Risk pre-control mechanism of mines based on evidence-based safety management and safety big data

doi:10.21203/rs.3.rs-2454988/v1

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Risk pre-control mechanism of mines based on evidence-based safety management and safety big data

https://doi.org/10.21203/rs.3.rs-2454988/v1

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published 07 Oct, 2023

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The overexploitation of mineral resources and the heavy use of mineral resources have caused serious environmental damage. The growing problem of mine safety also directly threatens the personal safety of the surrounding population and hinders the development of the local economy. Evidence-based safety eliminates the reliance on intuition and unsystematic aspects of traditional safety management systems by taking into account the actual production situations on site, making safety decision-making activities more scientific. However, there is frequently a lag in the transformation and feedback of evidence information, which obstructs the realization of effective safety decision-making activities. From the perspective of process safety management risk analysis and the transformation of safety big data and safety evidence, this paper proposes a new mine risk pre-control mechanism. First and foremost, based on process safety management, evidence-based safety is successfully applied to mine risk control. Secondly, from the perspective of information transformation, a mine risk pre-control mechanism based on evidence-based safety management and safety big data is established. Finally, taking mine open area monitoring as an example, the application analysis of the mine risk pre-control mode constructed above is carried out. The risk pre-control mechanism proposed in this paper provides a new idea for the practice of mine risk management.

safety management

safety big data

risk analysis of mines

evidence-based

process safety management

At present, the development and demand of mineral resources have been growing for a long time. As an important infrastructure in the development of mineral resources, mines have major environmental pollution and risk hazards. Mineral resources are the main energy foundation of the word and one of the most important parts of national economy. In recent years, in particular, with the development of the mining industry, the complexity of technology and the lag in management updates have made accident prevention a more intractable problem. At the same time, with the improvement of infrastructure and rapid socio-economic development, the overexploitation of mineral resources and the heavy use of mineral resources have caused serious environmental damage (Krupskaya et al.,2022; Wang, et al., 2020). For example, unjustified mining patterns would result in the destruction of large amounts of construction land, as mining activities would result in a variety of wastes. Mining will also cause the underground to be emptied, affect the stability of mountains and slopes, increase the risk of residents above empty areas, and lead to a series of geological hazard activities such as landslides. In addition, the overexploitation of mineral resources can lead to various water environmental problems, as well as atmospheric pollution resulting from waste gas, dust and waste residue from production processes (Paluchamy and Mishra, 2022). Especially in the past two years, with the national promotion of carbon compliance and carbon neutrality, the problem of energy conservation and emission reduction of mining enterprises has become increasingly prominent. Traditional safety and environmental management methods are mostly based on managerial experience, and to a certain extent, they can effectively contain accidents. With the advent of the information age, a massive amount of original data has accumulated and is growing exponentially. However, current management methods can no longer meet the basic needs of intrinsic safety; consequently, the technical defects of safety management methods have gradually become the primary cause of accidents (Wang et al., 2016).

The existence of accident, emergency and random factors in the mine system brings difficulties and challenges to safety production, and reasonable safety management methods can reduce the hidden risk of production. Many scholars have discussed a variety of safety management methods from different perspectives: Paul et al. (Paul and Maiti, 2007) discussed the mechanism of accidents by analyzing the behavior characteristics of personnel in mine disasters; Faced with the problems existing in the traditional safety management methods, Li et al. (Li et al., 2009) constructed a closed-loop structure for a mine safety management system in terms of the barrel theory and analyzed the weak links in the process of safety production. Zhang et al. (Zhang et al., 2022) evaluated and improved the sustainable safety performance of a petrochemical plant from the perspective of human behavior factors, and pointed that BBS (behavior-based safety) management can reduce occupational injuries and accidents. Other mine practitioners and safety professionals have also looked for more scientific methods of safety management (Abdelhamid and Everett, 2000; Kennedy and Kirwan, 1998; Khan et al., 2016). The above safety management methods support accident prevention to a certain extent, but some deficiencies remain: a. The safety management methods are most often carried out by safety management personnel using personal experience, which often leads to one-sided and mechanical imitation of safety decision-making; b. Traditional safety management activities are limited to macro safety inspections, which makes it easy to ignore potential microscopic risks in the complex production process; c. Traditional safety decision-making activities draw lessons after the occurrence of accidents, resulting in hysteresis in the acquisition of risk information and risk prevention; d. Traditional safety management activities are mostly single-point prevention and control, which often ignores key factors related to safety production, as a consequence, system analysis methods are open to discussion; e. Management methods frequently ignore the potential risk information evoked by the gestating accident, but only by obtaining the risk information can we further guide the safety management personnel to make correct safety decisions (Yang, 2012).

