# New Method to Study the Effectiveness of Mining Equipment: A Case Study of Surface Drilling Rigs
## 2 Methods  
Mining processes comprise a vast array of complex factors to evaluate, which include management strategies, equipment characteristics, maintenance programs, mine design, mine planning, operating conditions and operator's skills, among other elements. The dynamic model developed in this study aims to accomplish the following main objectives: (i) equipment state monitoring; (ii) weak area detection; (iii) maintenance plan development; (iv) residual mining equipment's life estimation; and (v) future mining operations simulation. The model, named OMEE, has been built to be flexible and adaptative according to mining operations. Thus, it introduces a novel methodology to evaluate the effectiveness of mining equipment through the analysis of the four factors shown in Figure 1.  
The OMEE method has been applied to analyze the surface drill rig fleet performance in two case studies located in the northwest of Spain for 10 years. Specifically, these studies pertain to open-pit coal mines characterized by benches ranging from 8 to 18 m high, depending on slope stability and economic factors. The extraction process consists of removing an overburden located in the upper part and then the coal seams. The process consists of the following phases: drilling, blasting; loading, and hauling.  
The equipment is composed of Tamrock Pantera 1100 (Sandvick AB, Sandviken, Sweden) for the drilling phase, Hitachi EX5500 excavators (Hitachi Construction Machinery Co., Ltd., Hitachinaka-shi, Japan) for loading and Caterpillar 789C trucks (Caterpillar Inc., Irving, TX, USA) for hauling. Additional pieces of equipment, such as Caterpillar D10 (Caterpillar Inc., Irving, TX, USA) and Komatsu D 475 (Komatsu Ltd., Tokyo, Japan) dozens, are used in auxiliary processes of the mine. Figure 2 gives an overview of one of the case studies analyzed.  
Figure 1: Factors that encompass the OMEE.  
Initially, adequate KPIs are defined to evaluate the specific parameters of the surface drill rig in the process, followed by the development of a specific maintenance program for the drilling rig equipment. Subsequently, data collection from the mining equipment has been conducted daily for the period of ten years using onboard instruments and the mining operator's input. The database has been designed to obtain the relevant information about mining equipment performance, maintenance programs and spare parts inventory, following a systematic four-step process: (1) definition of the monitoring parameters, (2) data storage, (3) data interpretation, and (4) data 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 analyze the real-time performance behavior of the drilling rigs. 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 identify potential weak areas in the process.