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New, undestroyed greases of the same brands as those used in a field test, described in Part 1, were examined using conventional methods, such as the SKF V2F test, the roll stability test (ASTM D‐1831), the Grease Worker (ASTM D‐217), the torque test (ASTM 1478‐91), bleeding measurements ( IP 121), yield stress measurements, the 4‐ball test (ASTM D 2266‐86), base oil viscosity measurements, thickener content and the cone penetration test (ASTM D217‐88). The greases have also been tested with several new test methods developed at the University. A specification for relevant testing methods was drawn up and the connections between the tested parameters were investigated. It was found that the mechanical stability could be predicted with a combination of ASTM D‐1831 and the limiting shear stress coefficient γ. This coefficient is capable of predicting wear. It was found that the bearing temperature could be predicted by using the base oil viscosity.

Describes a comprehensive field test to determine the best grease for spherical roller bearings in railway waggon wheels and increase the knowledge of grease lubrication. Nine different fully‐formulated commercial greases were examined in the wheel bearings of five ore waggons, used for transporting ore commercially by railroad from the Kiruna Mine in northern Sweden to Narvik in northern Norway for shipping to foreign markets. After the end of the test period, the wear and electrical damage, as well as the rust on the bearings, were also studied. In order to find out the optimum grease for this application, draws up a specification of requirements and uses a systematic approach to development of an evaluation method that could be applied to greases in actual service.

The process of finding the ultimate grease is described in this report using an example from railway applications. This example includes steps such as a requirement list, field tests, laboratory tests and an evaluation method. The example deals with the problems discovered in a field test performed to determine the best grease for tapered roller bearings in railway wagon wheels and to increase the knowledge of grease lubrication. Seven different fully formulated commercial greases were examined in the wheel bearings of one ore wagon, used for transporting ore commercially by railway from the Kiruna Mine in northern Sweden to Narvik in northern Norway for shipping to foreign markets. The steps performed in this study are recommended in all problems associated with finding the optimal grease for different types of applications.

Wear life of mill liners is an important parameter concerning maintenance decision for mill liners. Variations in process parameters such as different ore properties due to the use of multiple ore types influence the wear life of mill liners whereas random order of processing, processing time and monetary value of different ore types leads to variation in mill profitability. The purpose of the present paper is to develop an economic decision model considering the variations in process parameters and maintenance parameters for making more cost‐effective maintenance decisions.

Correlation studies, experimental results and experience of industry experts are used for wear life modeling whereas simulation is used for maximizing mill profit to develop economic decision model. The weighting approach and simulation have been considered to emphasize the contribution of parameters such as ore value and processing time of a specific ore type to a final result.

A model for estimating lifetime of mill liners has been developed based on ore properties. The lifetime model is combined with a replacement interval model to determine the optimum replacement interval for the mill liners which considers process parameters of multiple ore types. The finding of the combined model results leads to a significant improvement in mill profit. The proposed combined model also shows that an optimum maintenance policy can not only reduce the downtime costs, but also affect the process performance, which leads to significant improvement in the savings of the ore dressing mill.

The proposed economic decision model is practically feasible and can be implemented within the ore dressing mill industries. Using the model, the cost‐effective maintenance decision can increase the profit of the organization significantly.

The novelty is that the new combined model is applicable and useful in replacement decision making for grinding mill liners, in complex environment, e.g. processing multiple ore types, different monetary value of the ore type and random order of ore processing.

The aim of this study is to determine the variation of the different oil analysis instruments in terms of standard deviation and CV‐values, when measuring samples of fully formulated hydraulic and gear oils taken from working systems.

In this investigation two different spectrometric techniques, ICP‐OES and RDE‐OES, have been studied to determine the instruments' precision of measurement and ability to measure the absolute level of contamination.

The ICP has better precision of measurement of the two instruments, but cannot predict the absolute values of contamination when oil samples are only treated by organic solvent dilution if the samples include large or dense particles. It is therefore not too good, with the sample pre‐treatment method used, at detecting wear processes that produce dense/large particles, such as pitting failure. For instance, microwave‐assisted acid digestion could be used for sample pre‐treating to obtain accurate results in that case. It should, however, be able to detect wear mechanisms that produce small particles such as abrasive wear in any case: the ICP has a repeatability value of r=3 per cent and a reproducibility value of R=12 per cent for contamination levels of between 50‐400 PPM and r=0.6 PPM and R=2 PPM, respectively, at values below 50 PPM; the RDE cannot predict the absolute value of contamination if this includes large or dense particles if proper sample pre‐treatment is not used. It is therefore not good at detecting wear mechanisms that produce dense/large particles (if the oil samples are not pre‐treated properly) such as pitting but should be able to detect abrasive wear and similar processes that produce small particles in any case; the RDE's precision of measurement is not as good as the ICP, with a reproducibility variation of R=r=25 per cent for contamination levels between 20‐500 PPM and R=r=6 PPM for contamination level below 20 PPM.

Measuring only on fully formulated oils from hydraulic and gear systems.

The study will be of significant support regarding industrial interpretation of measurement results from the most common oil particle measurement methods.

No other similar studies are known.

The purpose of this paper is to present a practical model to determine the economic replacement time (ERT) of production machines. The objective is to minimise the total cost of capital equipment, where total cost includes acquisition, operating, maintenance costs and costs related to the machine’s downtime. The costs related to the machine’s downtime are represented by the costs of using a redundant machine.

In total, four years of cost data are collected. Data are analysed, practical optimisation model is developed and regression analysis is done to estimate the drilling rigs ERT. The artificial neural network (ANN) technique is used to identify the effect of factors influencing the ERT of the drilling rigs.

