Social benefits of the mine occupational health and safety management systems of mines in China and Sweden based on a fuzzy analytic hierarchy process: A comparative study

Abstract

In this study, AHP and FAHP models are carried out to comprehensively evaluate the social benefits of the occupational health and safety management systems of a mine located in the southwest of Hubei Province, China and a mine located in Luleå, Sweden. Reasonable factor sets, decision sets, weight sets, and experience in consistency are utilized in order to empirically analyze on a case-by-case basis. The results demonstrate that the social benefit of the mine occupational health and safety management system for the mine in China is of the “general” rank; thus, it needs to be further improved. In contrast, the system for the mine in Sweden is of the “relatively good” rank. The fundamental difference lies in the degree of emphasis placed on people. The results of this study provide a direction for improving the further development of mine occupational health and safety management systems.

Keywords

FAHP social benefits OHSAS

1 Introduction

OHSAS18001 occupational health and safety is an advanced modernized production safety management method that is widely carried out worldwide. It focuses on systematic ideas of health and safety management, and the aim of establishing a complete set of occupational health and safety mechanisms is to control and reduce occupational health and safety risks, minimize the occurrences of production accidents, and reduce occupational disease [8].

With the frequent occurrence of domestic mine accidents coupled with the reduction of available mineral resources, society has become more focused on the dual importance of economic benefits and social benefits.

In particular, humanization, social and economic structures, and resource recycling soon have attracted a great deal of attention. In response, there is a great need for the development of a reasonable analysis and evaluation method for the social benefits evaluation of mine occupational health and safety management systems [9].

Because the social benefits of these systems are inherently vague, it is necessary to utilize a tool known as the fuzzy set theory. Zadeh first introducedfuzzy set theory to deal with the vagueness of human thought, and the method was oriented to the rationality of uncertainty due to imprecision or vagueness. A major contribution of the fuzzy set theory is its capability to represent vague data. A fuzzy set is a class of objects with a membership function ranging between one and nine. Fuzzy set theory resembles human reasoning in its use of approximate information and uncertainty to generate decisions. It was specifically designed to mathematically represent uncertainty and vagueness. Fuzzy set theory implements groupings of data with boundaries that are not sharply defined (i.e., fuzzy). Any methodology or theory implementing “crisp” definitions, such as classical set theory, arithmetic, and programming, may be “fuzzified” by generalizing the concept of a crisp set to a fuzzy set with blurredboundaries [2].

The geographical positions and natural conditions of mines vary greatly and are influenced by many factors that are hard to accurately calculate. Therefore, in this paper, the fuzzy comprehensive evaluation method is adopted in order to conduct an empirical analysis of the social benefits of the OHSAS systems of a mine located in the southwest of Hubei Province, China and a mine located in Luleå, Sweden. This study provides valuable guidance for the comprehensive development of China mines. It also contributes to research on a model of occupational health and safety satisfaction evaluation basedon SEM.

2 Comprehensive evaluation indicator system on social benefits of mine OHSAS

The comprehensive evaluation indicator system of the social benefits of a mine OHSAS is related to mine safety production, operations, community, society, and so on. The mutual contact and mutual restriction factors constitute an organic whole, which is the basis of the comprehensive evaluation. Based on analyzing the mine safety status and investigating the community residents as well as following the principle of covering all aspects of an operating system and in the ways of man- machine-environment system analysis, the total target layer is OHSAS 18001 social benefits evaluation indicators. There are six first-grade evaluation indicators and nineteen second-grade evaluation indicators included in this study [8]. This can be seen in Fig. 1.

In Fig. 1, the indicators refer to the following:

U—mine OHSAS 18001 social benefits evaluation indicators; U₁—influence on humanization; U₂—influence on comprehensiveness; U₃—influence on sustainability; U₄—influence on social economy; U₅—influence on natural resources; U₆—influence on ecology and environment; U₁1—influence on people’s health care; U₁2—influence on people’s satisfaction with OHSAS; U₁3—influence on investment in OHSAS; U₁4—influence on improvement of people’s education and science services; U₂1—influence on accidents, such as industrial injuries and fire injuries; U₂2—influence on harmony and stability in community; U₂3—influence on community satisfaction with social conditions; U₃1—influence on environmental sustainable development; U₃2—influence on people’s customs; U₃3—influence on social culture; U₄1—influence on employment rate; U₄2—influence on people’s economic life; U₄3—influence on economic structure; U₅1—influence on natural resources consumption coefficient; U₅2—influence on natural resources comprehensive utilization benefits; U₅3—influence on comprehensive efficiency saving of natural resources; U₆1—influence on pollution damage to natural resources; U₆2—influence on damage to green areas and the forest; and U₆3—influence on ecological management cost.

