A method for dynamic management of personnel qualification and on-the-job suitability assessment in a thermal power plant

Abstract

The application discloses a kind of thermal power plant personnel qualification dynamic management and post suitability evaluation method, belong to electric power safety management technical field.The method is by building the multidimensional index system including five dimensions of educational background, training record, operation performance, safety record and post experience, introduce time attenuation factor to the dynamic conversion of historical authentication data, and the qualification comprehensive index (QCI) is calculated;Further, through the post suitability evaluation algorithm engine, QCI is multidimensionally matched with post requirement vector, and the post suitability evaluation index (PSI) is calculated;According to the comparison result of PSI and preset double threshold (T1=75, T2=60), trigger three-level early warning mechanism and automatically generate post adjustment suggestion, training plan push and comprehensive management report.The application realizes the change from static certificate management to dynamic capability evaluation, effectively reduces the safety risk caused by the mismatch between personnel ability and post demand, and provides scientific and quantitative decision basis for the safety production of thermal power plant.

Description

Technical Field

[0001] This invention relates to the field of power safety production management technology, specifically to a method for dynamic management of personnel qualifications and job suitability assessment in thermal power plants, and in particular to a method for dynamic tracking of personnel capabilities and job matching assessment based on multi-dimensional index quantification, time decay factor correction, and a dual-threshold early warning mechanism. Background Technology

[0002] Thermal power plants are high-risk industrial production sites, and the qualifications and technical skills of their operators directly affect the safe operation of equipment and personal safety. my country's "Regulations on the Management of Safety Technical Training and Assessment for Special Operation Personnel" (Order No. 30 of the State Administration of Work Safety) and relevant technical standards in the power industry clearly require that special operation personnel in thermal power plants obtain corresponding certificates and undergo regular retraining and re-examination. However, the current management model has the following prominent problems: First, the existing management model is based on static certificate management, relying mainly on annual or periodic assessment records to determine whether personnel are qualified. This model cannot reflect the dynamic changes in personnel's knowledge and skills during the interval between assessments, especially the skill decline of personnel who have not used the computer for a long time. For example, if a person passes the annual assessment and is reassigned to an administrative position for six months, their actual operational skills may have significantly deteriorated, but the system will still mark them as "qualified" before the next assessment, which poses a safety hazard.

[0003] Second, there is a lack of a systematic matching and evaluation mechanism between the existing personnel qualification management and job requirements. Job adjustments often rely on the subjective experience and judgment of managers, lacking quantitative ability-job matching analysis tools, resulting in frequent "person-job mismatch" problems. This not only wastes highly skilled talents but also poses safety risks due to insufficient capabilities in key positions.

[0004] Third, in the existing management system, the training plan is mainly based on the unified annual plan, which makes it impossible to provide differentiated and precise training based on individual skill gaps, resulting in serious waste and misalignment of training resources. Summary of the Invention

[0005] This invention provides a method for dynamic management of personnel qualifications and job suitability assessment in thermal power plants. By constructing a multi-dimensional quantitative indicator system, introducing a time decay factor to achieve dynamic correction, designing a job suitability assessment algorithm and a three-level early warning mechanism, it achieves real-time dynamic tracking of personnel qualifications and scientific quantitative assessment of job matching.

[0006] The technical solution adopted in this invention is as follows: A method for dynamic management of personnel qualifications and job suitability assessment in thermal power plants includes the following steps: S1 collects multidimensional raw data of personnel from the personnel basic information database (1), training record database (2), assessment results database (3), operation record database (4), safety incident record database (5) and job requirement specification database (6); data collection supports two modes: periodic triggering (with a natural month as the cycle) and event triggering (instant triggering for safety incidents and unqualified assessments).

[0007] S2, through the data cleaning and preprocessing module (7), the original data is filled with missing values, outliers are removed and data is normalized; through the indicator quantification calculation module (8), the original data of each type is converted into quantitative indicator values ​​Di (i=1,2,3,4,5) in five dimensions, namely: education qualification dimension D1 (18), training record dimension D2 (19), operation performance dimension D3 (20), safety record dimension D4 (21), and job experience dimension D5 (22).

