Metallurgical industry employee safety behavior risk index quantification method and device

Abstract

The invention relates to the technical field of safety behavior assessment, and provides a metallurgical industry employee safety behavior risk index quantification method and device. The method comprises the following steps: analyzing individual evaluation scores to obtain the grade distribution proportion of each evaluation index; constructing an evaluation matrix between the safety factor set and the corresponding evaluation indexes by using the grade distribution proportion; weighting the corresponding evaluation matrix by using the sub weight vectors to obtain sub comprehensive evaluation values; determining a total weight vector of all the safety factor sets; constructing a sub-target evaluation matrix by using the sub comprehensive evaluation values of all the safety factor sets; weighting the sub-target evaluation matrix by using the total weight vector to obtain a total comprehensive evaluation value; and according to the total weight vector and the total comprehensive evaluation value, generating a total target evaluation vector so as to obtain an evaluation result of the group safety behavior, and solving the problem that targeted improvement measures cannot be effectively put forward due to the fact that the group safety behavior condition cannot be quantified.

Description

Technical Field

[0001] The present invention relates to the technical field of safety behavior assessment, and in particular to a method and device for quantifying the safety behavior risk index of employees in the metallurgical industry. Background Art

[0002] Unsafe human behavior is the main cause of accidents and casualties. Given the complex working environment and multiple risk factors in the metallurgical industry, standardized management of human safety behavior is particularly important.

[0003] Existing research on employee safety behavior in the metallurgical industry mostly adopts a questionnaire survey method with the theme of "employee + safety behavior". When analyzing and evaluating employee safety behavior, there are certain limitations when considering the influencing factors. It fails to fully cover factors such as employees' psychological conditions, personality characteristics, behavioral habits, educational background, and skill levels, and thus cannot quantify the risk assessment of employees' safety behavior.

[0004] Furthermore, existing safety behavior research focuses solely on individual employees. Relying solely on risk assessments of individual safety behaviors, it's impossible to capture the overall safety behavior of a group. Compared to individual safety behaviors, group safety behavior is more valuable for improving an enterprise's safety management system. Because this inability to characterize group safety behavior doesn't allow for effective, targeted improvement measures for enterprise safety management systems, employee safety behavior research has limited effectiveness in improving the quality of employee safety risk prevention and control in the metallurgical industry.

[0005] In view of this, overcoming the defects of the prior art is an urgent problem to be solved in this technical field. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a method and device for quantifying the safety behavior risk index of employees in the metallurgical industry. Its purpose is to quantify the safety behavior risk assessment of employees and obtain the risk assessment results of group safety behavior based on the individual evaluation scores of the questionnaire survey, thereby solving the problem that it is impossible to effectively propose targeted improvement measures for the enterprise safety management system due to the inability to quantify the group safety behavior status.

[0007] The present invention adopts the following technical solutions:

[0008] In a first aspect, the present invention provides a method for quantifying the safety behavior risk index of employees in the metallurgical industry, comprising:

[0009] Analyze individual evaluation scores to obtain the grade distribution ratio of each evaluation indicator; use the grade distribution ratio to construct an evaluation matrix between the safety factor set and the corresponding evaluation indicators; wherein a safety factor set includes multiple evaluation indicators;

[0010] Determine a sub-weight vector for each safety factor set; use the sub-weight vector to weight the corresponding evaluation matrix to obtain a sub-comprehensive evaluation value;

[0011] Determine a total weight vector of all safety factor sets; construct a sub-goal evaluation matrix using the sub-comprehensive evaluation values of all safety factor sets; and weight the sub-goal evaluation matrix using the total weight vector to obtain a total comprehensive evaluation value.

[0012] A total target evaluation vector is generated according to the total weight vector and the total comprehensive evaluation value to obtain an evaluation result of the group safety behavior.

[0013] Furthermore, generating a total target evaluation vector based on the total weight vector and the total comprehensive evaluation value to obtain an evaluation result of the group safety behavior includes:

[0014] The product of the total weight vector and the total comprehensive evaluation value is determined as the total target evaluation vector;

[0015] Determining the maximum value of the elements in the total target evaluation vector, and determining the evaluation grade interval in which the maximum value falls, so as to obtain the evaluation grade to which the maximum value belongs;

[0016] The obtained evaluation level is determined as the evaluation result of the group safety behavior.

[0017] Furthermore, the individual evaluation scores are analyzed to obtain the grade distribution ratio of each evaluation indicator; and using the grade distribution ratio, an evaluation matrix between the safety factor set and the corresponding evaluation indicator is constructed, including:

[0018] Determining the evaluation level range into which each evaluation indicator in the individual evaluation score falls;

[0019] Statistically calculate the distribution of scores for the same evaluation indicator in each evaluation level interval to obtain the proportion of the number of people falling into each evaluation level interval to the total number of people evaluated for each evaluation indicator;

[0020] For each evaluation indicator, all the grade distribution proportions are used as elements to construct a comment set;

[0021] An evaluation matrix is constructed using the comment set of all evaluation indicators of the same safety factor set.

[0022] Furthermore, the sub-comprehensive evaluation values of all safety factor sets are used to construct a sub-goal evaluation matrix; the sub-goal evaluation matrix is weighted using the total weight vector to obtain a total comprehensive evaluation value including:

[0023] Obtaining a sub-comprehensive evaluation value of each safety factor set, and using the obtained sub-comprehensive evaluation value as an element to form the sub-goal evaluation matrix using each element;

[0024] The product of the total weight vector and the sub-goal evaluation matrix is determined as the total comprehensive evaluation value.

[0025] Furthermore, determining the sub-weight vectors of each safety factor set includes:

[0026] Acquire multiple evaluation indicators belonging to the same safety factor set, and construct a matrix to be judged between the acquired evaluation indicators;

[0027] Normalizing each column of the matrix to be judged, summing the normalized matrix row by row, and normalizing the summation result to obtain a corresponding candidate weight vector;

[0028] Performing a consistency check on the candidate weight vector; when the candidate weight vector fails the consistency check, adjusting the candidate weight vector to re-perform a consistency check on the adjusted candidate weight vector until the candidate weight vector passes the consistency check, and determining the candidate weight vector that passes the consistency check as the sub-weight vector.