2.1 U₁-Influence on humanization

Humanization is the development of well-rounded individuals. The project implementation must primarily impact the following aspects of society: health care, satisfaction with OHSAS, investment in OHSAS, and improvement in education and science services.

2.2 U₂-Influence on comprehensiveness

It is necessary that the overall project meets certain societal needs and adapts to society according to the following aspects: accident prevention (such as industrial injuries and fire injuries), promotion of community harmony and stability, and community satisfaction with social conditions.

2.3 U₃-Influence on sustainability

The sustainable benefit is the sum of both the tangible and intangible benefits of the project, which primarily consist of the following: influence on environmental sustainable development, on people’s customs, and social culture.

2.4 U₄-Influence on social economy

This indicator focuses on issues such as employment benefits, income distribution, and economic life through such aspects as the influence on employment rate, on people’s economic life, and on economic structure.

2.5 U₅-Influence on natural resources

Specific indicators of the impact on natural resources include the water, land, forest, mineral, energy, and other resources consumption coefficients; natural resources comprehensive utilization benefits; and comprehensive efficiency saving of natural resources.

2.6 U₆-Influence on ecology and environment

This indicator includes the following three aspects: influence on the pollution damage to natural resources, the damage to green areas and the forest, and the ecological management cost.

3 Mine comprehensive evaluation model on the social benefits of the occupational health and safety management system based on a fuzzy analytic hierarchy process

In the evaluation process, there are no qualitative indicators. Instead, they must be transformed into quantitative indicators through specific processing methods that do not affect the evaluation process and results. This method can overcome limitations of the analytic hierarchy process, the subjectivity of human thought, and the fuzziness of individual judgment [1, 5, 9].

The fuzzy AHP method is used to evaluate the social benefits of the mine occupational health and safety management system, including building evaluation factor sets, evaluation weight sets, evaluation decision sets, consistency checking, fuzzy comprehensive evaluation matrix, and comprehensive fuzzy evaluation.

3.1 Evaluation factor sets

The social benefits evaluation of the mine occupational health and safety management system includes six first-grade evaluation indicators and nineteen second-grade evaluation indicators. The six first-grade assessment indicators are expressed below: $U = {U_{1}, U_{2}, U_{3}, U_{4}, U_{5}, U_{6}}$

In the equation, each indicator refers to that listed in Fig. 1. The above six factors need to be further refined, and the refined factors are as follows: $U_{1} = {U_{11}, U_{12}, U_{13}, U_{14}}$ $U_{2} = {U_{21}, U_{22}, U_{23}}$ $U_{3} = {U_{31}, U_{32}, U_{33}}$ $U_{4} = {U_{41}, U_{42}, U_{43}}$ $U_{5} = {U_{51}, U_{52}, U_{53}}$ $U_{6} = {U_{61}, U_{62}, U_{63}}$

Likewise, in the equation above, each indicator refers to that listed in Fig. 1.

3.2 Evaluation decision sets

The social benefits evaluation indicators of OHSAS can be divided into four grades: very good, relatively good, general, and not good [6]. Thus, the evaluation decision sets can be expressed as below: $V = {V_{1}, V_{2}, V_{3}, V_{4}}$

In the equation, the terms are as follows: V₁ – very good V₂ – relatively good V₃ – general V₄ – notgood.

3.3 Evaluation weight sets

In this paper, the importance of the indicators is scored by the relevant experts in order to determine the weight value of each indicator in this factor, and the results are used to construct the judgment matrix that employs the 1–9 scale method proposed by A.L. Saatyin order to determine the specific values. If the parameter on the horizontal axis is less important than the parameter on the vertical axis, it is a value between 1 and 9. If the opposite is true, it is a value between the reciprocals of 1/2 and 1/9 [4; Table 1].

3.4 Consistency checking

The test index for the consistency of a judgment is the following: CR = CI/RI. In the equation, CI = (λ-n)/(n – 1), and n is the order of the judgment matrix. RI is the random consistency index of the judgment matrix [3]. Suppose the set RI is as shown in Table 2. If CR ≤10%, the matrix is consistent, and AHP can be continued. If CR >10%, it requires revision because the matrix is not consistent. In this paper, the root mean square method is used to carry out the consistency test. The model calculation procedure is as follows:

Multiply the elements of B by line $u_{ij} = \prod_{j = 1}^{n} b_{ij}$ .

The nth root of the resultant product $u_{i} = \sqrt[n]{u_{ij}}$ .

Normalize the root mean square vector and obtain the feature vector $W_{i} = \frac{u_{i}}{\sum_{i = 1}^{n} u_{i}}$ .

Calculate the largest eigenvalue of the judgment matrix $λ_{max} = \sum_{i = 1}^{n} \frac{(AW)_{i}}{(nW)_{i}}$ .

