Equipment lean index evaluation method based on variable management and control

Abstract

The invention provides an equipment lean index evaluation method based on variable control. The method comprises the following steps: acquiring various variables in an equipment lean evaluation process according to core indexes of equipment; and according to each variable, obtaining an evaluation score corresponding to the evaluation object so as to perform lean evaluation on the evaluation object. According to the variable control-based equipment lean index evaluation method provided by the invention, by controlling core indexes and variables, different variables are subjected to unified latitude operation and are combined according to classes, so that accurate evaluation is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of production site equipment operation and maintenance management, and in particular to an equipment lean index evaluation method based on variable control. Background Art

[0002] With the development of intelligent production and processing equipment, on-site equipment and equipment-related lean management are receiving more and more attention.

[0003] Lean management originated from lean production. Lean management is a management model formed by enterprises integrating lean thinking with their own management activities. Lean management requires enterprises to establish a continuous improvement system so that waste elimination activities can continue continuously. Only then can the company's operations become more efficient and create greater value for the company, employees and society.

[0004] According to the requirements of lean management, the correlation between the various indexes involved in the equipment lean index evaluation process is complex, and a huge amount of data needs to be processed. These data involve different dimensions and categories, and need to be calculated and analyzed. When the scoring rules and other related settings are changed, all scores must be recalculated, which requires a lot of manpower and material resources to analyze and calculate, resulting in unnecessary waste of human resources. In addition, there may be errors caused by manual calculations, and data re-verification is required, which may cause considerable trouble to subsequent work.

[0005] At present, the indicator structure system for equipment lean evaluation is still not perfect, and the indicator variable driven management mechanism has not been established. This is the core problem that needs to be solved in the stage of improving equipment operation and maintenance efficiency. Summary of the invention

[0006] The main purpose of the present invention is to solve the above-mentioned problems and shortcomings, and to provide an equipment lean index evaluation method based on variable control. By controlling core indicators and variables, different variables are unified in calculation dimensions and combined by category for accurate evaluation.

[0007] To achieve the purpose of the invention, the present invention provides an equipment refinement index evaluation method based on variable control, which adopts the following technical scheme:

[0008] A lean index evaluation method for equipment based on variable control obtains various variables in the lean evaluation process of equipment according to the core indicators of the equipment; and obtains the evaluation score corresponding to the evaluation object according to each variable to conduct a lean evaluation of the evaluation object.

[0009] Furthermore, the variable content contained in the evaluation object is set, and the evaluation score of the evaluation object is obtained after unifying the latitude of each variable.

[0010] Furthermore, each variable is created into a corresponding equipment lean index, and a lean index library is established to define the corresponding ranges and levels of the lean indexes of different equipment, and to conduct lean index evaluation.

[0011] Furthermore, a linear relationship between the equipment lean index score, the lean index evaluation level and the number of levels, and a linear relationship between the equipment lean index score and the evaluation object score are established to obtain the evaluation object score and evaluate the evaluation object.

[0012] Furthermore, the corresponding equipment lean index is created based on the variables by using the direct proportion method, and the equipment lean evaluation grade is obtained according to the obtained equipment lean index.

[0013] Furthermore, the formula for the direct proportional method is Among them, y i is the equipment lean index obtained by transformation, X i is the actual value of the variable output by EAM, X i It is the variable threshold obtained through EAM historical data statistics.

[0014] Furthermore, the lean index score is obtained based on the established equipment lean index, lean index evaluation, etc. and the linear relationship between the lean index score and the number of grades, and the evaluation object is evaluated.

[0015] Furthermore, the linear equation of the lean index score is Among them, n1 is the number of events with a lean index evaluation level of A, n2 is the number of events with a lean index evaluation level of B, n3 is the number of events with a lean index evaluation level of C, n4 is the number of events with a lean index evaluation level of D, and λ is the lean index score.

[0016] Furthermore, the final score of the evaluation object is obtained according to the relationship between the evaluation object score and the lean index score.

[0017] Furthermore, the relationship between the evaluation score, the evaluation object score, and the lean index score is:

[0018] α=β1·λ 关联精益指数1 +β2·λ 关联精益指数2 +…+β n ·λ 关联精益指数n

[0019] Among them, α is the final score of the evaluation result, and β is the corresponding correlation index weight coefficient.