Some scholars believe that the failure of safety management activities results from unsuccessful corporate organization activities (Mitropoulos, 2005; Xue and Fu, 2018), but the essence of safety management activities are safety decision-making activities carried out by obtaining relevant information. The nonstandard acquisition of risk information can lead to the failure of safety decision-making activities and ultimately trigger accidents. Wang et al. (Wang, et al., 2017) proposed an evidence-based safety (EBS) management method, which is mainly used to bridge the gap between safety management research and actual engineering production practice. Through theoretical analysis, it solves the problem of safety decision-making by building on the best scientific evidence. The term "evidence-based" is derived from medicine (David and David, 1997; Alvan, et al., 1997; Grol and Grimshaw, 1999)and after nearly 30 years of development, "evidence-based" ideas have penetrated into many fields, as the unique perspective, scientific methods and interdisciplinary nature of this concept have produced revolutionary influences in many disciplines (Miller and Forrest, 2001; Neely et al., 2021; Gert, 2010; Susan et al., 2010; Micheal and Mike, 2004; Oakley, 2010). The objectivity of the "evidence-based" idea has been fully reflected in its application; it can also provide a scientific theoretical framework for the efficient safety management of mining enterprises.

In response to disaster risks, governments and safety regulatory agencies in some countries have established process safety management (PSM) mechanisms (Knegtering and Pasman, 2009; Kwon, 2006), which are aimed at producing full-time domain processes. PSM mechanisms use a series of methods, such as risk identification, risk evaluation, risk decision-making and program execution, to carry out an uninterrupted improvement activity (Khan, et al., 2015). From the PSM perspective (Kletz, 1999; Planas et al., 2014), mine disaster risk is a manifestation of hidden dangers, while mine accidents are the extension of hidden dangers, and there is often a correlation between them. Within the limit that the mine safety system can maintain, even if there is a disaster risk, safe production can continue. However, when the risk exceeds the disaster threshold that the mine itself can manage, it will evolve into a hidden danger. As a series of risks evolve into hidden dangers, various hidden dangers in the spatial sequence will influence each other and gradually increase; this stimulates the disaster chain, which will obtain energy, and disasters and accidents will occur accordingly. Obviously, the effective acquisition of management methods and risk information is a prerequisite for preventing risks from turning into accidents. Many scholars have conducted research in the field of risk control: Cao et al. (Cao et al., 2012) optimized risk management measures and control countermeasures by discussing the control of employee safety behavior; S. Amirshenava et al. ( Amirshenava and Osanloo, 2018) proposed a risk identification model that integrates a 3D risk matrix and MCDM technology; and Zhang et al. ( Zhang et al., 2012) conducted an in-depth study on the early warning technology of multisource information coupling for mine disaster sources and proposed a method for locating spatiotemporal abnormal risks.

Risk control theory provides a strong guarantee for improving the visualization of mine risks. However, the ambiguity of risk information data, the lack of comprehensive information elements, and the complexity of the entire management process have created challenges in mining risk prevention and control. Therefore, it is inevitable that mine risk control would ally with information platforms with novel management methods. In order to reduce the risk of casualties and economic losses caused by mining accidents, Dong et al. (Dong et al., 2021) established a man-machine-environment system composed of evaluation indicators and defined the classification standard of indicators. McGinn et al. (McGinn et al., 2001) presented the concept for an integrated web-based system in support of the assessment and information needs associated with worker safety. Yang et al. (Yang et al., 2022) analyzed he current situation of drinking water sources along the mainstream of Yangtze River, which could be attributed to the superposition of human activities and natural background factors, it could contribute to the government's targeted management and control of safety risk sources for drinking water sources along the Yangtze River Basin. Yan et al. (Yan et al., 2021) proposed a new evaluation method named cloud cluster analysis, which solved the problem that the lack of relevant classification methods and standards made it difficult to evaluate the fan system of underground metal mines in high cold and altitude. Wu et al. (Wu et al., 2022) proposed an uncertainty prediction model for mining safety production situation in order to explore the occurrence and development law of mining safety production accidents, analyze its future change trends, and aim at the ambiguity, non-stationarity, and randomness of mining safety production accidents. Ouyang et al. (Ouyang et al., 2018) proposed the application of big data to safety science research and explored the basic connotation and application principles of safety big data (SBD). Other scholars have also emphasized the feasibility of using big data in safety science and adapted it in the theoretical research into safety decision-making (Walker and Strathie, 2016; Guo et al., 2015; Wang et al., 2020). Big data provides an extensive decision-making foundation for security management activities and provides a broad source of "evidence" for EBSs. However, the challenge of turning massive data into useful evidence information still urgently needs to be addressed.