[0008] S3, calculate the time decay factor of each dimension by using the time decay factor engine (9) according to the formula f(t)=e^(-λ·Δt), where Δt is the time since the last certification or assessment (unit: month), and λ is the differential decay coefficient of each dimension: λ1=0.05 (educational qualifications), λ2=0.10 (training records), λ3=0.20 (operational performance), λ4=0.15 (safety records), λ5=0.08 (job experience).

[0009] S4, the multi-dimensional weight configuration module (10) provides the weights wi of each dimension (default configuration: w1=0.20, w2=0.25, w3=0.30, w4=0.15, w5=0.10, satisfying Σwi=1), and the qualification comprehensive index calculation module (11) calculates the personnel qualification comprehensive index QCI according to the formula QCI=Σ(wi·Di·f(t)), with a value range of [0, 100].

[0010] S5. Extract the job requirement vector PRV={R_min_i, R_opt_i} (i=1,...,5) of the target job from the job requirement specification library (6). The job suitability assessment algorithm engine (12) calculates the job suitability assessment index PSI according to the formula PSI=100×Σ(wi·Di·f(t)) / Σ(wi·R_opt_i), with a value range of [0, 100]. The job is divided into four levels: special operation job (38), main operation job (39), auxiliary operation job (40), and general auxiliary job (41).

[0011] S6. The early warning threshold determination module (13) determines PSI according to the position - level adaptive dual thresholds (T1, T2): when PSI ≥ T1, it is a first - level early warning (green, normal); when T2 ≤ PSI < T1, it is a second - level early warning (orange, attention); when PSI < T2, it is a third - level early warning (red, alarm).

[0012] S7. Trigger corresponding handling processes according to the early warning levels respectively: for the first - level early warning, the third - level early warning output module (14) records and archives it, and sets the next evaluation period; for the second - level early warning, the training plan automatic push module (16) pushes a targeted training plan and sets a re - evaluation within 30 days; for the third - level early warning, the position adjustment suggestion generation module (15) automatically generates handling suggestions and submits them for approval; finally, the management report automatic generation module (17) summarizes and issues a comprehensive management report.

[0013] Compared with the prior art, the present invention has the following beneficial effects: (1) Dynamic tracking replaces static management: By introducing the time - decay factor f(t)=e^(-λ·Δt), the present invention realizes the dynamic and continuous tracking of personnel qualifications. Compared with the static records of the existing annual assessment, it can reflect the risk of personnel's ability decline during their tenure in real - time, and can shorten the identification period of unqualified ability from an average of 12 months to 1 natural month, significantly improving the timeliness and accuracy of management.

[0014] (2) Quantitative suitability assessment replaces subjective judgment: Through the suitability assessment algorithm engine (12) and the suitability assessment matrix, the matching degree between personnel capabilities and job requirements is quantified as the PSI index, eliminating the uncertainty of subjective experience judgment in traditional management. The decision - making of position adjustment is well - documented, and the compliance is significantly improved.

[0015] (3) Precise and differential early warning push: The three - level early warning mechanism combines the analysis of the gap vector GAP_i to achieve precise and differential push of training plans. Compared with the traditional unified training plan, it can increase the effective utilization rate of training resources by about 35%, avoiding the waste of misplaced training resources.

[0016] (4) Active prevention replaces post - event handling: Through historical trend analysis (monitoring the trend slope k of consecutive N≥3 cycles), the present invention realizes the early identification of the trend of personnel ability decline, and can issue early warning prompts when PSI is still within the qualified range, truly achieving "pre - event prevention" rather than "post - event remedy".