[0029] Furthermore, before analyzing the individual evaluation scores to obtain the grade distribution ratio of each evaluation indicator, the method further includes:

[0030] Constructing evaluation indicators; assigning similar evaluation indicators to a safety factor set to obtain multiple safety factor sets;

[0031] Conduct a safety behavior questionnaire assessment on employees to obtain an individual assessment score for each employee.

[0032] Furthermore, after determining the sub-weight vectors of each safety factor set and weighting the corresponding evaluation matrix using the sub-weight vectors to obtain the sub-comprehensive evaluation value, the method further includes:

[0033] Determining the maximum value of the elements in the sub-comprehensive evaluation value;

[0034] Determining the evaluation grade interval into which the maximum value falls, so as to obtain the evaluation grade to which the maximum value belongs;

[0035] The obtained evaluation level is determined as the evaluation result of each safety factor set.

[0036] Furthermore, the use of the sub-weight vectors to weight the corresponding evaluation matrix to obtain the sub-comprehensive evaluation value includes:

[0037] An evaluation matrix of the safety factor set is obtained; and a product of the obtained evaluation index and the sub-weight vector is determined as a sub-comprehensive evaluation value of the safety factor set.

[0038] In a second aspect, the present invention further provides a device for quantifying the safety behavior risk index of employees in the metallurgical industry, comprising:

[0039] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the processor to execute the method for quantifying the safety behavior risk index of employees in the metallurgical industry described in the first aspect.

[0040] In a third aspect, the present invention further provides a non-volatile computer storage medium, which stores computer-executable instructions, and the computer-executable instructions are executed by one or more processors to complete the method for quantifying the safety behavior risk index of employees in the metallurgical industry described in the first aspect.

[0041] In a fourth aspect, a computer program product comprising instructions is provided, which, when executed on a computer or a processor, causes the computer or processor to execute the method for quantifying the safety behavior risk index of employees in the metallurgical industry as described in the first aspect.

[0042] In the fifth aspect, the present invention also provides a metallurgical industry employee safety behavior risk index quantification system, including the metallurgical industry employee safety behavior risk index quantification device as described in the second aspect, and uses the metallurgical industry employee safety behavior risk index quantification method as described in the first aspect to complete the interaction of the metallurgical industry employee safety behavior risk index quantification device of the second aspect.

[0043] Different from the prior art, the present invention has at least the following beneficial effects:

[0044] The present invention analyzes individual assessment scores to obtain the grade distribution ratio of each evaluation indicator, and then constructs an evaluation matrix and a sub-goal evaluation matrix. The corresponding evaluation matrix is weighted using a sub-weight vector, and the sub-goal evaluation matrix is weighted using a total weight vector. By constructing the evaluation matrix and formulating each safety factor set and the corresponding evaluation indicators, a quantitative relationship is established between the individual assessment scores and the various evaluation indicators and safety factor sets involved in group safety behavior, solving the problem of fuzzy evaluation indicators and difficulty in quantification. Based on the total weight vector and the total comprehensive evaluation value, an overall goal evaluation vector is generated to obtain the evaluation results of group safety behavior. This allows the evaluation results to be used to obtain the performance and problems of employee safety behavior in each safety factor set dimension and evaluation indicator, providing a personalized reference basis for daily safety management and decision-making in enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort.

[0046] Figure 1 This is a flow chart of a method for quantifying the safety behavior risk index of employees in the metallurgical industry provided by an embodiment of the present invention;

[0047] Figure 2 is a flow chart of step 10 provided in an embodiment of the present invention;

[0048] Figure 3 This is a statistical chart of safety behavior evaluation of employees of each team / position type in a pickling workshop provided by an embodiment of the present invention;

[0049] Figure 4 This is a distribution diagram of evaluation results of various indicators of individual safety behaviors of pickling workshop employees provided by an embodiment of the present invention;

[0050] Figure 5 This is a schematic diagram of the distribution of safety behavior evaluation levels of employees in each team / position type in a pickling workshop provided by an embodiment of the present invention;

[0051] Figure 6 is a flow chart of step 20 provided in an embodiment of the present invention;

[0052] Figure 7 This is a schematic diagram of an evaluation process for an individual safety behavior evaluation level provided by an embodiment of the present invention;

[0053] Figure 8 This is a flow chart of another method for quantifying the safety behavior risk index of employees in the metallurgical industry provided by an embodiment of the present invention;

[0054] Figure 9 is a flow chart of step 30 provided in an embodiment of the present invention;

[0055] Figure 10 is a flow chart of step 40 provided in an embodiment of the present invention;

[0056] Figure 11 This is a schematic diagram of an evaluation process for a group safety behavior evaluation level provided by an embodiment of the present invention;

[0057] Figure 12 The present invention provides a schematic diagram of the structure of a device for quantifying the safety behavior risk index of employees in the metallurgical industry. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0059] Unless the context requires otherwise, throughout the specification and claims, the term "including" is to be interpreted as meaning open inclusion, that is, "including, but not limited to". In the description of the specification, the terms "one embodiment", "some embodiments", "exemplary embodiments", "example", "specific example" or "some examples" and the like are intended to indicate that the specific features, structures, materials or characteristics associated with the embodiment or example are included in at least one embodiment or example of the present disclosure. The schematic representation of the above terms does not necessarily refer to the same embodiment or example. In addition, the specific features, structures, materials or characteristics may be included in any one or more embodiments or examples in any appropriate manner, that is, although they may be carried in the embodiments or examples of the above terms due to reasons such as the order and position of appearance, it is not limited to that they can be carried in combination by one embodiment or example.

[0060] In the description of the present invention, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing the present disclosure and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present disclosure.