Calculate CR = CI/RI = (λ-n)/(n – 1)/ RI.

3.5 Fuzzy comprehensive evaluation matrix

For the i indicator, the membership degree of each social benefit is the fuzzy subset R_i = (r_i1, r_i2, …, r_im). The fuzzy comprehensive judgment matrix of each indicator is as follows: $R = [\begin{matrix} r_{11} & r_{12} & \dots & r_{1 m} \\ r_{21} & r_{22} & \dots & r_{2 m} \\ \dots & \dots & \dots & \dots \\ r_{n 1} & r_{n 2} & \dots & r_{nm} \end{matrix}]$

It is a fuzzy relation matrix from U to V [7].

3.6 Comprehensive fuzzy evaluation

The model of the social benefits of the mine occupational health and safety management system based on FAHP follows a step-by-step calculation in order to obtain the membership vectors of each layer, and the weight set and factor evaluation matrix are combined to make the fuzzy matrix synthesis operation [4]. The evaluation results of each level are obtained according to the fuzzy comprehensive evaluation principle: B_i = W_i . R_i

4 Empirical analysis

Two mines are used as examples in this study. One is located in the southwest of the Hubei Province in the central part of China, and it has general hydrogeological conditions. Additionally, OHSAS18001 has currently been utilized for the site for more than three years. As a result, it has a good reputation in the society as well as the local community. The second mine is located in Luleå in northern Sweden, east of Lake Rosa. OHSAS18001 was employed for this site several years ago, and it too has a high reputation. Utilizing these the two mines as an example, this paper evaluates, analyses, and compares the social benefits of OHSAS through a fuzzy analytic hierarchy process (FAHP) method and a fuzzy comprehensive evaluation model.

4.1 The consistency test of indicator weight

In order to ensure the validity and consistency of the evaluation model, the indicators need to be tested. Additionally, twelve Chinese individuals, including senior director auditors, academics, staff members, and residents, were invited to judge the importance of the indicators in the AHP method [9]. In this paper, the root mean square method is used to carry out the consistency test. The calculation procedure of the U_c layer subordinate indicator weight is shown in Table 3. According to the aforementioned formulas, the following is obtained: $u_{ij} = \prod_{j = 1}^{n} b_{ij}$ = 0.2500, 16.0000, 0.2500, 0.2500, 16.0000; u_i = $\sqrt[n]{u_{ij}}$ = 0.7937, 1.5874, 0.7937, 0.7937, 1.5874, 0.7937; $W_{i} = \frac{u_{i}}{\sum_{i = 1}^{n} u_{i}}$ = 0.1250, 0.2500, 0.1250, 0.1250, 0.2500, 0.1250; λ_max = 6.0000; CR = CI/RI = (λ-n)/(n – 1)/1.24 = 0 < 0.1. Thus, the result has passed the consistency test. Additionally, the calculation result of the U_s layer subordinate indicator weight is as follows: $u_{ij} = \prod_{j = 1}^{n} b_{ij}$ = 96.0000, 1.3333, 0.1250, 0.0625, 4.0000, 0.2500; $u_{i} = \sqrt[n]{u_{ij}}$ = 2.1398, 1.0491, 0.7071, 0.6299, 1.2599, 0.7937; $W_{i} = \frac{u_{i}}{\sum_{i = 1}^{n} u_{i}}$ = 0.3250, 0.1600, 0.1070, 0.0960, 0.1910, 0.1210; λ_max = $\sum_{i = 1}^{n} \frac{(AW)_{i}}{(nW)_{i}}$ = 6.1418; CR = CI/RI = (λ-n)/(n – 1)/1.24 = 0.0228 < 0.1.Thus, the result has passed the consistency test. From Table 3, it can be determined that the weights of the influence on humanization, comprehensiveness, sustainability, social economy, natural resources, ecology and environment, and the social benefits evaluation indicator of OHSAS are as follows:

$\begin{matrix} W_{c} = [0.1250 0.2500 0.1250 0.1250 \\ 0.2500 0.1250] \end{matrix}$ and $\begin{matrix} W_{s} = [0.3250 0.1600 0.1070 0.0960 \\ 0.1910 0.1210] \end{matrix}$