[0017] (5) Strong system compatibility: The method of the present invention is compatible with the interfaces of the existing enterprise human resource management system (HRMS) and training management system (TMS), and is easy to be quickly deployed and applied based on the existing informatization foundation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1This is the overall architecture diagram of the dynamic management of personnel qualifications and job suitability assessment system for thermal power plants of the present invention; Figure 2 This is a flowchart illustrating the overall evaluation method of the present invention. Figure 3 This is a diagram illustrating the multidimensional index system structure of the Quality Comprehensive Index (QCI) of this invention. Figure 4 This is a schematic diagram of the job suitability assessment matrix of the present invention; Figure 5 This is a diagram of the three-level early warning system architecture and a time decay factor curve of the present invention.

[0019] In the diagram: 1-Personnel Basic Information Database, 2-Training Record Database, 3-Assessment Score Database, 4-Operation Record Database, 5-Safety Incident Record Database, 6-Job Requirements and Specifications Database, 7-Data Cleaning and Preprocessing Module, 8-Indicator Quantification Calculation Module, 9-Time Decay Factor Engine, 10-Multi-Dimensional Weight Configuration Module, 11-Qualification Comprehensive Index Calculation Module, 12-Job Suitability Assessment Algorithm Engine, 13-Early Warning Threshold Determination Module, 14-Three-Level Early Warning Output Module, 15-Job Adjustment Suggestion Generation Module, 16-Automatic Training Plan Push Module, 17-Automatic Management Report Generation Module, 18-Educational Qualification Dimension D1, 19-Training Record Dimension D2, 20-Operation... The following are the performance dimensions: D3 (performance dimension), D4 (safety record dimension), D5 (job experience dimension), D6 (education level score), D7 (professional matching degree), D8 (professional title certificate level), D9 (annual training hours), D0 (training project coverage rate), D1 (assessment pass rate), D2 (operational standardization score), D3 (work task completion rate), D4 (skill assessment score), D5 (safety violation count conversion score), D6 (accident participation record conversion score), D7 (safety training completion rate), D8 (years of service in the position), D9 (job rotation experience score), D0 (number of times participating in important tasks), D1 (special operation position), D2 (main operation position), D3 (auxiliary operation position), D4 (general auxiliary position). Detailed Implementation

[0020] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. In the following embodiments, the parameter values ​​are preferred examples, and those skilled in the art can make appropriate adjustments within the scope of protection of the claims according to actual application scenarios.

[0021] Example 1: Dynamic Suitability Assessment for Steam Turbine Master Operators This embodiment uses the turbine master operator of the 2×330MW coal-fired power generating unit of Huaneng Qingdao Thermal Power Company as the evaluation object to illustrate the specific implementation process of the method of the present invention.

[0022] S1, Data Acquisition: The system automatically collects the original data of the target personnel from various databases, including: the personnel basic information database (1) has an undergraduate degree (power plant thermal power engineering major) and holds a special operation certificate for turbine operation shift; the training record database (2) has completed 52 hours of training in the current year; the assessment score database (3) has a recent turbine professional assessment score of 82 points; the operation record database (4) has a 98% completion rate for operation tasks this month and an operation standardization score of 91 points; the safety incident record database (5) has no safety violation records in the past 12 months; the job requirement standard database (6) has excellent requirement thresholds for each dimension of the main operation position (39) as R_opt={90,85,90,95,80}.

[0023] S2, Data Processing: After processing by the data cleaning and preprocessing module (7), the quantitative index values ​​of each dimension are obtained through the index quantification calculation module (8): D1=88 (80 points for undergraduate degree, 10 points for perfect professional matching, -2 points for holding a special operation certificate, plus 88 points); D2=86 (52 hours of study completed in the year, 60 hours required, coverage rate 87%, assessment pass rate 100%, comprehensive calculation 86 points); D3=91 (91 points for operational standardization, 98% task completion rate, 82 points for skills assessment, comprehensive weighted 91 points); D4=100 (no violations in the past 12 months, basic 100 points + 5 points for bonus, maximum 100 points); D5=82 (7 years of work experience, participated in 2 major overhauls as the main operator, comprehensive 82 points).

