A Key Performance Indicator and Lifetime Analysis of Diesel vs. Battery Powered Load Haul Dump Vehicles in Underground Mining Operations
- Restrictions on Access:
- Open Access.
- One of the most prohibitive issues that plague new technologies reaching the mass market is the STEM (science, technology, engineering, and mathematics) gap. This occurs when STEM personnel and non-STEM personnel have difficulty expressing their ideas efficiently. The most frequent example of this is the expressing of a new technology or idea as a monetary value. This research focuses on bridging that gap by developing an economic model that adapts to different processes and compares technology by assessing the value each technology adds to the process. This is achieved by an economic value study for the major equipment of a process carried out in the desired process industry. This dissertation focuses on exploring battery powered alternatives to diesel powered underground load haul dump (LHD) equipment. The economic model developed for this project provides corporate investors and, in turn, its consumer base with an added net value to the process for each alternative. Corporate customers and audience being; plant and operations managers, corporate operations and technology, engineering and reliability decisions makers. The project was divided into four chapters, each of which consist of an accepted or submitted peer reviewed journal publication. The first chapter involved determining the current default equipment used in the process in combination with the replacement technology. All the data that could be obtained for the equipment and process was gathered and, with appropriate assumptions for missing or incomplete data, used to initiate development of the model used to compare the technologies. The lead acid battery is most commonly used for battery powered mining equipment. Two battery chemistries, lithium-ion and Sodium Metal Halide (NaMX), were selected as the replacement technology using six criteria for cell performance; safety, environmental footprint, life span, degradation, scalability and toughness. Initial calculations were conducted to determine approximate battery cost, volume and weight. The second chapter, involved process flow diagram creation and investigation of the equipment and each step of the process. Key performance indicators were calculated using operational mine data and were also used to find out the main factors that impact the economic value of each technology. Analysis of the performance data led to the understanding of the distribution of uptime and downtime for each vehicle. Understanding each issue that added more downtime for both electric and diesel powered LHDs allowed for the estimation of uptime and downtime for battery powered LHDs. The third chapter finalized the value model used to convert technical details of the technology to a single economic value. Wear characteristics and life time of both the current and replacement technology were calculated using the same data set used in the second chapter added to the existing input parameters. The parameters were used in numerical models to determine the value each technology contributed to the process. Assessments focused on both profit and cost only analysis for a more in depth comparison of each technology's value. A stability analysis was performed to address the variability of the input parameters. This was used to develop a range of conditions in which each technology was superior. The fourth chapter expanded the value model, exploring new parameters and their effect of the value of the new technology. A parameter, focusing on the reduction of energy costs due to reductions in ventilation requirements, was added to determine the effect reduced energy costs had on the value battery LHDs. Multiple battery chemistries were analyzed not only compared to diesel but each other to determine the technology that would add the most value to an underground hard rock mine. The model was improved to allow for sensitivity model to be run by computer allowing for orders of magnitude improvement in accuracy. The parameters are adjusted for inflation each year, however the revenue and costs remains the same for each year. There would be significant reduction in the variation in the input parameters over a 10-year span than a 35-year span; therefore the model duration was shortened to the span of a lifetime of an LHD, or 10 years.
- Dissertation Note:
- Ph.D. Pennsylvania State University 2016.
- Reproduction Note:
- Microfilm (positive). 1 reel ; 35 mm. (University Microfilms 10-154595)
- Technical Details:
- The full text of the dissertation is available as an Adobe Acrobat .pdf file ; Adobe Acrobat Reader required to view the file.
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