[0061] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present disclosure, unless otherwise specified, "multiple" means two or more. In addition, for example, the description may also use the method of adding "A" and "B" at the end to describe the same type of nouns as two independent individuals. In this case, the corresponding features defined as "A" and "B" are only used to distinguish the description purposes of the same type of individuals, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated.

[0062] When describing some embodiments, the expressions “coupled”, “coupled” and “connected” and their derivatives may be used. For example, when describing some embodiments, the term “connected” may be used to indicate that two or more components are in direct physical or electrical contact with each other. For another example, when describing some embodiments, the term “coupled” may be used to indicate that two or more components are in direct physical or electrical contact. However, the term “connected” or “coupled” may also mean that two or more components are not in direct contact with each other, but still cooperate or interact with each other, such as “optical coupling”, “wireless connection”, etc. The embodiments disclosed herein are not necessarily limited to the contents of the present invention.

[0063] In the description of the present invention, the expression "A and / or B" (where A and B are used to formally represent specific characteristic contents) will be involved, and the corresponding expressions include the following three combinations: only A, only B, and a combination of A and B.

[0064] As used herein, "about," "substantially," or "approximately" includes the stated value and an average value that is within an acceptable range of deviation from the particular value as determined by one of ordinary skill in the art taking into account the measurements in question and the errors associated with the measurement of the particular quantity (i.e., the limitations of the measurement system).

[0065] In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0066] Embodiment 1:

[0067] In order to solve the above problems, Figure 1 As shown, an embodiment of the present invention provides a method for quantifying the safety behavior risk index of employees in the metallurgical industry, including:

[0068] Step 10: Analyze the individual evaluation scores to obtain the grade distribution ratio of each evaluation indicator; use the grade distribution ratio to construct an evaluation matrix between the safety factor set and the corresponding evaluation indicators; wherein a safety factor set includes multiple evaluation indicators.

[0069] The individual assessment scores are the scores of employees taking the safety behavior questionnaire. The safety behavior questionnaire is generated based on the evaluation indicators of the embodiment of the present invention. Therefore, the performance of each evaluation indicator can be analyzed according to the score results, and the level distribution ratio and evaluation matrix can be obtained. The level distribution ratio of each evaluation indicator included in the safety factor set is used as an element to construct the evaluation matrix of the safety factor set.

[0070] Currently, research on employee safety behavior has certain limitations when considering its influencing factors, and fails to fully cover factors such as employees' psychological conditions, personality traits, behavioral habits, educational background, and skill levels. The path to employee safety behavior is: first, employees must have safety intentions and safety skills, that is, the employee has the ability to achieve operational goals; at the same time, the employee also needs to accurately understand safety behaviors and recognize the unsafe nature of the behavior; finally, the employee also needs to have a high perception of the value of safety behaviors, so that the employee will intentionally choose safe behaviors. However, the current approach of the entire industry to this issue is mainly based on subjective factors. There is a lack of a scientific method to determine which specific aspects to evaluate employee safety behaviors and how to scientifically evaluate employee safety behaviors. Therefore, it is impossible to provide targeted safety training and education to employees, resulting in an inability to improve employee safety behaviors.

[0071] To solve this problem, an embodiment of the present invention constructs evaluation indicators; similar evaluation indicators are assigned to a security factor set to obtain multiple security factor sets.

[0072] In one embodiment, the employee safety behavior evaluation factor set U covers three dimensional safety factor sets, namely: safety awareness factor set U1, safety attitude factor set U2, and safety skill factor set U3. Safety awareness factor set U1 covers four evaluation indicators: u11 cognition, u12 attention, u13 experience, and u14 memory. Safety attitude factor set U2 covers three evaluation indicators: u21 motivation, u22 will, and u23 commitment. Safety skill factor set U3 covers three evaluation indicators: u31 job safety operation ability, u32 accident prevention ability, and u33 emergency rescue ability. The following will explain how to scientifically select safety factor sets and evaluation indicators.

[0073] In one embodiment, employees are assessed on their safety behavior through a questionnaire to obtain an individual assessment score for each employee. Specifically, based on the employee safety behavior assessment system, a knowledge base of assessments for each position and job type is adapted to generate a questionnaire assessment QR code for employees to scan and participate in the assessment.

[0074] The employee safety behavior assessment system covers the assessment knowledge base of various positions and types of work in long-process metallurgical enterprises, including types of work, inspection and maintenance, and other related auxiliary types of work in various process links of long-process metallurgical enterprises, such as coking, sintering, ironmaking, steelmaking, rolling, energy and environment, transportation, quality inspection, security, inspection and maintenance, and special operations, covering nearly 300 operating positions.

[0075] A customized assessment knowledge base for each job type. The enterprise's assessment targets operators at all levels in the pickling mill, involving two types of personnel in the pickling mill: engineers and operators. The engineer category includes three positions: quality engineer, process control engineer, and on-site safety engineer. The operator positions include 12 positions: job supervisor, shift leader, entrance walking beam operator, acid regeneration operator, welder operator, pickling operator, post-pickling quality control operator, rolling mill operator, coiling operator, emulsion operator, online quality inspection, and export operator. The assessment collected safety procedures, safety management systems, training materials, scope of responsibilities, and special operations related to the aforementioned 15 positions. The assessment also included understanding the enterprise's organizational structure, compiling job lists, and reviewing job settings. The assessment also collected safety procedures, safety management systems, training materials, scope of responsibilities, and special operations related to the operator positions. The assessment was then compared with the existing knowledge base of the developed metallurgical enterprise employee safety behavior assessment system. The target knowledge base was adjusted to form a customized assessment knowledge base for the enterprise.

[0076] Using a customized assessment knowledge base, adapted to the assessment question bank for each job position within the company, the questionnaire covers multiple aspects, including safe job operations, hazardous working environments, special operations, safety awareness, and safety attitudes. A QR code for the questionnaire assessment website is generated and distributed to all employees, allowing them to scan and participate.