Based on the above research, valuable and transformable "safety evidence" is the core content of EBS, which aims to generate date suitable for safe production through the transformation of vast raw data. After screening and processing, SBD is transformed into effective safety evidence that can be used to carry out safety decision-making activities, thereby making safety management activities more scientific and reinforcing risk prevention work in mine production. In view of evidence-based safety, this paper starts from the process of mine safety production and transforms SBD and safety evidence to establish a risk analysis-based pre-control mechanism for mine risks.

2.1 Evidence-based safety management

Distinguished from the broad concept of EBSs, the mine evidence-based management prevention mechanism incorporates the following four elements: (1) Evidence. This is vital for EBS to make safety decisions. It principally includes the professional skills of managers and the actual situation in the mine production process. (2) Safety professionals. EBS helps safety management personnel and safety technical personnel realize safe production. (3) Specific mine production management problems. The mine production and operation systems are interrelated. When adopting the risk prevention mechanism, the particularity and pertinence of the work and the operation environment should be considered to ensure the effectiveness of the prevention mechanism. (4) Implementation of the organizational environment. The organizational environment includes organizational behavior, such as the safety culture of the enterprise and the manager's attitude toward safe production. The basic elements of the mine EBS concept are shown in Fig. 2.

Unlike traditional safety management methods, the EBS management methods used in mines have the following advantages as shown in Table 1.

Table 1

Differences between traditional safety methods and evidence-based safety management methods
Contrast aspect	Traditional means of safety management	Evidence-based safety management approach
Decision-making evidence	Traditional safety management methods rely on peer and personal experience, which often leads to one-sidedness and the mechanical imitation of safety decisions.	EBS evidence sources are often multilevel and multiobjective, including the production experience, safety skills, safety scientific methods, safety accident case base, safety literacy of decision-makers and practitioners, etc. The making of safety decisions is often scientific and targeted, which is also the core content of EBS.
Risk assessment stage	Effectiveness evaluation indicators are usually fuzzy and qualitative intermediate indicators.	The EBS risk assessment index is a quantitative critical index with clear risk direction and clear warning information that can often show the safety performance of the system.
Risk identification stage	Traditional safety management activities are limited to macro safety inspections. It is impossible to form clear questions about the actual problems of safety production requirements, and some potential micro risks still cannot be identified.	The EBS method usually pays attention to micro changes and the micro nature of the production process and is committed to exploring the causes and essence of risk problems; therefore, the identified risks are often targeted.
Risk prevention and control concept	Traditional safety decision-making activities usually draw lessons from an accident after it occurs, and the acquisition of risk information and risk prevention and control methods are lagging.	By seeking the best evidence, EBS gives early warning of accident risk before an accident happens through risk information capture, risk information collection and storage, risk information integration and conversion, and evidence information mining and extraction combined with risk information flow to prevent accidents.
Risk decision	Decision-making costs are low, but safety managers are highly subjective, while the effect of decision-making activities is often restricted by decision-makers’ abilities, safety skills and safety literacy.	To carry out effective data-driven security decision-making and adhere to "effective evidence", decision-making activities are often supported by technical indicators and other data.
Feedback on practical effects of decision-making programs	Limited to on-site feedback.	EBS often has a practical effect feedback link, whereby after the implementation of evidence-based intervention, it is determined whether the effect achieved is in line with expectations, so that the effectiveness of the management method can be understood in real time and follow-up effect feedback offered to ensure the logic of safety management methods.

EBS management is more scientific and objective than traditional management concepts, and it provides strong theoretical support in seeking intrinsic safety for mines.

2.2 Evidence

In evidence-based decision-making, evidence-based management, and evidence-based education, "evidence" is usually scientific information used to improve decision-making tasks and produce positive effects. In EBS, evidence can be understood as security information that supports EBS decision-making, and it can be divided into the following categories.

Unlike traditional safety information, EBS "evidence" has the following characteristics: (Ⅰ) Safety evidence is formed by the processing of safety information and only partly comprises macro safety information; (Ⅱ) To turn safety information into safety "evidence", it is not possible to simply rely on managers; safety professionals need to use modern scientific methods and tools to collate, screen, identify and research safety information; (Ⅲ) Evidence comes not only from safety information but also from collected relevant research results; (ⅳ) Safety information often has paradigm characteristics, while evidence is scientific, pertinent, and high quality.

