Risk assessment model of mining equipment failure based on fuzzy logic

Petrović, Dragan; Tanasijević, Miloš; Milić, Vitomir; Lilić, Nikola; Stojadinović, Saša; Svrkota, Igor

doi:10.1016/j.eswa.2014.06.042

Cited by 79 publications

(34 citation statements)

References 17 publications

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“…The possibility to operate imprecise and insufficient data Replacement time and downtime of the conveyor [15] * This paper combines sensor technology, LoRa wireless sensor network technology, and GPRS (General Packet Radio Services) remote communication technology, and uses PHP (Hypertext Preprocessor) language and MySQL database to design a set of automated decision support systems for salt lake production. The system uses voltage, current and brine level inquired by sensors to establish a data classification model to determine the fault status of brine pumps.…”

Section: Dynamic Traffic Lights Managementmentioning

confidence: 99%

Improving Intelligence and Efficiency of Salt Lake Production by Applying a Decision Support System Based on IOT for Brine Pump Management

Cui

Zhang

et al. 2018

Electronics

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At present, due to their geographical distribution, environmental conditions and traditional monitoring technologies, the manual inspection of brine pumps in Qinghai Saline Lake can not be effectively carried out in real time, so the pumps have a high failure rate. This has seriously affected the chemical production of this saline lake. The paper designed a remote real-time monitoring terminal and a decision support system based on LoRa technology, GPRS (General Packet Radio Services) remote communication technology and remote-control technology. The system integrated the liquid-level sensing model and the decision support model for brine pump management. The system monitored and analyzed the voltage, current, and liquid-level parameters in real time to determine the operating status or failure of the brine pump. The ID3 (Iterative Dichotomiser 3) method was used to establish the correlation models between the dynamic monitoring information and the brine pump failure, which is the core of the decision support model. The remote controller was implemented to display and control the running status of the brine pumps when the maintenance personnel received the warning information. PHP (Hypertext Preprocessor) language and a MySQL database were implemented to realize the data display, management and decision support system.

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Section: Dynamic Traffic Lights Managementmentioning

confidence: 99%

Improving Intelligence and Efficiency of Salt Lake Production by Applying a Decision Support System Based on IOT for Brine Pump Management

Cui

Zhang

et al. 2018

Electronics

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“…Based on uncertain random variables, Chen et al [28] developed a practical evaluation model for coal mine safety based on uncertain random variables. According to fuzzy set theory, Petrović et al [29] presented a risk evaluation model to evaluate the failures of electromechanical equipment. Lokhande et al [30] came up with a risk evaluation approach based on the identified critical parameters, including depth to height of extraction Unfortunately, the blasting gave rise to naked light, and then the gas was lighted and began burning.…”

Section: Themementioning

confidence: 99%

“…Risk evaluation [25][26][27][28][29][30][31] Assessing the roof fall risk during retreat mining in room and pillar coal mines; evaluating explosion risk in underground coal mines; developing a comprehensive model for coal mine safety; using fuzzy set theory to assess the risk of mining equipment failure; assessing pot-hole subsidence risk in coal mine; using risk performance indicators to analyze coal mine accidents.…”

Section: Themementioning

confidence: 99%

An Approach for Understanding and Promoting Coal Mine Safety by Exploring Coal Mine Risk Network

et al. 2017

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Capturing the interrelations among risks is essential to thoroughly understand and promote coal mining safety. From this standpoint, 105 risks and 135 interrelations among risks had been identified from 126 typical accidents, which were also the foundation of constructing coal mine risk network (CMRN). Based on the complex network theory and Pajek, six parameters (i.e., network diameter, network density, average path length, degree, betweenness, and clustering coefficient) were employed to reveal the topological properties of CMRN. As indicated by the results, CMRN possesses scale-free network property because its cumulative degree distribution obeys power-law distribution. This means that CMRN is robust to random hazard and vulnerable to deliberate attack. CMRN is also a small-world network due to its relatively small average path length as well as high clustering coefficient, implying that accident propagation in CMRN is faster than regular network. Furthermore, the effect of risk control is explored. According to the result, it shows that roof collapse, fire, and gas concentration exceeding limit refer to three most valuable targets for risk control among all the risks. This study will help offer recommendations and proposals for making beforehand strategies that can restrain original risks and reduce accidents.

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“…Several MCDM methods have been applied to FMECA, with a trend towards incorporating them with fuzzy logic [4], e.g. fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) ( [5]; [6]; [7]; [8]); VIKOR (VIsekriterijumska optimizacija i KOmpromisno Resenje) with fuzzy logic [9]; fuzzy AHP ( [10]; [11]); fuzzy logic with grey theory [12]; or simply fuzzy logic applied to the risk factors [13]. The adoption of subjective criteria to either rank or sort a set of alternatives results in a group decision problem arising.…”

Section: Introductionmentioning

confidence: 99%

Fmeca-Based Optimization Approaches Under an Evidential Reasoning Framework

Lolli¹,

Gamberini²,

Balugani³

et al. 2018

dtetr

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One of the major shortcomings of traditional failure modes, effects and criticality analysis is the absence of any interconnection between failure ranking and a procedure for selecting the most critical maintenance/improvement tasks to be carried out. This limits the potential of FMECA for implementation in real environments. In order to bridge this gap, three different 0-1 knapsack models have been formulated. The first aims to select the failures in order to maximise cost savings. The second enriches the selection problem by also taking into account the probabilities of solving the failures with a set of maintenance tasks. The third aims to select the maintenance tasks to maximise the expected profit. In particular, the last two models make use of an evidential reasoning framework to deal with the epistemic uncertainty related to these probabilities. A dataset from a manufacturer of lift winches has been used to validate this proposal, as well as to comment on the need for group decision support systems that are capable of converting the FMECA ranking into maintenance tasks in real environments.

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Risk assessment model of mining equipment failure based on fuzzy logic

Cited by 79 publications

References 17 publications

Improving Intelligence and Efficiency of Salt Lake Production by Applying a Decision Support System Based on IOT for Brine Pump Management

Improving Intelligence and Efficiency of Salt Lake Production by Applying a Decision Support System Based on IOT for Brine Pump Management

An Approach for Understanding and Promoting Coal Mine Safety by Exploring Coal Mine Risk Network

Fmeca-Based Optimization Approaches Under an Evidential Reasoning Framework

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