[0024] S3, Time Decay Factor Calculation: The most recent professional assessment for this person was 3 months ago (Δt=3). The calculation results of the decay factors for each dimension are as follows: f1(t)=e^(-0.05×3)=0.861; f2(t)=e^(-0.10×3)=0.741; f3(t)=e^(-0.20×3)=0.549; f4(t)=e^(-0.15×3)=0.638; f5(t)=e^(-0.08×3)=0.787.

[0025] S4, Qualification Comprehensive Index (QCI) calculation: Using the default weight configuration (w1=0.20, w2=0.25, w3=0.30, w4=0.15, w5=0.10), QCI=0.20×88×0.861+0.25×86×0.741+0.30×91×0.549+0.15×100×0.638+0.10×82×0.787=15.15+15.93+14.99+9.57+6.45=62.09 points.

[0026] S5, Post Adaptability Assessment Index Calculation (PSI): For the main operation position (39), the excellent requirement for the comprehensive score = Σ(wi × R_opt_i) = 0.20 × 90 + 0.25 × 85 + 0.30 × 90 + 0.15 × 95 + 0.10 × 80 = 18 + 21.25 + 27 + 14.25 + 8 = 88.5 points; PSI = 100 × 62.09 / 88.5 = 70.2 points.

[0027] S6, Early Warning Level Judgment: For the main operation position (39), the adaptive thresholds are T1 = 80 and T2 = 65. PSI = 70.2, which satisfies T2(65) ≤ PSI(70.2) < T1(80), triggering a level 2 early warning (orange attention).

[0028] S7, Disposal Output: The training plan automatic push module (16) analyzes the gap vectors in each dimension. GAP_3 = 0.30 × (91 × 0.549 - 90) = 0.30 × (49.96 - 90) = -12.01 (the largest gap in the operation performance dimension), GAP_2 = 0.25 × (86 × 0.741 - 85) = 0.25 × (63.73 - 85) = -5.32 (the second largest gap in the training record dimension); the system automatically pushes two targeted training plans, "Strengthened Training on Turbine Simulator On-site Operation (24 class hours)" and "Review Training on Turbine Professional Technical Theory (16 class hours)", to this person, requiring completion within 30 days and triggering a re-evaluation within 15 days after completion.

[0029] Embodiment 2: Event-triggered Immediate Assessment - Re-assessment after Safety Violation This embodiment illustrates the specific implementation process of the safety event trigger mechanism. A person in a certain boiler auxiliary operation position (40) had a serious violation operation (arbitrarily解除联锁保护) in a certain month. After the safety event record library (5) added this event record, the system immediately triggered the immediate assessment process without waiting for the regular assessment cycle.

[0030] After this person triggered the immediate assessment, 20 points were deducted from the safety record dimension D4 due to the serious violation, dropping from the original 95 points to 75 points; the time decay factor Δt = 0 (immediately triggered, without decay); after recalculating QCI and PSI, PSI dropped from the original 73.5 points to 61.2 points, which is near the critical value of the level 2 early warning threshold T2 = 60 for the auxiliary operation position (40), triggering a level 3 early warning (red alarm).

[0031] It should be noted that the expression "擅自解除联锁保护" in the original text seems to be incomplete. You may need to check and correct it according to the actual situation. If it is a specific technical term, it should be accurately translated. The above translation is a rough one based on the existing text.The job adjustment suggestion generation module (15) automatically generates disposal suggestions: it is suggested to immediately suspend the independent duty qualification of this person and implement the "mentor - apprentice" supervision for taking up the post; push the "Special Training on Safety Regulations Learning and Safety Awareness Enhancement (40 class hours)"; conduct a safety special assessment after 30 days, and the independent post qualification can be restored only after being approved by the chief engineer. The above - mentioned disposal suggestions are automatically reported to the Human Resources Department and the Safety Supervision Department for filing and record - keeping, forming a closed - loop management.

[0032] Embodiment 3: Historical trend analysis - Early warning intervention This embodiment illustrates the specific implementation process of the historical trend analysis steps. The PSI records of a person in a special electrical maintenance operation post (38) for 5 consecutive months (N = 5) are: {84.2, 82.5, 80.1, 79.3, 77.8}.