The results show that the redundant rig cost has the largest impact on ERT, followed by acquisition, maintenance and operating costs. The study also finds that increasing redundant costs per hour have a negative effect on ERT, while decreases in other costs have a positive effect. Regression analysis shows a linear relationship between the cost factors and ERT.

The proposed approach can be used by the decision maker in determining the ERT of production machines which used in mining industry.

The research proposed in this paper provides and develops an optimisation model for ERT of mining machines. This research also identifies and explains the factors that have the largest impact on the production machine’s ERT. This model for estimating the ERT has never been studied on mining drilling rigs.

A common model in the age‐based replacement policy is based on the cost attribute and assumes that the model parameters are known. In practice, the model parameters are estimated from limited historical data, which brings uncertainty into the model. Moreover, minimizing the cost is not the only goal of the maintenance activity. From the decision maker's point of view, the multi‐attributes and the uncertainty of the age‐based replacement policy are two important aspects to take into consideration in the decision‐making process. The purpose of this paper is to propose an approach for a robust‐optimum multi‐attribute age‐based replacement policy.

The proposed approach is based on a combination of the multi‐attribute age‐based replacement policy and robust design problem philosophy. A case study is provided for illustrating the application of the proposed method.

It is found that the proposed approach can determine the interval time for preventive replacement that provides a robust and optimum solution for a multi‐attribute age‐based replacement policy.

The proposed approach can be used by the decision maker in determining a robust‐optimum interval time for preventive replacement of multi‐attribute age‐based replacement, a time interval which is not only optimum, but also robust.

This paper presents an approach that simultaneously considers the multi‐attributes and the uncertainty in the age‐based replacement policy which is, to date, not available.

The purpose of this paper is to analyse and compare the downtime of four drilling machines used in two underground mines in Sweden. The downtime of these machines was compared to show what problems affect downtime and which strategies should be applied to reduce it.

The study collects failure data from a two-year period for four drilling machines and performs reliability analysis. It also performs downtime analysis utilising a log-log diagram with a confidence interval.

There are notable differences in the downtime of most of the studied components for all machines. The hoses and feeder have relatively high downtime. Depending on their downtime, the significant components can be ranked in three groups. The downtime of the studied components is due to reliability problems. The study suggests the need to improve the reliability of critical components to reduce the downtime of drilling machines.

The method of analysing the downtime, identifying dominant factors and the interval estimation for the downtime, has never been studied on drilling machines. The research proposed in this paper provides a general method to link downtime analysis with potential component improvement. To increase the statistical accuracy; four case studies was performed in two different mines with completely different working environment and ore properties. Using the above method showed which components need to be improved and suggestions for improvement was proposed and will be implemented accordingly.

Tourist destinations are constantly changing products, evolving as per the controls exerted by the stakeholders. The study aims to map the pattern of tourism development and identify the strategies formed at the destination over a seven-decade period for a state as a unit of analysis.

The paper evaluates tourism development through the tourism area life cycle (TALC) model and uses Mintzberg's strategy analysis process to identify strategies. The study involves time series analysis, pattern matching and explanation-building techniques. The TALC is plotted for the number of tourist arrivals from 1947 to 2019, and strategies are mapped for each stage.

The TALC shows a cycle-recycle pattern of tourism development. The research revealed several strategies at different stages. Both the central and state governments and entrepreneurs, distinctively and in conjunction, have formed strategies. The pattern shows the period of piecemeal and global strategic changes contributing to tourism development.

The research unearths the strategies that drive the development curves of TALC, emphasising the integration of TALC with other theories. The research also assesses the strategy formed in the pre-tourism stage.

The research brings to light the use of TALC as a strategic road-mapping tool. In addition, the study emphasises the significance of global and piecemeal strategic periods and stakeholder's regulatory and operational roles.

The research uses a unique methodology that maps the strategies, periods of strategic changes and incremental strategies for each stage of TALC, along with identifying the stakeholders.

The aim of this study is to determine the variation of the different oil analysis instruments in terms of standard deviation and CV‐values, when measuring samples of fully formulated hydraulic and gear oils taken from working systems.

In this investigation, two different spectrometric techniques, inductively coupled plasma‐optical emission spectrometers (ICP‐OES) and rotating disk electrode‐optical emission spectrometers (RDE‐OES), have been studied to determine the instruments' precision of measurement and ability to measure the absolute level of contamination. The study was based on a series of measurements using artificial contamination mixed with oil.

The ICP has better precision of measurement of the two instruments, but cannot predict the absolute values of contamination when oil samples are only treated by organic solvent dilution if the samples include large or dense particles. It is therefore not too good, with the sample pre‐treatment method used, at detecting wear processes that produce dense/large particles, such as pitting failure. For instance, microwave‐assisted acid digestion could be used for sample pre‐treating to obtain accurate results in that case. It should, however, be able to detect wear mechanisms that produce small particles such as abrasive wear in any case. The ICP has a repeatability value of r=3 percent and a reproducibility value of R=12 percent for contamination levels of between 50 and 400 ppm and r=0.6  and R=2 ppm, respectively, at values below 50 ppm. The RDE cannot predict the absolute value of contamination if this includes large or dense particles if proper sample pre‐treatment is not used. It is therefore not good at detecting wear mechanisms that produces dense/large particles (if the oil samples are not pre‐treated properly) such as pitting but should be able to detect abrasive wear and similar processes that produce small particles in any case. The RDE's precision of measurement is not as good as the ICP, with a reproducibility variation of R=r=25 percent for contamination levels between 20 and 500 ppm and R=r=6 ppm for contamination level below 20 ppm.

Only the effects from lubricating oils are studied.

This study will significantly increase the industrial knowledge concerning measurement precision in particle contamination measurement systems.

No similar study is found.