Table 2

Mine EBS evidence classification
Safety evidence category	Related explanation
Mine production accident	The series of events that occur in the focal mine or other similar mines leading to casualties, equipment damage, environmental damage, economic loss, threat to or destruction of safety status. The evidence features of this type of event include the direct cause, indirect cause, accident process and accident consequence.
Safety management experience of mine personnel	The experience of mine safety management personnel and mine decision-making organizations, including the front-line production experience of safety personnel, safety management skills, management experience in response to emergencies, management experience in dealing with common mine production accidents, and experience in daily mine safety management activities.
Organizational decision-making environment	The organization and management of the mine management decision-making level toward the mine production system, the safety science literacy of the decision maker, and the safety management ability at the decision-making level in the mine enterprise.
Mine production status	The mine production period, the key tasks of the mine, the significant assignments of the mine’s current safety prevention and control, the current production conditions of the mine’s high-risk-coefficient working conditions, and the characteristics of the high-risk areas.
The most recent research results from safety science theory	A safety science database provided by various scientific retrieval tools and the most recent safety science theories that safety managers need to obtain.
Related policies and industry standards	Mine safety production standards, safety laws and regulations designated by the state, safety production norms formulated by local governments and related industries, safety ethics, etc.
Technical Support	Software and hardware technical support to achieve safe production and obtain safety information, including journals, technical manuals, works related to production safety, evidence data collection system, data statistical analysis platform, mining safety production data, mining platform, mining tools, etc.

Selecting evidence from safety information is an important part of EBS management. To ensure effective EBS activities, it is necessary to ensure that decision-making is practical and feasible and can achieve the expected results for mine production, which requires the scientific transformation of safety information into evidence. With the maturity of big data theory and technology, EBS decision-making has gradually shifted from experience-driven to data-driven quantification. Therefore, a scientific process is urgently needed that takes the input of the original safety information and delivers the output of evidence-based risk decision-making.

2.3 Mine risk pre-control mechanism based on evidence-based safety management

EBS includes evidence-based diagnosis and evidence-based intervention in mine disaster risk control. Evidence-based diagnosis mainly adopts risk identification and risk assessment methods to identify and analyze common mine disasters and determines the risk hazard degree of the analyzed object according to the basic characteristics of the identified hazard sources. Evidence-based interventions mainly use safety management methods combined with evidence-based methods to propose reasonable risk prevention and control measures for the identified disaster risks and corresponding mine risk assessment results. The implementation steps of EBS in mine risk control are shown in Fig. 3.

(1) Risk identification stage. Combining national safety standards, safety laws and regulations, mine safety production systems, mine production norms and mining enterprise production requirements, an initial evidence-based decision-making evidence set is established, and risk identification work is conducted in sequence for mine risks. Risk identification is the first step in evidence-based diagnosis in the EBS method and aims at identifying risk objects.

(2) Risk evaluation stage. The management experience of on-site safety managers is combined, the initial evidence set is utilized, and key technical means are adopted to analyze and mine useful information from the evidence set; ultimately, algorithm models, data analysis models and other methods are used to realize a feasibility evaluation of mine disasters.

(3) Risk analysis and diagnosis stage. Incorporated with the above steps, the mine disaster risk grade and the object set of evidence-based intervention are determined, and the problem structure is further normalized and standardized. As evidence is retrieved, the objects of intervention are analyzed in depth, and specific safety management problems are summarized to determine the basic direction of safety management and evidence-based intervention.

(4) Risk control intervention stage. Evidence-based intervention is carried out according to the experience of safety management personnel and the safety production requirements of the mine production systems, mainly including on-site intervention and evidence-based intervention. On-site intervention is mainly based on the work experience of on-site safety management personnel. The evidence intervention method quantifies the evidence, uses multiple evidence sets for an objective and comprehensive analysis, and then implements effective safety management activities.

(5) Effect evaluation stage. Effect evaluation investigates whether the effect achieved is in line with expectations after the implementation of evidence-based intervention. It includes immediate effect evaluation and after-effect evaluation. If the effect is not satisfactory, there is a return to the risk management and control phase, and the evidence-based intervention will be resumed until the effect meets the expectation.

From the EBS risk control path, it is found that the original data cannot meet the universal requirements in the EBS process due to the complexity of the original data information and the high data interference intensity. At the same time, the information chain transmission in the process of evidence transformation is usually one-way, and the transformation and feedback process for evidence information is commonly carried out after the safety decision has been made, which may also lead to a delay in safety decision-making and poor effects. Evidence-based security management principally is realized when risk management and control is built on the best evidence, while the best evidence requires the information in the security database to be transformed and screened, so it is necessary to add the concept of SBD.

