application. It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0148] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for monitoring equipment, characterized in that, include: Monitor production-related data of the equipment to be monitored; wherein, the production-related data includes planned working time, actual operating time, and ineffective working time during the production process; The effective operating time is determined based on the actual operating time and the ineffective operating time; Based on the effective operating time, the planned operating time, and the actual operating time, the overall equipment efficiency of the equipment to be monitored is determined.

2. The method according to claim 1, characterized in that, The invalid working time includes the time lost due to failure, the time lost due to performance loss, and the time lost due to quality loss of the monitored equipment. The determination of effective operating time based on the actual operating time and the ineffective operating time includes: The effective operating time is determined based on the actual start-up time, the quality loss time, the failure loss time, and the performance loss time.

3. The method according to claim 2, characterized in that, The method further includes: Based on the actual operating time and the performance loss time, the net operating time is determined; The determination of the overall equipment efficiency of the monitored equipment based on the effective operating time, the planned operating time, and the actual operating time includes: The time utilization rate is determined based on the planned working time and the actual operating time. Based on the effective operating time and the net operating time, the yield of the equipment to be monitored is determined; The performance efficiency of the device under monitoring is determined based on the net operating time and the actual operating time. Based on the time utilization rate, the yield rate, and the performance efficiency, the overall equipment efficiency of the device to be monitored is determined.

4. The method according to claim 2, characterized in that, The production-related data includes shutdown fault status, non-shutdown status, effective production status, and ineffective production status; The monitoring of production-related data of the equipment under monitoring includes: Monitor the status information of the device under monitoring, as well as the duration of each status; wherein, the status information includes paused status, fault status, and running status; The shutdown fault state and the non-shutdown state are determined from the fault states; wherein, the duration of the shutdown fault state is determined as the fault loss time. Effective production states and ineffective production states are determined from the operating states; wherein, the duration of the ineffective production state is determined as the performance loss time.

5. The method according to claim 1, characterized in that, The method further includes: Within a monitoring cycle, the overall efficiency of the device is updated according to a set time pattern; Based on the overall efficiency of the equipment updated according to a set time pattern, the efficiency change trend of the monitored equipment is determined.

6. The method according to claim 5, characterized in that, The method further includes: The equipment cycle time of the device to be monitored is determined based on the efficiency change trend. Based on the efficiency change trend and the equipment cycle time, a performance report of the equipment to be monitored is generated.

7. The method according to claim 6, characterized in that, The method further includes: Based on the production-related data and the efficiency change trend, an equipment performance change graph is output and displayed; wherein the equipment performance change graph is presented in one or more ways, such as a bar chart or a pie chart.

8. The method according to claim 7, characterized in that, Applied to display devices, the device performance change graph includes one or more of the following: utilization rate analysis graph, device status analysis graph, comparison analysis graph with similar devices, cycle time analysis graph, fault detail analysis graph, abnormal data graph, and detail table; The output and display of the device performance change graph includes: Display one or more of the following controls: utilization rate analysis control, equipment status analysis control, similar equipment comparison analysis control, cycle time analysis control, fault details analysis control, abnormal data control, and details table control; In response to an operation on any of the controls mentioned above—the utilization rate analysis control, the equipment status analysis control, the similar equipment comparison analysis control, the cycle time analysis control, the fault details analysis control, the abnormal data control, and the details table control—the corresponding graph triggered by the operation is displayed.

9. An electronic device, characterized in that, include: The processor and memory, wherein the memory stores machine-readable instructions executable by the processor, wherein when the electronic device is running, the machine-readable instructions are executed by the processor to perform the steps of the method as described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the method as described in any one of claims 1 to 7.

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