Where W_c represents the weight of the mine located in China, and W_s represents the weight of the mine located in Sweden. The indicators U and B are the same. Furthermore, as shown in Tables 4 through 9, all indicators pass the consistency test. (The operation method is the same as that used in Table 3). The corresponding weights of the U_c and U_s layers from U₁ to U₆ areas follows: $W_{c 1} = [0.4820 0.1170 0.2180 0.1830],$ $W_{c 2} = [0.2500 0.2500 0.5000],$ $W_{c 3} = [0.6370 0.1150 0.2580],$ $W_{c 4} = [0.1170 0.2680 0.6250],$ $W_{c 5} = [0.1050 0.2580 0.6470],$ $W_{c 6} = [0.2970 0.5400 0.1630],$ $W_{s 1} = [0.3320 0.4240 0.1810 0.0630],$ $W_{s 2} = [0.5280 0.3330 0.1390],$ $W_{s 3} = [0.3200 0.5580 0.1220],$ $W_{s 4} = [0.5280 0.3320 0.1400],$ $W_{s 5} = [0.1420 0.4290 0.4290],$ and $W_{s 6} = [0.5280 0.3330 0.1390] .$

4.2 Single factor evaluation matrix

According to the actual mine OHSAS18001 operation and access to relevant information, this paper scores each second indicator on the basis of a comprehensive consideration of the expert opinions. The results of which are shown in Table 10 [9].

4.3 Fuzzy comprehensive evaluation

The first-grade fuzzy comprehensive evaluation is carried out according to each second-grade indicator weight W_i and each corresponding single factor matrix R_i of the U_c layer.

$\begin{matrix} B_{c 1} = W_{c 1} . R_{c 1} = \\ (0.4820, 0.1170, 0.2180, 0.1830) . \\ [\begin{matrix} 0.2 0.4 0.3 0.1 \\ 0.1 0.2 0.5 0.2 \\ 0.2 0.3 0.4 0.1 \\ 0.2 0.2 0.5 0.1 \end{matrix}] \\ = (0.1883, 0.3182, 0.3818, 0.1117) . \end{matrix}$

The evaluation grade membership of the five other first-grade indicators of the U_c layercan be calculated as shown in Table 11. The U_s layer is included.

The fuzzy comprehensive evaluation is carried out for the U_c and U_s layers by using the result of the first-grade fuzzy evaluation:

$\begin{matrix} B_{c} = W_{c} . R_{c} = (0.1250, 0.2500, 0.1250, \\ 0.1250, 0.2500, 0.1250) . \\ [\begin{matrix} 0.1883 0.3182 0.3818 0.1117 \\ 0.2250 0.4750 0.2750 0.0250 \\ 0.2887 0.2278 0.3782 0.1268 \\ 0.2522 0.2673 0.3270 0.1635 \\ 0.2667 0.2020 0.4040 0.1373 \\ 0.1866 0.2540 0.4297 0.1297 \end{matrix}] \\ = (0.2360, 0.3007, 0.3570, 0.1063) \\ (normalized treatment) \end{matrix}$

$\begin{matrix} B_{s} = W_{s} . R_{s} = \\ (0.3250, 0.1600, 0.1070, 0.0960, 0.1910, 0.1210) . \\ [\begin{matrix} 0.2089 0.9428 0.2613 0.1000 \\ 0.2333 0.4667 0.2667 0.0333 \\ 0.3436 0.3238 0.2762 0.0564 \\ 0.3388 0.3720 0.2280 0.0612 \\ 0.2429 0.2000 0.4000 0.1571 \\ 0.1611 0.2333 0.4528 0.1528 \end{matrix}] \\ = (0.2404, 0.3511, 0.3102, 0.0983) \\ (normalized treatment) \end{matrix}$

According to the comprehensive evaluation result, the mine in China achieves a 0.2360 probability of “very good” social benefits, a 0.3007 probability of “relatively good”, a 0.3570 probability of “general”, and a 0.1063 probability of “not good”. According to the maximum membership degree [7], the implementation of an occupational health and safety system in the mine in China would result in social benefits at the “general” level, which still needs to be further improved. However, in Sweden, there is a 0.2404 probability of “very good” social benefits, a 0.3511 probability of “relatively good”, a 0.3102 probability of “general”, and a 0.0983 probability of “not good”. Thus, according to the maximum membership degree, the implementation of an occupational health and safety system in the mine in Sweden would result in “relatively good” social benefits.

5 Conclusion

The multi-stage evaluation indicators system of the mine OHSAS social benefits was implemented by the Delphi and FAHP methods. The results indicated that the social benefits level from the OHSAS in Sweden is higher than that from the OHSAS in China, especially in the weight aspects of the influence on people’s satisfaction with OHSAS.That is to say, the mine in Sweden puts more emphasis on people.

This study provides an improved direction for the development of an occupational health and safety management system for mines and provides a certain reference value for the actual work.

By using the fuzzy comprehensive evaluation method, numerous factors that affect the system operation can be comprehensively considered, and the social benefits of amine can be comprehensively and objectively evaluated so as to improve the efficiency of the system. For future work, the research in this area should be strengthened, and the constructed model should be optimized.

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