[0020] In summary, the equipment lean index evaluation method based on variable control provided by the present invention has the following technical advantages compared with the prior art:

[0021] 1. Variable control: By controlling the core indicator variables, focusing on business scenarios, strengthening infrastructure construction, and comprehensively improving the equipment management level through process reengineering and method innovation;

[0022] 2. Unify the evaluation dimensions; use equal conversion and direct proportional method to process the variable data dimensionlessly, assign weights (%) to determine the evaluation rules, combine by category, and evaluate accurately;

[0023] 3. Determine the new variable threshold; set it as the average threshold of historical data, such as the new fault handling time threshold, set it as the historical average fault handling time of the handler;

[0024] 4. Iterative update of variable thresholds; Based on statistical historical data, the thresholds of each variable are determined by analyzing the number of faults within a certain period, and the variable thresholds are determined by the average value of statistical variable historical data. The statistical method of historical data follows the distribution law of the standard normal distribution curve. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 : A flow chart of a method for evaluating equipment lean index based on variable control provided by the present invention;

[0026] Figure 2 : A logical relationship diagram of core indicators, variables and indexes of a device lean index evaluation method based on variable control provided by the present invention;

[0027] Figure 3 : A schematic diagram of normal distribution of variable thresholds in a method for evaluating equipment lean index based on variable control provided by the present invention;

[0028] It should be noted that these drawings and textual descriptions are not intended to limit the conceptual scope of the present invention in any way, but are intended to illustrate the concept of the present invention for those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The following embodiments are used to illustrate the present invention but are not used to limit the scope of the present invention.

[0030] In the description of the present invention, it should be noted that the directions or positional relationships indicated by terms such as “upper”, “lower”, “front”, “back”, “left”, “right”, “vertical”, “inside” and “outside” are based on the directions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as a limitation on the present invention.

[0031] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0032] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0033] The present invention provides an equipment lean index evaluation method based on variable control, which obtains various variables in the equipment lean evaluation process according to the core indicators of the equipment; obtains the equipment lean index corresponding to the evaluation object according to each variable and performs lean evaluation by category.

[0034] The present invention provides a method for evaluating equipment lean index based on variable control, such as Figure 1 The evaluation process shown decomposes the core indicators of the equipment into corresponding variables, classifies and combines the variables according to different evaluation objects, obtains the lean index corresponding to the variables involved in each evaluation, and performs lean evaluation by category according to the evaluation rules.

[0035] The core indicators of the equipment are decomposed into corresponding variables. In this embodiment, a single equipment is taken as the base point, such as Figure 2 As shown in the figure, the core indicators of the equipment include but are not limited to failure downtime rate, MTBF / MTTR, inspection completion rate, scheduled maintenance / minor repair plan fulfillment rate, operation and maintenance cost, and single machine energy consumption. These seven core indicators are decomposed into 21 variables, including:

[0036] Decompose the downtime rate into six variables: reporting response time, technical personnel approval time, business manager approval time, fault handling time, fault closure time, and operating time;

[0037] Decompose MTBF into two variables: total number of failures and operating time;

[0038] Decompose MTTR into two variables: total number of failures and failure repair time;

[0039] Decompose the inspection completion rate into two variables: planned quantity and completed quantity;

[0040] Decompose the scheduled maintenance / minor repair plan completion rate into two variables: planned completion quantity and completed quantity;

[0041] Decompose the operation and maintenance costs into four variables: spare parts cost, fault repair cost, maintenance cost, and major repair cost;

[0042] The energy consumption of a single machine is decomposed into three variables: load power cost, standby power cost, and loss power cost.

[0043] Among them, different core indicators may have the same variable names, but due to the different corresponding core indicators, the corresponding application modes, methods and calculation methods are different in the subsequent lean evaluation process, thus playing a corresponding role in the lean evaluation.