3.1 Advanced concepts of safety big data

To ensure safe production in the mining system, it is necessary to excavate various risk data according to the characteristics of the mine and then obtain safety information to address mine disasters and hidden risks. SBD serves as such a medium. However, due to the large amount and miscellaneous types of original big data, unscreened and unprocessed data cannot provide an effective reference for decision-making. Huang et al. (Huang et al., 2018) believed that moving from raw data to safety science theory takes several key steps: "original big data–safety data–safety information–safety knowledge–safety science theory". Ouyang et al. (Ouyang et al., 2016) pointed out that the production of SBD must start with initial data collection and move through preprocessing, data storage and management, data analysis and mining, data application and feedback. When making risk decisions, the safety knowledge, internal details and inherent safety mode contained in the original data should be extracted and utilized by the decision maker as the basis of the safety decision. It is important to pay attention to the transformation from raw data into SBD that is available in the mine, and it requires a series of stable operating mechanisms to frame a systematic path from the original database input to the safety decision output.

During mine production, the construction of a large safety database has the following functions: (1) The establishment of a large mine safety database can create a disaster prevention center and realize an integrated prevention process from risk identification and risk evaluation to risk management. SBD technology can support information flow, evolve into safety laws through safety information analysis, realize scientific and standardized safety management, guide safety production practices in mines, and reduce mine disaster risks. (2) The construction of a large mine safety database can provide insights into the direction of safety management, provide a practical basis for mine safety production, and achieve EBS prevention in mine production. (3) The large mine safety database can be structured to simulate risk evolution. When risk factors in the production process are identified, the same or similar disaster accident occurrence chains can be found in the database to simulate the evolution of the disaster occurrence process, visualize the safety management effect and the early warning, and provide a timely early warning function for risk prevention. (4)A large mine safety database can continuously optimize the mine safety production system and expand the mine safety production database to provide a broader source of safety information retrieval to guide mine safety management.

3.2 Safety big data and safety evidence

In the process of mine risk management and control, SBD and EBS can be integrated to analyze mine risk for due to the following qualities: (1) Both EBS and SBD have the same decision-making objects, participants, usage scenarios and safety goals. (2) The core of EBS is to seek "evidence" for risk prevention, while that of SBD is to make use of "security business experience", transform it into "data-driven quantification", and use security data as a form of "security evidence". (3) The source of safety evidence is supported by SBD, and the role of SBD is to collect, analyze and evaluate evidence for mine risk prevention. (4) Obtaining, collecting, and transforming original big data into evidence is an important task in EBS activities. The original mine data must be sorted and transformed into safety information that fits the mine production scenario and further interpreted based on the experience of safety managers to render it suitable knowledge for safe production and a source for evidence-based intervention and decision-making. (5) In the risk pre-control mode under the prevention mechanism, safety managers will adopt different intervention methods to carry out safety management activities based on the results of the risk identification and risk evaluation; using SBD technology to obtain safety information, they do not need to know "why", as long as they know "how to". This can overcome irrational decision-making concepts. (6) The essence of "evidence" in EBSs is safety information and safety experience; SBDs also deliver safety information, and both EBS and SBD convey the same content. The "evidence" that EBS follows can be extracted by using secure big data technology.

The data scattered in the original production system itself are abstract, and only after structured and patterned processing can they be transformed into useful information that can be referred to in the mine risk factor identification process. If unprocessed original information, such as security status information and equipment status information, is used to directly carry out risk pre-control, the workload is very high, productivity is low, and availability and efficiency cannot be guaranteed. Only by using computer technologies such as artificial intelligence, cloud computing, and scientific computing visualization to select the original information and combining this with the work safety experience of the on-site personnel for interpretation can the safety evidence for a particular problem be obtained. The complete chain from data to effective evidence is operated by a formulation system with the safety management mechanism as the carrier, and it is based on the organizational structure and material resources of the mine.

It should be noted that scenario modeling is a prerequisite for promoting the transformation of data into effective evidence. In the risk identification stage, after the original data are collected and processed, they can be summarized, and the safety data can be classified through storage, extraction and processing to improve the risk assessment process.

4.1 Construction of the risk pre-control mechanism

Using the strength of the EBS concept and the PSM risk analysis process, combined with the basic concepts of SBD, a dynamic risk pre-control mechanism is established, as shown in Fig. 4.

The figure reflects the dynamic transformation of raw data into safety evidence, including the data source, the processes for different information transformation stages, and the risk analysis process included in PSM, and it reflects the external mechanism of EBS management. See content 3.2 for specific connotations.