[0077] The employee safety behavior assessment system used in this embodiment covers nearly 300 operational positions in long-process metallurgical enterprises. This system integrates the risk characteristics of different positions to form a personalized knowledge base, creating a unique database for each position. This database covers basic safety skills, specialized safety skills, and emergency response skills. This addresses the difficulty in understanding and quantifying employee safety behaviors, as well as the lack of targeted and reliable support in daily safety training.

[0078] Step 20: Determine the sub-weight vectors of each safety factor set; use the sub-weight vectors to weight the corresponding evaluation matrix to obtain a sub-comprehensive evaluation value.

[0079] The embodiment of the present invention determines the sub-weight vector by using the hierarchical analysis method, which will be described below. The elements in the sub-weight vector are: weights for weighting the evaluation indicators under the same safety factor set.

[0080] Step 30: Determine the total weight vector of all safety factor sets; use the sub-comprehensive evaluation values of all safety factor sets to construct a sub-goal evaluation matrix; use the total weight vector to weight the sub-goal evaluation matrix to obtain a total comprehensive evaluation value.

[0081] The elements in the total weight vector are: weights for weighting each set of safety factors.

[0082] Step 40: Generate a total target evaluation vector based on the total weight vector and the total comprehensive evaluation value to obtain an evaluation result of the group safety behavior.

[0083] The present invention analyzes individual assessment scores to obtain the grade distribution ratio of each evaluation indicator, and then constructs an evaluation matrix and a sub-goal evaluation matrix. The corresponding evaluation matrix is weighted using a sub-weight vector, and the sub-goal evaluation matrix is weighted using a total weight vector. By constructing the evaluation matrix and formulating each safety factor set and the corresponding evaluation indicators, a quantitative relationship is established between the individual assessment scores and the various evaluation indicators and safety factor sets involved in group safety behavior, solving the problem of fuzzy evaluation indicators and difficulty in quantification. Based on the total weight vector and the total comprehensive evaluation value, an overall goal evaluation vector is generated to obtain the evaluation results of group safety behavior. This allows the evaluation results to be used to obtain the performance and problems of employee safety behavior in each safety factor set dimension and evaluation indicator, providing a personalized reference basis for daily safety management and decision-making in enterprises.

[0084] The following describes how to scientifically select a set of safety factors and evaluation indicators:

[0085] First, we construct a first-level indicator for evaluating employee safety behavior. Based on a large number of theoretical research results in behavioral psychology, organizational behavior, and other fields, combined with the risk characteristics of the metallurgical industry, we propose evaluation dimensions for employee safety awareness, safety attitude, and safety skills. Among them, safety awareness refers to the understanding of safety in people's minds, including safety values and safety vigilance; safety attitude refers to the will and desire of employees to fulfill their safety production responsibilities and achieve safety performance; safety skills refer to what people know when facing risks, including safety regulations, safety capabilities, safety common sense, etc. The following assumptions are made around workers' safety behavior:

[0086] H1: Safety awareness has a significant positive impact on workers' safety behavior.

[0087] H2: Safety attitude has a significant positive impact on workers' safety behavior.

[0088] H3: Safety skills have a significant positive impact on workers' safety behavior.

[0089] In one embodiment, a stratified random sampling method was used to conduct a questionnaire survey on 100 workers in a metallurgical enterprise. After the questionnaire survey, 98 valid questionnaires were obtained, with a recovery rate of 98%. The data were collated (e.g., the data were tested for reliability and validity and common method bias), and descriptive statistical analysis and direct effect analysis were performed. The results of the descriptive statistical analysis are shown in the following table:

[0090]

[0091]

[0092] The descriptive statistics and correlation coefficients of each variable are shown in the table above. The results show that safety awareness and safety behavior (r = 0.312, p < 0.01), safety attitude and safety behavior (r = 0.308, p < 0.01), and safety skills and safety behavior (r = 0.236, p < 0.01) are all significantly positively correlated. This provides support for Hypotheses H1, H2, and H3.

[0093] path Effect size SE 95% confidence interval Safety awareness → safe behavior 0.291 0.034 [0.107，0.327] Safety attitude → safety behavior 0.406 0.038 [0.253，0.484] Safety Skills → Safe Behaviors 0.322 0.034 [0.186，0.501]

[0094] The test results of direct effect analysis are as follows:

[0095] As can be seen from the above table, the direct effect value of safety awareness on safety behavior is 0.291, and the 95% confidence interval is [0.107, 0.327], which does not include 0, and the direct effect is significant; the direct effect value of safety attitude on safety behavior is 0.406, and the 95% confidence interval is [0.253, 0.484], which does not include 0, and the direct effect is significant; the direct effect value of safety skills on safety behavior is 0.322, and the 95% confidence interval is [0.186, 0.501], which does not include 0, and the direct effect is significant.

[0096] According to descriptive statistical analysis and direct effect analysis, the verification results of the hypothesis are all valid, that is, workers' safety awareness, safety attitude, and safety skills have a significant positive impact on workers' safety behavior. Therefore, this paper selects safety awareness, safety attitude, and safety skills as the first-level indicators for evaluating the safety behavior of workers in metallurgical enterprises. Starting from the above three dimensions, a corresponding set of safety factors is constructed, and each second-level indicator is used as an evaluation indicator and classified into the corresponding set of safety factors. The evaluation index system of the safety behavior of workers in metallurgical enterprises is obtained, which is as follows:

[0097] Metallurgical enterprise workers' safety awareness is evaluated through four indicators: cognition, attention, experience, and memory regarding safety production. Cognition reflects values, while attention, experience, and memory reflect vigilance. Safety attitude encompasses motivation, will, and commitment, with motivation and commitment reflecting aspirations. Safety skills encompass accident prevention (before an incident), basic safety capabilities (during an incident), and emergency response (after an incident). These three safety factors and ten evaluation indicators cover all aspects of employee safety behavior.