[0044] Furthermore, different variables correspond to different equipment lean indexes. In the present embodiment, the above 21 variables are created into corresponding 19 equipment lean indexes, which are defined as: submission response index (GZ1), technician approval index (GZ2), business manager approval index (GZ3), fault handling index (GZ4), fault closure index (GZ5), operation index (GZ6), total fault number index (SZ), maintenance index (spot inspection completion rate) (WZ1), maintenance index (scheduled maintenance / minor repair plan completion rate) (WZ2), spare parts cost index (CZ1), repair cost index (CZ2), maintenance cost index (CZ3), major repair cost index (CZ4), load power cost index (QZ1), standby power cost index (QZ2), loss power cost index (QZ3), maintenance efficiency index (RZ1), fault repair efficiency index (RZ2), and major repair efficiency index (RZ3). Among them, the two variables of planned quantity and completed quantity corresponding to the core indicator inspection completion rate are created as the maintenance index (WZ1), and the two variables of planned quantity and completed quantity corresponding to the core indicator maintenance / minor repair plan completion rate are created as the maintenance index (WZ2).

[0045] In this embodiment, 19 equipment lean indexes are created based on 22 variables using the direct proportional method. The specific method uses the following formula:

[0046]

[0047] Among them, X i is the actual value of the variable output by EAM (Enterprise Asset Management), X0 is the variable threshold obtained by EAM historical data statistics, and y i is the equipment lean index obtained by conversion.

[0048] By converting variables into equipment lean indexes through formulas, all lean evaluation data are unified into the same dimension, avoiding evaluation errors caused by different dimensions and data when directly using variables for lean evaluation.

[0049] The iterative update of variable thresholds is based on statistical historical data. The thresholds of each variable are determined by analyzing the number of faults within a certain period. That is, the variable thresholds are variable values ​​and are adjusted according to the set period.

[0050] The determination of the variable threshold conforms to the distribution law of the standard normal distribution curve. For example, the fault handling time of a certain type of fault is statistically analyzed. The average handling time within one year is 24 minutes, the standard deviation is 3, and the value corresponding to the probability of 0.75 is taken as the variable threshold. Through calculation, it is 26 minutes. The standard normal distribution is as follows: Figure 3 Normal distribution and the calculation of variable thresholds based on the normal distribution principle are conventional techniques and will not be described in detail.

[0051] In this embodiment, the variable threshold can be obtained through conventional data of the industry or basic data of the equipment, and during use, an iterative update cycle is set, and historical data within the cycle is used, such as the number of faults, to analyze and determine each variable or value, and the variable threshold is determined by statistically averaging the historical data of the variable.

[0052] Determination of new variable thresholds; set them as the average thresholds of historical data, such as the new fault handling time threshold, set it as the historical average fault handling time of the handler;

[0053] In the present invention, the defined equipment lean index is combined by category, so as to utilize core indicators, variables and equipment lean index, calculate the corresponding equipment lean index through variables, and perform lean evaluation on different evaluation objects according to the index score and preset evaluation principles.

[0054] Furthermore, in this embodiment, a lean index library as shown in Table 1 is established. In the lean index library, lean indexes of different equipment are defined. In the definition, a data calculation method or a calculation formula (Formula 1) for the lean index of each equipment is given. Different lean index names have different variable thresholds and actual variable value data and units in Formula 1. For example, when calculating the corresponding lean index of the failure downtime rate (core indicator), Formula 1 is transformed into GZ=T 实际 / T i , the corresponding data are all time, and the corresponding variable threshold X0 is the response reference time T i , the actual value of the variable X i is the actual response time T 实际 ; When calculating the corresponding lean index total failure index SZ in MTBF / MTTR (core indicator), Formula 1 is transformed into:

[0055] SZ=N 实际 / (N 基准 *E),

[0056] The corresponding data is the number of devices, and the variable threshold X0 is the number of single device failure benchmarks N基准 The actual value of the variable Xi is the actual number of single equipment failures N. 实际 Although the data units used are different, after calculation by Formula 1, they are all ratios without units, thus unifying the data into the same evaluation dimension.

[0057] The time obtained by calculating the standard normal distribution of all response times in this cycle is used to determine the levels corresponding to different index ranges to evaluate the lean index level. The lean index library also includes the equipment lean level corresponding to each core indicator. According to the evaluation requirements, the scores are divided into sections, and different sections correspond to different lean levels.