4.2 Basic connotation of the risk pre-control mechanism

The mine safety risk pre-control mechanism based on EBS and SBD condenses and sublimates mine risk prevention and control methods. Combining the generation of SBD, the basic theories of EBS management and the PSM risk analysis process, the operational path of the mechanism (as shown in Fig. 5) includes the following steps:

(1) From raw data to safety evidence

In the mine production process, the identification and utilization of the original data provides the basis for the mine to engage in EBS activities. a. The original data are not the specific data of a certain subcategory of research object but all of the data of the research object. b. Raw data are usually extensive and universal, and they often express the macroscopic phenomena of a class of objects. c. The original data reflect not the causal relationship between the data and the object but the correlation. Based on the characteristics of the original data, the safety problems in each link of mine production form specific original data resources. These set the constraint space and decision-making starting point for the establishment of the EBS mechanism in the mine and reveal the inevitability and feasibility of the transformation from original data to safety evidence.

In line with the basic principles of big data technology, data transformation includes the following steps:

a. Collection and preprocessing of original data. Depending on the different original data sources, the datasets will also have different structures and patterns. Therefore, for multiple heterogeneous original datasets, the data need to be integrated and processed. From the original database, which contains a variety of jumbled mine production information, managers must integrate mine data in light of risk management objectives.
b. Conversion of original data to SBD. The sources of SBD include two levels. First is the consciousness level, which considers whether the original data are related to the safety goal, the safety system, safety production, and the promotion of mine safety management. The second is the surface level, which observes safety phenomena related to mine production. After completing the above process, a large secure database is constructed by correlating and transforming the original data and security issues.
c. Transformation of security big data into security information. After the security database is constructed, the security features of different data information in the database are extracted. Based on the universality and breadth of the data and the demands of safety production, the key technologies (data processing, integration, weighting, modeling, consistency assessment, gray correlation processing, etc.) are used to mine the safety data and transform them into effective data for the analysis of safety information.
d. Conversion of safety information to safety evidence. The effective data information is turned into scenarios and interpreted in combination with the work experience of field managers. Through screening, analysis and the mining of safety rules, the structure and function of safety information are further reorganized to obtain safety information and effective evidence related to the scenario and to guide the development of EBS management activities.

(2) From safety evidence to evidence-based diagnosis.

Safety evidence is the core of EBS, and its application value can only be realized if it can be used by decision makers to guide practice. Unlike traditional EBS management, the safety evidence transformed by SBD draws on the practical experience of safety managers, and its formation process considers whether it is authentic, appropriately targeted and scientific, making the original evidence-based intervention activities more "risk predicting". The process of conducting evidence-based diagnosis based on safety evidence includes the following steps:

a. Risk identification stage

Risk identification is the beginning of evidence-based diagnosis activities. Risk prediction uses contextualized safety evidence and a series of technical means to investigate potential hazardous factors in the production site or diagnostic area, and it analyzes the direct, derivative, and secondary consequences that they produce. The risk identification process should follow the following principles: ① Rational. Periodic inspection of risks and hidden dangers throughout the mine should be carried out according to the safety evidence information. Priorities are set and reliable investigations conducted by combining the actual production situation of the mine with the company's own characteristics. ② Timely. Risk identification activities should be launched in a specific time period, and related activities should be carried out according to the production plan at different stages. ③ Scientific. Operating at the frontier of safety science, technical means are used to reveal the location, disaster-causing mode and path of the potential accident for dangerous and harmful factors existing in the mine system and to accurately and scientifically describe and display them. ④ Systematic. Mine risk identification covers a wide range of factors, and risk identification activities should include all processes of the production and operation systems and management activities.

b. Risk assessment stage

Safety management decision-makers need to evaluate the identified risk factors, in particular to determine the safety risk state and safety problem set for the environment of a specific situation in a mine through data processing methods combined with case studies and the relevant qualitative and quantitative research conclusions.

c. Risk prediction stage

Unlike traditional EBS methods, the most important task of evidence-based management activities under the SBD perspective is prediction, in particular, the use of mathematical operations and logical analysis to predict the trend and possibility of future risk accidents for the research object.

(3) From evidence-based diagnosis to evidence-based intervention

a. Evidence-based intervention stage

The above process is used to obtain the risk development situation and potential degree of harm of the research object.