[0098] In order to illustrate the generation process of the evaluation matrix, Figure 2 As shown, the step 10 includes:

[0099] Step 101: Determine the evaluation level range into which each evaluation indicator in the individual evaluation score falls.

[0100] The following specific example is used to illustrate the process of generating an evaluation matrix:

[0101] The pickling workshop of the enterprise collected a total of 55 valid questionnaires from employees. The questionnaires were statistically analyzed and the specific situation is as follows:

[0102] The full score of the questionnaire is 100 points. Individual evaluation scores are divided into five levels: excellent, good, medium, low, and poor. The corresponding scores for each evaluation level range are as follows: excellent (80, 100], good (60, 80], medium (40, 60], low (20, 40], and poor (0, 20). For example, when the score of an evaluation indicator in an employee's individual evaluation score is 82, the score falls into the "excellent" evaluation level range.

[0103] In one embodiment, the statistical results of the safety behavior assessment of employees in each team / position type in the pickling workshop are shown in the following table:

[0104]

[0105]

[0106] like Figure 3 Shown is a statistical chart of safety behavior assessment of employees in each team / position type in a pickling workshop.

[0107] The statistical results of the evaluation grade ranges of the individual evaluation scores of employees in each team / position type in the pickling workshop are shown in the following table:

[0108]

[0109] like Figure 5 The figure shows the distribution of employee safety behavior evaluation levels in each team / position type in the pickling workshop. Among them, the distribution of each level in each team is, from left to right, engineer position, operation position A team, operation position B team, operation position C team and operation position D team.

[0110] From the above statistical results, it can be seen that the evaluation level range of employees' comprehensive performance in individual safety behavior is mainly concentrated in the medium and good levels, while low and excellent account for a relatively small proportion.

[0111] Step 102: Count the distribution of scores of the same evaluation indicator in each evaluation grade interval to obtain the grade distribution ratio of the number of people falling into each evaluation grade interval to the total number of people evaluated for each evaluation indicator.

[0112] For example, in one embodiment, the distribution diagram of the evaluation results of each indicator of individual safety behavior of employees in the pickling workshop is as follows: Figure 4As shown; accordingly, the distribution diagram of the evaluation results of each indicator of safety behavior of employees in a pickling workshop is shown in the following table:

[0113]

[0114]

[0115] Among them, the "Proportion" column in the above table is the proportion of the number of people falling into each evaluation level range to the total number of people evaluated.

[0116] Step 103: For each evaluation indicator, all grade distribution proportions are used as elements to construct a comment set.

[0117] Since individual evaluation scores are divided into five levels: excellent, good, medium, low, and poor, the comment set V is defined as (excellent V1, good V2, medium V3, low V4, poor V5). That is, the elements in the comment set are the distribution proportions of excellent, good, medium, low, and poor corresponding to each evaluation indicator.

[0118] In one embodiment, after a pilot test of 1,000 employees in a metallurgical enterprise, five evaluation level intervals can be classified according to the test results and the employees' daily safety performance, namely, excellent, good, medium, low, and poor, and score ranges can be assigned to the five evaluation level intervals.

[0119] Step 104: Construct an evaluation matrix using the comment sets of all evaluation indicators of the same safety factor set.

[0120] This embodiment of the present invention transforms qualitative evaluations into quantitative ones, providing an overall assessment of employee safety behaviors, which are constrained by multiple factors. Specifically, for each evaluation indicator, a matrix is constructed based on the proportion of each element in the comment set. This matrix is then used to perform a fuzzy comprehensive assessment.

[0121] According to the test score results of each indicator, the ratio of the number of people in each comment set to the total number of people participating in the test is calculated, and the ratio corresponding to the comment set of each evaluation indicator is used as a row element in the evaluation matrix to construct the evaluation matrix of the safety factor set.

[0122] In one embodiment, the evaluation matrix R i :

[0123]

[0124] For example, the evaluation matrix of security awareness is R1:

[0125]

[0126] The evaluation matrix of safety attitude is R2:

[0127]

[0128] The evaluation matrix of safety skills is R3:

[0129]

[0130] The embodiment of the present invention uses the hierarchical analysis method to construct a judgment matrix to test the rationality and consistency of the weight vector. Figure 6 As shown, in step 20, determining the sub-weight vectors of each safety factor set includes:

[0131] Step 201: Acquire multiple evaluation indicators belonging to the same safety factor set, and construct a matrix to be judged between the acquired evaluation indicators.

[0132] First, clarify the goals and hierarchy. Objective level: Evaluate employee safety behaviors. Criteria level: Include three dimensions: Safety Awareness (U1), Safety Attitude (U2), and Safety Skills (U3). Indicator level: Safety Awareness (U1): U11 Cognition, U12 Attention, U13 Experience, and U14 Memory. Safety Attitude (U2): U21 Motivation, U22 Willpower, and U23 Commitment. Safety Skills (U3): U31 Job Safety Operational Ability, U32 Accident Prevention Ability, and U33 Emergency Rescue Ability.

[0133] Then, through expert scoring, a judgment matrix is constructed between the target layer and the criterion layer (U1, U2, and U3). For U1, a judgment matrix is constructed between U1 and u11, u12, u13, and u14; for U2, a judgment matrix is constructed between U2 and u21, u22, and u23; and for U3, a judgment matrix is constructed between U3 and u31, u32, and u33. The process of constructing a judgment matrix based on expert scoring is selected by those skilled in the art based on the specific application scenario and is not limited here.

[0134] Since the employee safety behavior evaluation index system established in the embodiment of the present invention and the determination of the corresponding weights are based on discussions and scoring by metallurgical industry experts, it can comprehensively cover all key elements of employee safety behavior, accurately map the actual influence of each indicator, and ensure the scientificity and reliability of the evaluation results.

[0135] Step 202: normalize each column of the matrix to be judged, sum the normalized matrix row by row, normalize the summation result, and obtain the corresponding candidate weight vector.

