A new methodology has been proposed to help study the efficiency of surface mining drill fleets.
The method involves the evaluation of a vast array of complex factors, including management strategies, equipment characteristics, maintenance programs, mine design, site planning, operating conditions as well as workforce skills.
The Overall Mining Equipment Effectiveness (OMEE) model was developed to realise equipment state monitoring, weak area detection, efficient maintenance scheduling, residual equipment life estimation and future mining simulation.
According to Spanish academics Juan Gutierrez-Diez, Ana Castanon and Marc Bascompta, the OMEE method was applied to analyse the performance of two surface drill fleets at two coal mines, located in the northwest of Spain, over a 10-year period.
In effect, these stages help in defining the monitoring parameters (using data storage, interpretation and analytics), cross-checking analysis, knowledge extraction and decision-making.
“Data collection has been combined using a data mining approach, which provides data and statistics to analyse the real-time performance behaviour of the drilling rigs,” the researchers said.
“Moreover, daily worksheets have been devised to collect pertinent information about mining equipment performance, maintenance activities and spare parts inventory, including drilling parameters, machine patterns, spatial patterns and any other specific factors.
“Finally, the OMEE method is employed to cross-check against the entire drilling rig fleet, assessing the influence of the maintenance program, management strategy and operating conditions on the effectiveness of the drilling rig equipment, as well as assessing potential weak areas in the process.”
One of the aims of this new approach, the researchers said, sought to optimise mining equipment usage by assessing availability, utilisation and productivity based on evaluating the most sensitive inputs in real-time.
Consequently, it provided comprehensive insights into the whole life cycle of the mining equipment and, therefore, allowed the researchers to know specific areas where efforts needed to be focused in order to improve the equipment’s effectiveness.
“Mining processes must be managed optimally to achieve maximum mining equipment productivity,” they said.
“Several factors significantly influence production efficiency, such as the operator´s skill or attitude, but mining equipment can still underperform due to mechanical and technical issues or inappropriate operating management.
“In mining processes, the operating conditions are vital to achieve production targets and, for this reason, it is important to estimate how the drilling rig is performing in real-time.
“The influence of scheduled maintenance programs on mining equipment effectiveness and availability has been widely proven.
“Appropriate maintenance policies should be developed to improve safe conditions, reliability, availability and effectiveness, avoiding unexpected failures and breakdowns.”
The list of selected KPIs, the researchers said, assisted in measuring the drilling rig performance behaviour and, subsequently, developing an appropriate method to analyse the mining process, identify poor performance and estimate improvement potential.
To this end, the selected indicators adhered to known recommendations which included correlating with strategic aims, being significant and effective in representing and explaining the process as well as making it all reliable, comprehensive, consistent and comparable.
In this regard, the KPIs ultimately allowed the researchers to determine the real-time performance of the equipment with a high degree of conformity.
“The case studies analysed are an example of the potential that this method can offer to the mining industry in achieving sustainable goals with a user-friendly approach,” they said.
“The method presented can be used to analyse individual and collective performance of mining equipment, identify the key influencing factors in the mining process, pinpoint the weak areas of the process and estimate the potential improvements.
“Mining equipment is subjected to continuous degradation throughout its operation life, and most of the replacement models study the life cycle cost.
“This research shows that the OMEE method could be an important tool for replacement decisions, analysing the trend over time of the mechanical and technical availability rates and the production index.”
In this regard, the availability rate emerged as a critical parameter for analysing the effectiveness of the maintenance policy, with results showing that the mechanical availability rate in both mines ranged from 94.4 to 99.5 per cent of the total hours.
This meant that the breakdown hours were from 5.6 to 0.5 per cent of the total hours.
On the other hand, the technical availability rate was from 83.2 to 91.8 per cent of the total time.
Ultimately, these results determined that the maintenance strategy developed was reliable and worked optimally in accordance with some previous research that emphasised how an accurate maintenance program could improve availability.
“The study of both mines shows, firstly, how effectiveness deviations can be identified,” the researchers said.
“Secondly, it estimates how effectiveness deviations influence the mining process and, lastly, where these deviations occur.
“The OMEE can be a valuable approach to measure mining equipment effectiveness and cross-checking between fleets during their life cycle when working under similar conditions.”