According to the practical experience of the safety management personnel and the production requirements of the mine system, management decisions and safety control means are implemented. The process mainly includes on-site intervention and evidence intervention: on-site intervention is implemented based on the work experience of on-site safety management personnel; evidence intervention is taken based on step (1) combined with the results of the data transformation, wherein a data analysis method is used to quantify the safety evidence so that it can be used to assist in safety decision-making and the further implementation of effective safety management activities.

b. Effect evaluation stage

Determining whether the evidence-based intervention process is reasonable and effective requires follow-up evaluation. The after-effect evaluation mainly incorporates on-site feedback and follow-ups. On-site feedback provides the real-time evaluation of evidence-based intervention based on feedback from on-site intervention in EBS activities. The follow-up evaluation compares the results of the risk intervention process with the expected overall objective and aims to achieve the desired safety effect by adjusting and controlling the subsequent behavior of those participating in the evidence-based intervention.

In EBS activities conducted using SBD thinking, security evidence is retrieved in a hierarchical manner, including original database analysis, data summary and cause analysis, research conclusion analysis and security evidence analysis; these correspond to the four stages of security evidence acquisition from original data to security evidence. Contextualized processing should be implemented at different stages of development to make the process of security evidence conversion more specific and scientific; this is also a basic requirement for putting EBS activities into effect.

Taking the stability analysis of the mined-out area in a lead-zinc mining area in Guangdong Province as an example, the pre-control model of mine risk established above was applied for analysis. Due to the existence of many mined-out areas (groups) in this mine, a large number of residual mineral resources cannot be recovered due to major hidden dangers to the mine’s safe production. Therefore, it is necessary to carry out management research. The EBS management research work aimed to accurately detect and ascertain the size and distribution of the mined-out areas in the middle of the mine and to provide follow-up risk stability analysis of the goafs, and a 3D physical model of the mined-out areas was established. The author of this article and the staff of the Dajianshan lead-zinc mine conducted a field survey of the three-dimensional conditions of the goaf and made real-time records for further management (as shown in Fig. 6).

(1) From raw data to safety evidence

Select the goaf of the mine as the monitoring object, use the goaf scanning device to obtain high-precision point cloud data, and use data analysis technology to process these original data. Data processing software was used to form the original three-dimensional surface model of the goaf from the high-precision point cloud data. Based on the above original 3D model, three-dimensional visualization technology was applied to realize the physical signs of the goaf risk area and reveal the risk information of the goaf stope. Digital processing techniques such as data processing, integration, weighting, and modeling were used to mine the safety data and establish a three-dimensional visualization model of complex empty area groups (as shown in Fig. 7). On the strength of the above depiction of the situation, combined with the experience of field managers, the safety risk information was interpreted artificially, and the information was screened and analyzed to obtain the basic situation for the goaf of the mine and the stability information of the stope.

Based on the scene and Fig. 8-a, the empty area was located in the upper area of the transportation roadway. The cross-sectional view of the exploration line shows that the bottom of the empty area was less than 2 m from the roof of the roadway. There are some wood supports at the site (Fig. 6-a, Fig. 6-b), but the supports were affected by moisture, and they had been severely damaged.

Figure 7-b shows that the length of the empty area reaches 75.72 m, the maximum height is approximately 63 m, and the width of the empty area is approximately 26 m. Overall, the empty area has a relatively large volume. From the projection map of the middle section (Fig. 8-b), it can be seen that the empty area includes the transportation roadway to the middle section; at present, the lower part of the roadway near the middle section of the exploration line has basically collapsed, and warning signs need to be set up in this part of the area to stop pedestrians from entering. In addition, to prevent further collapse in the empty area, it needs to be filled as soon as possible.

(2) From safety evidence to evidence-based diagnosis

Display the results in combination with the cloud map, the key inspection location for risk identification is determined, and the results should be submitted to the site safety manager in the form of a report. The production stage could be implemented in the full-time domain of risk identification activities; that is, the step (1) process should be carried out continuously. It is also necessary to integrate the risk information obtained by technical means with the experience of security managers to ensure that sufficient security evidence is obtained for risk identification. Referring to the characteristic index parameters of the 3D visualization of the abnormal area, combined with the on-site monitoring, case studies and relevant qualitative and quantitative research conclusions, the risk of the identified area is evaluated and analyzed. According to the results of the risk assessment and the constructed EBS database, combined with the rules of change for the characteristic parameters, the risk evolution trend can be predicted and quantified.

(3) From evidence-based diagnosis to evidence-based intervention

Directed by the results of the risk evaluation and risk prediction, reasonable and feasible risk prevention measures should be carried out. In the later stage of evidence-based intervention, scientific evaluation criteria should be established to evaluate the effect of the full-cycle of EBS activities; in particular, changes in the stability of the empty space after evidence-based intervention should be identified. The set of entire management activities are carried out in a cycle to continually analyze the degree of risk in the system objects. A timely assessment of the interventions that have been implemented needs to be carried out on a regular basis, and the assessment results are input into the large EBS management database as new evidence for reference. The engineering practice application process is shown in Fig. 9.