[0136] Step 203: Perform a consistency check on the candidate weight vector; when the candidate weight vector fails the consistency check, adjust the candidate weight vector to re-perform a consistency check on the adjusted candidate weight vector until the candidate weight vector passes the consistency check, and determine the candidate weight vector that passes the consistency check as the sub-weight vector.

[0137] A consistency test is performed on each judgment matrix, and the consistency index and consistency ratio are calculated. When the consistency ratio is less than 0.1, the consistency test is passed.

[0138] The process of determining the total weight vector based on the matrix to be judged between each set of safety factors is the same as the process of determining the sub-weight vector based on the matrix to be judged between each evaluation index, which will not be repeated here.

[0139] The three safety factor sets and ten evaluation indicators have different importance for evaluating employee safety behavior, and there are different opinions on this issue. Based on this, the embodiment of the present invention forms a roughly consistent weight allocation scheme through a certain amount of questionnaire surveys and expert brainstorming within the industry, and verifies the scientificity and rationality of the allocated sub-weight vectors through consistency testing.

[0140] In one embodiment, the total weight vector of the employee safety behavior factor set is finally determined to be A=(0.2721, 0.1199, 0.608), the sub-weight vector of the safety awareness factor set is A1=(0.1102, 0.287, 0.5526, 0.0502), the sub-weight vector of the safety attitude factor set is A2=(0.2721, 0.1199, 0.608), and the sub-weight vector of the safety skill factor set is A3=(0.7225, 0.1033, 0.1742).

[0141] In step 20, the use of the sub-weight vectors to weight the corresponding evaluation matrix to obtain the sub-comprehensive evaluation value includes:

[0142] An evaluation matrix of the safety factor set is obtained; and a product of the obtained evaluation index and the sub-weight vector is determined as a sub-comprehensive evaluation value of the safety factor set.

[0143] Determine the evaluation vector B of each sub-goal i ,in:

[0144] B i =A i ·R i

[0145] Among them, i = 1, 2, 3, B1 is the sub-weight vector of safety awareness, B2 is the sub-weight vector of safety attitude, and B3 is the sub-weight vector of safety skills.

[0146] The sub-weight vector of safety awareness is A1 = (0.1102, 0.287, 0.5526, 0.0502), and the sub-comprehensive evaluation value of safety awareness can be obtained as follows:

[0147]

[0148] The weight vector of safety attitude is A2 = (0.2721, 0.1199, 0.608), and the sub-comprehensive evaluation value of safety attitude can be obtained as follows:

[0149]

[0150] The weight vector of safety skills is A3 = (0.7225, 0.1033, 0.1741), and the sub-comprehensive evaluation value of safety skills can be obtained as follows:

[0151]

[0152] like Figure 7 As shown, the embodiment of the present invention constructs a set of safety factors, evaluates the individual safety behavior corresponding to each individual assessment score on multiple safety factors, obtains the sub-comprehensive evaluation value of each individual on different safety factor sets, and determines the evaluation result of the group safety behavior accordingly. After determining the sub-weight vectors of each safety factor set and using the sub-weight vectors to weight the corresponding evaluation matrix to obtain the sub-comprehensive evaluation value, it is also possible to directly evaluate the individual employee safety behavior according to the sub-comprehensive evaluation value to understand the employee safety behavior level, thereby proposing targeted countermeasures and suggestions; in order to obtain the evaluation situation on the dimensions of different safety factor sets, such as Figure 8 As shown, it also includes:

[0153] Step 501: Determine the maximum value of the elements in the sub-comprehensive evaluation value.

[0154] Step 502: Determine the evaluation level interval that the maximum value falls into, so as to obtain the evaluation level to which the maximum value belongs.

[0155] Step 503: Determine the obtained evaluation level as the evaluation result of each safety factor set.

[0156] For example, the sub-comprehensive evaluation value of safety awareness B1 = (0.398, 0.103, 0.353, 0.131, 0.005), each element in the sub-comprehensive evaluation value corresponds to excellent, good, medium, low, and poor, and the evaluation level to which the maximum value belongs is "excellent", and the corresponding proportion is 39.8%. Therefore, according to steps 501 to 503, the safety awareness assessment result of the pickling workshop employees is "excellent".

[0157] For another example, the sub-comprehensive evaluation value of safety attitude B2 = (0.173, 0.267, 0.435, 0.125, 0), the evaluation level to which the maximum value belongs is "medium", and the corresponding proportion is 43.5%. Therefore, according to steps 501 to 503, the safety attitude assessment result of the pickling workshop employee group is "medium".

[0158] For another example, the sub-comprehensive evaluation value of safety skills B3 = (0.363, 0.433, 0.166, 0.034, 0.004), the evaluation level to which the maximum value belongs is "good", and the corresponding proportion is 43.3%. Therefore, according to steps 501 to 503, the safety attitude assessment result of the pickling workshop employee group is "good".

[0159] In step 30, if Figure 9 As shown, the sub-comprehensive evaluation values of all safety factor sets are used to construct a sub-goal evaluation matrix; the sub-goal evaluation matrix is weighted using the total weight vector to obtain a total comprehensive evaluation value including:

[0160] Step 301: Obtain the sub-comprehensive evaluation value of each safety factor set, and use the obtained sub-comprehensive evaluation value as an element to form the sub-goal evaluation matrix using each element.

[0161] Form the sub-goal evaluation matrix R=(B1,B2,…,B S ) T .

[0162] Step 302: The product of the total weight vector and the sub-goal evaluation matrix is determined as the total comprehensive evaluation value.

[0163] Sub-goal evaluation matrix R:

[0164]

[0165] The total weight vector is A = (0.2721, 0.1199, 0.608), and the total comprehensive evaluation value B of employee safety behavior can be obtained as:

[0166]

[0167] In order to obtain the evaluation results of group safety behavior, such as Figure 10 As shown, the step 40 includes:

[0168] Step 401: The product of the total weight vector and the total comprehensive evaluation value is determined as the total target evaluation vector.