[0058] Lean levels and segment divisions can be set based on experience, including but not limited to the division mode shown in Table 1. It can also be set as a dynamic division mode. In the initial stage, the number of levels and the corresponding segment divisions are set according to industry experience and evaluation requirements. In the later stage, the adjustment cycle is set. According to the lean index score obtained in each cycle, the segment division method corresponding to the score and the corresponding lean level are adjusted. The cycle can be divided by time or by the number of lean evaluations, without any requirements or restrictions.

[0059] Table 1: Lean Index Library

[0060]

[0061]

[0062] A linear relationship between the evaluation object score and the lean index score is established, and the evaluation object is evaluated as “excellent, good, medium, or poor” based on the evaluation object score.

[0063] Specifically, according to the actual data and variable thresholds corresponding to each variable, and referring to the corresponding lean index definition and equipment lean grade evaluation in the lean index library, a linear relationship between the lean index score and the lean index evaluation grade and the number of grades is established. The linear equation between the lean index score and the lean index evaluation grade and the number of grades is as follows:

[0064]

[0065] Among them, n1 is the number of events with a lean index evaluation level of A, n2 is the number of events with a lean index evaluation level of B, n3 is the number of events with a lean index evaluation level of C, n4 is the number of events with a lean index evaluation level of D, and λ is the lean index score.

[0066] It should be noted that in Formula 2, n1, n2, n3 and n4 are set based on the fact that the lean index level evaluation in the lean index library mentioned above is divided into four levels: A, B, C, D (excellent, good, medium, and poor). In practical applications, according to the division method of the evaluation level, Formula 2 is adaptively modified, and each level and the corresponding number of levels are added to the formula, which is within the scope of protection of the present invention. The modified Formula 2 is:

[0067]

[0068] At this time, the evaluation level is divided into A to I levels, where I can be any level in increasing order after A. For example, if I is C, it is divided into A, B, C three levels; if I is F, the evaluation level is divided into A, B, C, D, E, F six levels... and so on, n1 to n i is the number of events corresponding to each lean index evaluation level, and I is the last level in the evaluation level.

[0069] Furthermore, a linear relationship between the evaluation object score and the lean index score is established, and the linear equation is fitted using the weighted average method, where the weighted coefficient corresponding to each evaluation level can be shown in Table 1. The formula between the evaluation object score and the lean index score after fitting is as follows:

[0070] α=β1·λ 关联精益指数1 +β2·λ 关联精益指数2 +…+β n ·λ 关联精益指数n , Formula 3

[0071] Among them, α is the final score of the evaluation result, and β is the weight coefficient of the corresponding correlation index. According to the lean requirements, the final score of the evaluation result is divided into sections, and each section corresponds to an evaluation result. For example, the relationship between the score of α and the evaluation result can be set as follows:

[0072] When 85<α≤100, the lean evaluation result is excellent;

[0073] When 75<α≤85, the lean evaluation result is good;

[0074] When 60<α≤75, the lean evaluation result is medium;

[0075] When α<75, the lean evaluation result is poor.

[0076] According to the assessment mechanism and with reference to the assessment results, rewards and assessments will be given to the assessment objects.

[0077] Preferably, the weight coefficients in Formula 3 can be obtained from Table 1. The weights corresponding to all evaluation levels are the same. In practical applications, the weight coefficients corresponding to the lean index of each device can be set separately according to historical data, historical evaluation results, and evaluation requirements.

[0078] In practical applications, the segmentation rules for the final score of the evaluation results can be determined according to the lean requirements. Similarly, the segmentation of the final score of the evaluation results can also be dynamic, and the segmentation can be dynamically adjusted according to the equipment's usage time, operating time, remaining rated life, and the development trend of the final score of the lean evaluation results, so that the lean evaluation can be closer to the actual situation.