[0033] The system conducts a linear regression analysis on 5 data points, and calculates the trend slope k=(77.8 - 84.2) / 4=-1.6 / month. The current PSI = 77.8, and it is still in the first - level warning range of the special operation post (38) (T1 = 85, current PSI < T1, it has already fallen into the second - level warning range T2 = 70, but PSI > T2). The trend slope k=-1.6, which does not reach the absolute threshold for triggering early warning k < - 2. The system records the trend data and marks "The ability shows a downward trend, it is recommended to pay attention" in the management report.

[0034] If the PSI continues to drop to 75.0 next month, at this time, the slope k for 6 consecutive months is approximately - 1.84 / month, and still does not reach k < - 2; if the PSI drops to 71.5 in July, the slope k for 7 consecutive months is approximately - 2.12 / month < - 2. The system triggers an early warning prompt, upgrades the warning level from the first level to the second level in advance, and automatically pushes the retraining plan, realizing active intervention when the PSI is still in the qualified range, preventing problems before they occur, and reflecting the core value of "preventive management" of this invention.

Claims

1. A method for dynamic management of personnel qualifications and job suitability assessment in thermal power plants, characterized in that, The method includes the following steps: S1. Collect multi-dimensional raw data of personnel from the basic personnel information database (1), training record database (2), assessment result database (3), operation record database (4), safety event record database (5) and job requirement specification database (6); S2. Clean and normalize the collected raw data through the data cleaning and preprocessing module (7) and the index quantization calculation module (8) to obtain the quantization index values Di (i = 1, 2, 3, 4, 5) for each dimension; S3. Calculate the time decay factor corresponding to each dimension according to the time interval Δt between each index and the last authentication by the time decay factor engine (9) according to the formula f(t)=e^(-λ·Δt), where λ is the decay coefficient for each dimension; S4. Obtain the weight wi (Σwi = 1) for each dimension through the multi-dimensional weight configuration module (10), and calculate the qualification comprehensive index QCI according to the formula QCI = Σ(wi·Di·f(t)) by the qualification comprehensive index calculation module (11); S5. Extract the job requirement vector PRV of the target job from the job requirement specification database (6), and calculate the suitability assessment index PSI by the suitability assessment algorithm engine (12) based on the qualification comprehensive index QCI and the job requirement vector PRV; S6. Compare the suitability assessment index PSI with the preset first threshold T1 and second threshold T2 (T1 > T2) by the warning threshold determination module (13). When PSI ≥ T1, trigger a first-level warning; when T2 ≤ PSI < T1, trigger a second-level warning; when PSI < T2, trigger a third-level warning; S7. Output corresponding handling actions by the third-level warning output module (14), job adjustment suggestion generation module (15), and training plan automatic push module (16) according to the warning level respectively, and generate a management report by summarizing through the management report automatic generation module (17).

2. The method according to claim 1, characterized in that, The quantization index values Di for each dimension described in step S2 specifically include: Educational qualification dimension D1 (18), including three sub-indices: educational level score (23), professional matching degree (24), and professional title certificate level (25); Training record dimension D2 (19), including three sub-indices: annual training hours (26), training project coverage rate (27), and assessment pass rate (28); Operation performance dimension D3 (20), including three sub-indices: operation standardization score (29), work task completion rate (30), and skill assessment result (31); Safety record dimension D4 (21), including three sub-indices: converted score of safety violation times (32), converted score of accident participation record (33), and safety training completion degree (34); Job experience dimension D5 (22), including three sub-indices: job working years (35), job rotation experience score (36), and number of important task participations (37).

3. The method according to claim 1, characterized in that, The decay coefficient λ for each dimension described in step S3 is set differently according to the index type: The decay coefficient λ1 of the educational qualification dimension D1 = 0.05, reflecting the characteristics of high stability and slow decay rate of educational qualifications; The decay coefficient λ2 of training record dimension D2 is 0.10, reflecting the moderate decay of training records over time; The decay coefficient λ3 of the operational performance dimension D3 is 0.20, reflecting the characteristic that operational skills decay rapidly if they are not continuously practiced. The decay coefficient λ4 of the security record dimension D4 is 0.15, reflecting the pattern of moderate reduction of security event records over time; The decay coefficient λ5 of the job experience dimension D5 is 0.08, reflecting the slow decay of the accumulated value of job experience.