[0169] Obtain the total target evaluation vector C:

[0170] C=A·B

[0171] Step 402: Determine the maximum value of the elements in the total target evaluation vector, and determine the evaluation level interval into which the maximum value falls, so as to obtain the evaluation level to which the maximum value belongs.

[0172] Determine the safety behavior evaluation level of group employees based on the principle of maximum affiliation.

[0173] Step 403: The obtained evaluation level is determined as the evaluation result of the group safety behavior.

[0174] Output statistical results, analyze and evaluate the results from multiple dimensions and angles according to needs, identify weak links, and provide targeted improvement opinions and suggestions.

[0175] According to the principle of maximum membership, the comment "excellent" accounts for the largest proportion, which is 35.0%. Therefore, the evaluation result (ie, evaluation level) of the safety behavior of the pickling workshop employees is "excellent".

[0176] The above analysis shows that the safety behavior evaluation of employees in the company's pickling mill workshop is excellent, with the ratings for safety awareness, safety attitude, and safety skills being excellent, fair, and good, respectively. Within the "safety awareness" factor set, the secondary indicator scores, from high to low, are experience, cognition, attention, and memory. Within the "safety attitude" factor set, the secondary indicator scores, from high to low, are commitment, motivation, and will. Within the "safety skills" factor set, the secondary indicator scores, from high to low, are accident prevention ability, job safety operation ability, and emergency rescue ability.

[0177] like Figure 11 As shown, the embodiment of the present invention provides a set of evaluation processes for group safety behavior evaluation levels, which can effectively quantify the level of group safety behavior and has wide applicability; the evaluation process can be used for safety behavior evaluation of employees at multiple levels such as work teams, work areas, workshops, branches, and companies in metallurgical enterprises to meet the safety behavior evaluation needs of different levels of the enterprise.

[0178] In an optional embodiment, in order to further improve the safety behavior level of employees in the pickling workshop of this enterprise, the following suggestions are put forward:

[0179] (1) Strengthen the construction of corporate safety culture. The formation of employees' safety awareness and safety attitude is inseparable from the company's safety culture. A positive and positive incentive safety culture can mobilize the potential of employees to take the initiative. The test results show that the current safety awareness of employees in the pickling workshop mainly depends on "experience". When building a safety culture, the pickling workshop can focus on "memory" and "attention", that is, through repeated and multiple methods to make safety awareness subtly instilled, such as eye-catching safety slogans, safety warnings, efficient and multiple safety education, direct and clear safety accident case studies, etc. Secondly, it is recommended to establish an incentive mechanism and assessment method to improve safety execution and ensure clear rewards and punishments.

[0180] (2) Strengthen the training of accident prevention capabilities. In accordance with the requirements of the "Guidelines for Curbing Major Accidents by Addressing Both the Symptoms and the Root Causes", "Dual Prevention Mechanism of Safety Risk Grading Control and Hidden Danger Investigation and Management", and "Guidebook for Identifying and Preventing Major Hazard Factors in the Metallurgical Industry", we will continuously improve our awareness of safety risks. At the same time, based on the actual situation of the pickling workshop, we will refine the safety risk identification, analysis and control guidelines. Relevant personnel such as process, equipment, safety, inspection and maintenance will participate in the guidance of each operating area and team to carry out hazard source identification, analysis, assessment and classification, formulate targeted safety risk control measures, continuously improve the safety risk control list, and strengthen safety risk education and skills training for the identified and assessed safety risks to ensure that all managers and employees have a basic understanding of safety risks and prevention and emergency measures.

[0181] (3) Improve emergency response and rescue capabilities. To improve the quality of emergency rescue team building, the pickling workshop should improve the emergency organization, clarify the division of responsibilities, form an emergency command and response team with smooth instructions, information sharing, and rapid response, formulate emergency plan training and drill plans, and implement daily training. With the help of activities such as "Safe Production Month" and "Fire Safety Month", through various methods such as competition-driven training, video teaching, desktop drills, functional drills, and comprehensive drills, combined with similar emergency response cases at home and abroad, comprehensive verification and systematic improvement of the emergency team's training effect, response capabilities and overall level. Strengthen the allocation and daily maintenance of emergency materials. According to the local climate, dangerous and harmful factors, and working environment, all kinds of emergency materials, equipment and equipment should be allocated in accordance with the law. The responsibility areas and responsibilities for daily maintenance should be clarified, and dedicated personnel should be assigned to manage them. Formulate a list of emergency materials and equipment. In accordance with the requirements of regional responsibility system and grid management, strengthen the construction and update management of information ledgers such as material quantity, management personnel, contact information, storage location, and test results. Establish visual daily inspection standards for emergency materials to ensure the quality of daily inspection and maintenance, and promote the timely availability of emergency materials, equipment and equipment for the pickling workshop and related parties.

[0182] Example 2:

[0183] like Figure 12, is a schematic diagram of an architecture of a device for quantifying the safety behavior risk index of metallurgical industry employees according to an embodiment of the present invention. The device for quantifying the safety behavior risk index of metallurgical industry employees according to this embodiment includes one or more processors 21 and a memory 22. Figure 12 A processor 21 is taken as an example.

[0184] The processor 21 and the memory 22 may be connected via a bus or other means. Figure 12 The bus connection is taken as an example.

[0185] Memory 22, as a nonvolatile computer-readable storage medium, can be used to store nonvolatile software programs and nonvolatile computer-executable programs, such as the method for quantifying the safety behavior risk index of metallurgical industry employees in this embodiment. Processor 21 executes the method for quantifying the safety behavior risk index of metallurgical industry employees by running the nonvolatile software program and instructions stored in memory 22.

[0186] The memory 22 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state memory device. In some embodiments, the memory 22 may optionally include a memory remotely located relative to the processor 21, and such remote memory may be connected to the processor 21 via a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0187] The program instructions / modules are stored in the memory 22, and when executed by the one or more processors 21, the method for quantifying the safety behavior risk index of employees in the metallurgical industry in the above-mentioned embodiment is executed, for example, each step of the method for quantifying the safety behavior risk index of employees in the metallurgical industry in the embodiment of the present invention described above is executed.

