TY - THES

T1 - Reliability Optimisation within Engineering of Mining Equipment

AU - Pirkkanen, Minna Susanna

N1 - embargoed until null

PY - 2012

Y1 - 2012

N2 - Even for a mining operation that is safe and sophisticated, the underground environment is wearing on the equipment. Machinery is an important link in productivity and maximum profitability is a reason to improve the reliability of the equipment. There is no point where equipment becomes too reliable, but there is a point where increasing the equipment reliability becomes unprofitable. Reliability improvements decrease operating costs during the equipment lifetime, but increase the acquisition costs of equipment. Optimised reliability can be determined by minimising overall life cycle cost (LCC). Reliability engineering increases the reliability and maintainability of equipment and therefore its availability in the mining process. In the short-term an equipment manufacturer pays the costs of reliability engineering, but improvements to reliability are cost savings for the mining operation. The manufacturer sells equipment to the customer, but also productivity. In the long-term, good reliability engineering gives the manufacturer a good reputation and new market possibilities. The Logic Tree Analysis in this project determines the value drivers from the reliability optimisation of the mining process for L&H equipment. The value drivers in reliability engineering were divided into four different groups: an average value selected in the operating context, reliability information analysed from field data, maintenance recommendations and requirements for the manufacturer’s reliability engineering from the mining process. Simultaneously with the analysis, tailored reliability engineering and reliability centred maintenance (RCM) material was written for Sandvik. The RCM process quantifies reliability and maintainability design and aims to minimise LCC. Reliability field data from Sandvik’s maintenance shops was analysed using the Weibull analysis. Reliability, downtime, number of failures, required spares and labour, as well as LCC and criticality in terms of safety, environment and operations results from the Monte Carlo simulations demonstrated how quantified lifetime information and RCM are used in design decisions, maintenance recommendations and reliability engineering. Sensitivity analyses for optimised RCM evaluate the effect on results of value drivers selected in the operating context. Reliability performance will be observed over the equipment lifetime, but decisions concerning reliability are mostly made at the equipment engineering stage. This project integrated the reliability engineering and product development process in the R&D and Lifetime Support interface. Reliability guidelines, requirements and actions in this project were added to the R&D project model. RCM verification at the end of product development vi project summarises the reliability engineering performed in new product development. The results of the reliability simulation are recommendations for equipment lifetime and guidance for current product engineering (CPE). Reliability engineering updates simulations with facilitations during the equipment lifetime and collects redesign requests and field feedback for CPE as well as the equipment database, which is a source for new reliability requirements. Reporting templates for communicating reliability information are introduced with case example results. Once reliability-engineering procedures are stabilised, an internal Sandvik reliability manual should be published as a foundation for continuous improvement. The reliability engineering database forms a collective experience.

AB - Even for a mining operation that is safe and sophisticated, the underground environment is wearing on the equipment. Machinery is an important link in productivity and maximum profitability is a reason to improve the reliability of the equipment. There is no point where equipment becomes too reliable, but there is a point where increasing the equipment reliability becomes unprofitable. Reliability improvements decrease operating costs during the equipment lifetime, but increase the acquisition costs of equipment. Optimised reliability can be determined by minimising overall life cycle cost (LCC). Reliability engineering increases the reliability and maintainability of equipment and therefore its availability in the mining process. In the short-term an equipment manufacturer pays the costs of reliability engineering, but improvements to reliability are cost savings for the mining operation. The manufacturer sells equipment to the customer, but also productivity. In the long-term, good reliability engineering gives the manufacturer a good reputation and new market possibilities. The Logic Tree Analysis in this project determines the value drivers from the reliability optimisation of the mining process for L&H equipment. The value drivers in reliability engineering were divided into four different groups: an average value selected in the operating context, reliability information analysed from field data, maintenance recommendations and requirements for the manufacturer’s reliability engineering from the mining process. Simultaneously with the analysis, tailored reliability engineering and reliability centred maintenance (RCM) material was written for Sandvik. The RCM process quantifies reliability and maintainability design and aims to minimise LCC. Reliability field data from Sandvik’s maintenance shops was analysed using the Weibull analysis. Reliability, downtime, number of failures, required spares and labour, as well as LCC and criticality in terms of safety, environment and operations results from the Monte Carlo simulations demonstrated how quantified lifetime information and RCM are used in design decisions, maintenance recommendations and reliability engineering. Sensitivity analyses for optimised RCM evaluate the effect on results of value drivers selected in the operating context. Reliability performance will be observed over the equipment lifetime, but decisions concerning reliability are mostly made at the equipment engineering stage. This project integrated the reliability engineering and product development process in the R&D and Lifetime Support interface. Reliability guidelines, requirements and actions in this project were added to the R&D project model. RCM verification at the end of product development vi project summarises the reliability engineering performed in new product development. The results of the reliability simulation are recommendations for equipment lifetime and guidance for current product engineering (CPE). Reliability engineering updates simulations with facilitations during the equipment lifetime and collects redesign requests and field feedback for CPE as well as the equipment database, which is a source for new reliability requirements. Reporting templates for communicating reliability information are introduced with case example results. Once reliability-engineering procedures are stabilised, an internal Sandvik reliability manual should be published as a foundation for continuous improvement. The reliability engineering database forms a collective experience.

M3 - Master's Thesis (University Course)

ER -