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dc.contributor.advisorMiller, Hugh B.
dc.contributor.authorPereira, Paulo R.
dc.date.accessioned2018-10-09T18:05:35Z
dc.date.accessioned2022-02-03T13:11:21Z
dc.date.available2018-10-09T18:05:35Z
dc.date.available2022-02-03T13:11:21Z
dc.date.issued2018
dc.identifierPereira_mines_0052E_11566.pdf
dc.identifierT 8578
dc.identifier.urihttps://hdl.handle.net/11124/172535
dc.descriptionIncludes bibliographical references.
dc.description2018 Summer.
dc.description.abstractThe main deciding factor on the purchase of a component brand for mining equipment is usually the retail price or acquisition cost differential of that component between different manufacturers. The components from different manufacturers will have different contributions to equipment downtime depending on their individual reliabilities, and therefore will directly influence revenue generation. The value of this downtime is often significantly higher than the differences in retail price or acquisition cost between the components. Compounding the situation is that mining companies do not have the models, tools and/or protocols to evaluate different component reliabilities and their immediate impact on the company’s cash flow. A comprehensive assessment of mining operations shows that there are no tools readily available to quantify that impact. As a result, this dissertation focuses on developing a methodology to establish these different reliabilities, how they affect equipment availability, and the immediate impact on a mining company’s cash flow. The methodology developed in this dissertation is evaluated by two approaches or (1) deterministic and (2) stochastic, based on Monte Carlo Simulation. To test the methodology, it is applied to two case studies involving hydraulic hoses from two different surface mines to quantify the relationship between component reliability, mining equipment availability and impact on the mining operation’s cash flow. The results from the models indicate that the lower reliability data set caused lower equipment availability and generated a larger net present value of the cash flows of the revenue loss than the data set with higher reliability. The results also indicate that the methodology can be successfully applied to any equipment component at any mine that uses a component reliability centered management program. The greatest contribution of this research is the methodology produced, which is a more viable alternative than conventional techniques to support operationally and financially effective equipment component purchasing decisions.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado School of Mines. Arthur Lakes Library
dc.relation.ispartof2010-2019 - Mines Theses & Dissertations
dc.rightsCopyright of the original work is retained by the author.
dc.subjectmodel
dc.subjectmining management
dc.subjectpurchasing management
dc.subjectequipment
dc.subjectMonte Carlo simulation
dc.subjectfinancial
dc.subjectreliability
dc.titleReliability based models to evaluate the financial consequences of mining equipment component selection and purchasing decisions
dc.typeText
dc.contributor.committeememberEggert, Roderick G.
dc.contributor.committeememberKim, Eunhye
dc.contributor.committeememberKaunda, Rennie
thesis.degree.nameDoctor of Philosophy (Ph.D.)
thesis.degree.levelDoctoral
thesis.degree.disciplineMining Engineering
thesis.degree.grantorColorado School of Mines


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