[0188] An embodiment of the present invention further provides a non-volatile computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions are executed by one or more processors, for example Figure 12 A processor 21 can enable the above one or more processors to execute the metallurgical industry employee safety behavior risk index quantification method in the specific embodiment of the present invention, for example, to execute the various steps of the metallurgical industry employee safety behavior risk index quantification method described above in the embodiment of the present invention; it can also realize Figure 12 The various modules and units described above; or executing the metallurgical industry employee safety behavior risk index quantification method in the specific embodiment of the present invention, for example, executing the various steps of the metallurgical industry employee safety behavior risk index quantification method of the embodiment of the present invention described above; it can also be realized Figure 12 The various modules and units described.

[0189] It is worth noting that the information interaction, execution process, etc. between the modules and units within the above-mentioned devices and systems are based on the same concept as the processing method embodiment of the present invention. The specific content can be found in the description of the method embodiment of the present invention and will not be repeated here.

[0190] Those skilled in the art will understand that all or part of the steps in the various methods of the embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), a disk or an optical disk, etc.

[0191] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for quantifying the safety behavior risk index of employees in the metallurgical industry, characterized by: include: Analyze individual evaluation scores to obtain the grade distribution ratio of each evaluation indicator; Using the grade distribution ratio, an evaluation matrix between a set of safety factors and corresponding evaluation indicators is constructed; wherein a set of safety factors includes multiple evaluation indicators; Determine a sub-weight vector for each safety factor set; use the sub-weight vector to weight the corresponding evaluation matrix to obtain a sub-comprehensive evaluation value; Determine a total weight vector of all safety factor sets; construct a sub-goal evaluation matrix using the sub-comprehensive evaluation values of all safety factor sets; and weight the sub-goal evaluation matrix using the total weight vector to obtain a total comprehensive evaluation value. A total target evaluation vector is generated according to the total weight vector and the total comprehensive evaluation value to obtain an evaluation result of the group safety behavior.

2. The method for quantifying the safety behavior risk index of employees in the metallurgical industry according to claim 1 is characterized in that: include: The product of the total weight vector and the total comprehensive evaluation value is determined as the total target evaluation vector; Determining the maximum value of the elements in the total target evaluation vector, and determining the evaluation grade interval in which the maximum value falls, so as to obtain the evaluation grade to which the maximum value belongs; The obtained evaluation level is determined as the evaluation result of the group safety behavior.

3. The method for quantifying the safety behavior risk index of employees in the metallurgical industry according to claim 1 is characterized in that: include: Determining the evaluation level range into which each evaluation indicator in the individual evaluation score falls; Statistically calculate the distribution of scores for the same evaluation indicator in each evaluation level interval to obtain the proportion of the number of people falling into each evaluation level interval to the total number of people evaluated for each evaluation indicator; For each evaluation indicator, all the grade distribution proportions are used as elements to construct a comment set; An evaluation matrix is constructed using the comment set of all evaluation indicators of the same safety factor set.

4. The method for quantifying the safety behavior risk index of employees in the metallurgical industry according to claim 1 is characterized in that: include: Obtaining a sub-comprehensive evaluation value of each safety factor set, and using the obtained sub-comprehensive evaluation value as an element to form the sub-goal evaluation matrix using each element; The product of the total weight vector and the sub-goal evaluation matrix is determined as the total comprehensive evaluation value.

5. The method for quantifying the safety behavior risk index of employees in the metallurgical industry according to claim 1 is characterized in that: include: Acquire multiple evaluation indicators belonging to the same safety factor set, and construct a matrix to be judged between the acquired evaluation indicators; Normalizing each column of the matrix to be judged, summing the normalized matrix row by row, and normalizing the summation result to obtain a corresponding candidate weight vector; Performing a consistency check on the candidate weight vector; When the candidate weight vector fails the consistency check, the candidate weight vector is adjusted to re-perform the consistency check on the adjusted candidate weight vector until the candidate weight vector passes the consistency check, and the candidate weight vector that passes the consistency check is determined as the sub-weight vector.

6. The method for quantifying the safety behavior risk index of employees in the metallurgical industry according to claim 1 is characterized in that: Also includes: Construct evaluation indicators; Classify similar evaluation indicators into one safety factor set to obtain multiple safety factor sets; Conduct a safety behavior questionnaire assessment on employees to obtain an individual assessment score for each employee.

7. The method for quantifying the safety behavior risk index of employees in the metallurgical industry according to claim 6 is characterized in that: Also includes: Determining the maximum value of the elements in the sub-comprehensive evaluation value; Determining the evaluation grade interval into which the maximum value falls, so as to obtain the evaluation grade to which the maximum value belongs; The obtained evaluation level is determined as the evaluation result of each safety factor set.

8. The method for quantifying the safety behavior risk index of metallurgical industry employees according to any one of claims 1 to 7, characterized in that: include: An evaluation matrix of the safety factor set is obtained; and a product of the obtained evaluation index and the sub-weight vector is determined as a sub-comprehensive evaluation value of the safety factor set.

9. A device for quantifying the safety behavior risk index of employees in the metallurgical industry, characterized in that: The device for quantifying the safety behavior risk index of employees in the metallurgical industry includes at least one processor and a memory, and the at least one processor and the memory are connected via a data bus. The memory stores instructions that can be executed by the at least one processor. After being executed by the processor, the instructions are used to implement the method for quantifying the safety behavior risk index of employees in the metallurgical industry as described in any one of claims 1-8.

10. A non-volatile computer storage medium, characterized in that The computer storage medium stores computer-executable instructions, which are executed by one or more processors to complete the method for quantifying the safety behavior risk index of metallurgical industry employees as described in any one of claims 1-8.

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