[0079] As described above, the equipment lean index evaluation method based on variable control provided by the present invention is preset in the control system, and according to the above, the core indicators of the equipment are decomposed according to the equipment classification, decomposed into various variables in the equipment lean evaluation process, and the corresponding equipment lean index is created according to the variables; the variables associated with the evaluation object are set, each evaluation object includes one or more variables, and different evaluation objects may have the same variables, so that the equipment lean index is obtained according to the variables included in the evaluation object, so as to perform lean evaluation on different evaluation objects;

[0080] During the evaluation, the control system presets the aforementioned formulas 1 to 3 (including various modified formulas), and according to different variables and the equipment lean index definition in the lean index library, the formula 1 is adaptively modified to calculate the equipment lean index corresponding to each variable;

[0081] The equipment lean index obtained by calculation is then calculated according to Formula 2 to calculate the equipment lean index score. Specifically, when calculating the equipment lean index score, the lean index obtained by calculation according to the definition in the lean index library and the transformed (if necessary, not necessary) formula 1 is compared with the lean index library to obtain the corresponding equipment lean grade, such as A, B, C, D, etc.; then, according to the evaluation grade of each variable in the evaluation object, the number of grades and the linear relationship in the equipment lean index, and Formula 2, the equipment lean index score corresponding to each variable and equipment lean index is planned;

[0082] Set the weight corresponding to the lean index of each equipment, obtain the final score of the lean evaluation result corresponding to the variable according to Formula 3, and make an evaluation of "excellent, good, medium, poor" for the evaluation object according to the evaluation rules, and finally complete the lean evaluation of the equipment.

[0083] It should be noted that when calculating the equipment lean index, corresponding data collection can be performed according to the type of the object to be evaluated and the variables included, and the equipment lean index score required for the evaluation object can be calculated purposefully.

[0084] When the method provided by the present invention is used to perform lean evaluation of each evaluation object, the recommended evaluation objects and the variables included in each evaluation object may be:

[0085] Technical staff evaluation:

[0086] Technical personnel evaluate and assign values ​​to daily work indicators based on fault response, fault repair cost, and major repair cost, and the evaluation score is calculated comprehensively based on the number of daily events and evaluation levels.

[0087] Operator comments:

[0088] Operator evaluation assigns values ​​to daily operation indicators in terms of fault closure time and inspection compliance rate, and the evaluation score is calculated comprehensively based on the number of daily events and evaluation levels.

[0089] Maintenance staff evaluation:

[0090] The ability evaluation of maintenance personnel is to evaluate and assign values ​​to daily work indicators in terms of fault response, fault repair time, total number of faults, quality of scheduled minor repairs, and maintenance costs. The evaluation score is calculated comprehensively based on the number of daily events and the evaluation level.

[0091] Comprehensive evaluation of equipment:

[0092] The comprehensive equipment evaluation is to evaluate and assign values ​​to daily operation indicators from aspects such as equipment performance status, failure downtime rate, annual maintenance cost, and equipment utilization rate. The equipment evaluation score is calculated comprehensively based on the number of daily events and the evaluation level.

[0093] Operation and maintenance cost evaluation:

[0094] The operation and maintenance cost evaluation is to evaluate and assign values ​​to daily operation indicators based on spare parts costs, fault repair costs, maintenance costs, major repair costs, and electricity costs. The evaluation score is calculated comprehensively based on the number of daily operations and indicator evaluations.

[0095] Single machine energy consumption evaluation:

[0096] The single-machine energy consumption evaluation is to evaluate and assign values ​​to the single-machine energy consumption indicators of the equipment based on the load electricity cost, standby electricity cost, and loss electricity cost, and obtain the single-machine energy consumption evaluation result of the equipment through comprehensive calculation.

[0097] Take the evaluation of technicians as an example:

[0098] As shown in Table 2, the variables associated with the technician evaluation and the corresponding equipment lean index are fault response (GZ1), fault repair cost (CZ2), and major repair cost (CZ4); wherein the weight coefficients of the lean indexes of various equipment are determined by the lean index library. In this embodiment, the weight coefficient of the fault response (GZ1) score is 0.2, the weight coefficient of the fault repair cost (CZ2) score is 0.4, and the weight coefficient of the major repair cost (CZ4) score is 0.4;

[0099] like Figure 1 The evaluation process shown in the figure obtains the corresponding variable threshold value according to the normal distribution principle through the daily collected data, and calculates the lean index according to the real-time data during the evaluation and formula 1 (if necessary, it is transformed according to the lean index library); the lean index can determine the index evaluation level by comparing the lean index library; as shown in Table 2, in September, the evaluation results of fault response (GZ1) included 22 A, 50 B, 2 C, and 0 D; the evaluation results of fault repair cost (CZ2) included 15 A, 53 B, 5 C, and 1 D; the major repair cost (CZ4) included 1 A, 1 B, 0 C, and 0 D; by checking the lean index library, A is assigned 100; B is assigned 80; C is assigned 60; and D is assigned 40; the equipment lean index score is calculated through formula 2, and then the final score of the evaluation result is obtained through formula 3, and according to the evaluation rules, the final evaluation level is excellent as shown in Table 2.