(1) Mine safety management based on evidence-based thinking avoids the intuitive and unsystematic safety decision-making resulting from traditional methods, it incorporate not only the objectivity and rationality of the evidence but also the actual safety situation in mine production, which also includes the entire process of decision-making implementation, ensuring that the safety decision-making activities have a more scientific basis.

(2) The safety problems in each link of mine production generate specific original data resources; these set the constraint space and decision starting point for the establishment of the risk pre-control mechanism in the mine and show the feasibility of the transformation from original data to safety evidence. Since security evidence is the core of EBS, the value of "evidence" can be realized only when it is applied in the security decision and the established security goal is achieved.

(3) The establishment of a large security database refines the evidence sources, reduces unnecessary processes in the transformation of original data into safety information, supports real-time and rapid security decisions, and improves the efficiency of safety management activities.

(4) The risk analysis method based on PSM can effectively control the total production process and provide a new perspective for risk analysis. It combines the classic EBS concept with risk identification, risk assessment, risk decision and risk prediction processes, thereby significantly improving the overall safety of the dynamic production process and controlling every link.

(5) When using evidence-based thinking to carry out safety management activities, decision-making and the application of evidence-based thinking and management activities play a crucial role in determining how to evaluate the reliability of the obtained evidence and how to apply the evidence to the actual mine safety production process in the face of varying evidence sources.

(6) It should be noted that EBS activity is not only a concept but also a safety management way of thinking, a safety management system and a set of safety scientific methods for system analysis. EBS also comprises an advanced stage of security management activities and security decision-making, and its aim is to help managers and practitioners conduct more scientific assessments.

(7) First, it should be noted that not all evidence are equal, the search for evidence is crucial, and sufficient evidence must be identified to support the safety decision-making activities of managers. Second, all the evidence found should be screened individually, each process is crucial when transforming raw data to SBD to security evidence. Third, evidence is a sufficient and necessary condition, but different mine safety production site conditions should be considered because establishing scenarios can make the transformation of safety evidence more specific and scientific.

On the basis of EBS theory, this paper proposes a new mine risk pre-control mechanism based on the transformation of SBD and safety evidence, starting with the complete process of PSM safety production. The mechanism shows researchers and security managers how PSM risk analysis can be applied to the EBS process to improve decision-making efficiency in security management activities. This paper contributes to the literature in the following ways: (1) a risk analysis perspective is applied to distinguish between traditional management methods and EBS management methods; (2) an application scheme for EBS management in mine risk control is proposed based on PSM; (3) a basic connection between SBD and safety evidence is established, and the feasibility of integrating SBD and EBS management is demonstrated; (4) a mine risk pre-control mechanism is build based on EBS and SBD, and its basic connotation is developed from the emergence of SBD, the basic theory of EBS and the PSM risk analysis process; (5) the process of transforming mine original data into safety evidence in the EBS concept is analyzed from the perspective of safety thinking. Based on the theoretical model, this paper provides a preliminary discussion of the mechanism of mine risk prevention and control and introduces use of the mechanism. Due to the basic characteristics of big data, the process of obtaining evidence needs to be further streamlined and refined, and there is still much room for improvement in the EBS process.

Author’s contributions: Conceptualization, methodology, Visualization, writing—original draft preparation: Jiachuang Wang; Validation and supervision: Jiang Guo; formal analysis and resources: Jia Guo; investigation: Jiachuang Wang.

Funding: This research was supported by National Natural Science Foundation of China (No. 52174140).

Compliance with ethical standards

Ethics approval and consent to participate: Not applicable in this manuscript.

Consent to publish Not applicable in this manuscript.

Competing interests: The authors have declare that they have no competing interests.

Availability of data and materials: Not applicable.

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Risk pre-control mechanism of mines based on evidence-based safety management and safety big data

Status:

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Abstract

Figures

1 Introduction

2 Overview Of Evidence-based Safety Management

2.1 Evidence-based safety management

2.2 Evidence

2.3 Mine risk pre-control mechanism based on evidence-based safety management

3 Safety Big Data

3.1 Advanced concepts of safety big data

3.2 Safety big data and safety evidence

4 Mine Risk Pre-control Mechanism Based On Ebs And Sbd

4.1 Construction of the risk pre-control mechanism

4.2 Basic connotation of the risk pre-control mechanism

5 Application

6 Discussion

7 Conclusion

Declarations

References

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