Developing a Context-Based Alert System for Haulage Cycle Optimization

"Productivity in openpit mines depends on the observation and adjustment of critical phases of operation. As one of the most expensive activities in openpit production, optimization of the load-haul-dump cycle becomes a critical aspect to address. Using simulation techniques and an ad hoc methodology for analyzing the key performance indicators (KPIs) involved in the production cycle, it is possible to compare actual performance and ideal operating conditions and develop an alert system when operating conditions are subpar with the expected production standards.Study objectivesThe purpose of this work is to implement a methodology for optimizing the haulage cycle by identifying and adjusting the factors that affect the cycle time performance. The methodology includes the implementation of an alert system emitting warning messages when one or several trucks are idle, or when the time of completing production tasks is falling outside a predefined value. This alert is compared with predefined KPIs and is used to determine corrective actions.The alert will:• Demonstrate the benefits of time analysis and how this affects the productivity results in the mining process.• Demonstrate the utility of KPIs in the extraction of ore and waste and how they help to identify equipment performance.• Develop software interfaces to visualize the alert system in order to increase awareness in the operations supervisor.• Make recommendations for future applications that can help improve the productive process of an openpit mine.Problem statementTransporting material in openpit mines may require the utilization of high capacity equipment, which also represents an elevated cost per hour. A supervisory system that controls the adequate distribution of trucks and shovels by providing the operational status of each unit shall contribute to increase productivity while subsequently reducing operational costs. Nevertheless, there is an issue with certain dead times such as queue trucks for loading, trucks waiting to be loaded and other delays. This creates inefficiencies in fuel consumption and energy utilization.For the identification of delays, a contextbased system could be required in order to help optimize the haulage cycle time by controlling delays in loading, haulage and dumping. After applying this methodology, efforts were focused in correcting out-of-standard performance values."