4. The method according to claim 1, characterized in that, The specific steps of calculating the job suitability assessment index (PSI) by the job suitability assessment algorithm engine (12) in step S5 include: Extract the minimum requirement threshold R_min_i and the excellent requirement threshold R_opt_i for each dimension of the target job from the job requirement specification library (6), and construct the job requirement vector PRV={R_min_i, R_opt_i} (i=1,...,5); The difference vector GAP_i between the weighted scores of personnel in each dimension and the minimum requirements of the position is calculated as GAP_i = wi·Di·f(t) - wi·R_min_i; The job suitability assessment index (PSI) is calculated using the formula PSI=100×Σ(wi·Di·f(t)) / Σ(wi·R_opt_i), and the PSI value range is [0,100].

5. The method according to claim 1, characterized in that, The collection of multidimensional raw data by personnel in step S1 also triggers the following mechanism: Regularly triggered mechanism: Automated data collection and index updates are performed on all on-duty personnel on a calendar month basis; Event triggering mechanism: When a new record is added to the security event log (5) or a record of failing the assessment appears in the assessment results database (3), the immediate assessment process is immediately triggered for the relevant personnel, without being restricted by the periodic cycle.

6. The method according to claim 1, characterized in that, The configuration of the weights wi for each dimension in step S4 satisfies the following constraints: The weight w1 for the educational qualification dimension ranges from [0.15, 0.25]. The training record dimension weight w2 ranges from [0.20, 0.30]. The operational performance dimension weight w3 ranges from [0.25, 0.35], making it the dimension with the highest weight. The weight w4 for the security record dimension ranges from [0.10, 0.20]. The weight w5 for the job experience dimension ranges from [0.05, 0.15]. And the sum of the weights of all dimensions satisfies w1+w2+w3+w4+w5=1.

7. The method according to claim 1, characterized in that, In step S6, the first threshold T1 and the second threshold T2 are adaptively set for different job levels: Special Operations Position (38): T1=85, T2=70; Main operator (39): T1=80, T2=65; Auxiliary operation positions (40): T1=75, T2=60; General auxiliary positions (41): T1=70, T2=55.

8. The method according to claim 1, characterized in that, The specific actions to be taken based on the warning level in step S7 are as follows: When a Level 1 warning is issued, the management report automatic generation module (17) records the results of this assessment, incorporates them into the personnel file, and sets the next automatic assessment cycle to one calendar month. When a Level II warning is issued, the training plan automatic push module (16) automatically matches and pushes targeted training courses based on the gap vector GAP_i of each dimension, requiring completion within 30 natural days and triggering a re-evaluation within 15 days after the training is completed; When a Level 3 warning is issued, the job adjustment suggestion generation module (15) automatically generates a job demotion or off-duty training suggestion, submits it to the human resources department and safety supervision department for approval, and triggers an immediate review.

9. The method according to claim 1, characterized in that, The method also includes a historical trend analysis step: A personnel competency trend vector is constructed using QCI and PSI data from N consecutive assessment periods (N≥3). Linear regression analysis is used to determine the trend slope k. When k < -2 and the PSI is in the first-level warning range, a second-level warning is triggered in advance. When k < -5, the alert level is directly upgraded to Level 3, ensuring preventative rather than reactive risk intervention.

10. The method according to claim 2, characterized in that, The converted score (32) for the number of security violations in security record dimension D4 is calculated according to the following rules: The base score is 100 points; A deduction of 5 points will be made for each general violation; 20 points will be deducted for each serious violation; 40 points will be deducted for each instance of involvement in a major safety incident. If there are no violations during the evaluation period, an additional 5 points will be awarded, with a total score cap of 100 points and a minimum of 0 points.

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