[0100] Table 2: Technical staff evaluation form

[0101]

[0102] In summary, the equipment lean index evaluation method based on variable control provided by the present invention has the following technical advantages compared with the prior art:

[0103] 1. Variable control: By controlling the core indicator variables, focusing on business scenarios, strengthening infrastructure construction, and comprehensively improving the equipment management level through process reengineering and method innovation;

[0104] 2. Unify the evaluation dimensions; use equal conversion and direct proportional method to process the variable data dimensionlessly, assign weights (%) to determine the evaluation rules, combine by category, and evaluate accurately;

[0105] 3. Determine the new variable threshold; set it as the average threshold of historical data, such as the new fault handling time threshold, set it as the historical average fault handling time of the handler;

[0106] 4. Iterative update of variable thresholds; Based on statistical historical data, the thresholds of each variable are determined by analyzing the number of faults within a certain period, and the variable thresholds are determined by the average value of statistical variable historical data. The statistical method of historical data follows the distribution law of the standard normal distribution curve.

[0107] As described above, similar technical solutions can be derived from the given solution content. However, any simple modification, equivalent changes and modifications made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A method for evaluating equipment lean index based on variable control, characterized in that: According to the core indicators of the equipment, various variables in the lean evaluation process of the equipment are obtained; according to each variable, the evaluation score corresponding to the evaluation object is obtained to conduct a lean evaluation of the evaluation object.

2. The equipment lean index evaluation method based on variable control according to claim 1, characterized in that: Set the variable content contained in the evaluation object, unify the latitude of each variable and obtain the evaluation score of the evaluation object.

3. The equipment lean index evaluation method based on variable control according to claim 1, characterized in that: Create corresponding equipment lean index for each variable, establish a lean index library, define corresponding ranges and levels of lean index for different equipment, and conduct lean index evaluation.

4. The equipment lean index evaluation method based on variable control according to claim 3 is characterized in that: Establish a linear relationship between the equipment lean index score, the lean index evaluation level and the number of levels, and the linear relationship between the equipment lean index score and the evaluation object score, obtain the evaluation object score, and evaluate the evaluation object.

5. The equipment lean index evaluation method based on variable control according to any one of claims 1 to 4, characterized in that: Based on the variables, the direct proportion method is used to create the corresponding equipment lean index, and the equipment lean evaluation grade is obtained according to the obtained equipment lean index.

6. The equipment lean index evaluation method based on variable control according to claim 5, characterized in that: The formula for the direct proportional method is Among them, y i is the equipment lean index obtained by transformation, X i is the actual value of the variable output by EAM, X i It is the variable threshold obtained through EAM historical data statistics.

7. The equipment lean index evaluation method based on variable control according to claim 5, characterized in that: The lean index score is obtained based on the established equipment lean index, lean index evaluation, etc. and the linear relationship between the lean index score and the grade quantity, and the evaluation object is evaluated.

8. The equipment lean index evaluation method based on variable control according to claim 7, characterized in that: The linear equation for the Lean Index score is Where A, B, C, …I are the set evaluation levels, n1 is the number of events with a lean index evaluation level of A, n2 is the number of events with a lean index evaluation level of B, n3 is the number of events with a lean index evaluation level of C, and n i is the number of events with a lean index evaluation level of I, and λ is the lean index score.

9. The equipment lean index evaluation method based on variable control according to claim 8, characterized in that: The final score of the evaluation object is obtained based on the relationship between the evaluation object score and the lean index score.

10. The equipment lean index evaluation method based on variable control according to claim 9, characterized in that: The relationship between the evaluation score, the evaluation object score, and the lean index score is: α=β1·λ 关联精益指数1 +β2·λ 关联精益指数2 +…+b n ·l 关联精益指数n Among them, α is the final score of the evaluation result, and β is the corresponding correlation index weight coefficient.

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