In plant partial noise enclosures for the mining industry /

Shipping list no.: 93-0394-P.

Annual report of the mining industry of Idaho.

Mode of access: Internet.

Economic impact of dissolved solids regulation upon the coal mining industry (R76-7) /

Includes bibliographical references.

An outline of political economy, designed for seminaries, and intended to explain the principles of this important science, by familiar examples, and to exhibit more particularly the great importance of agriculture, mining industry, manufactures, and internal imporvements to national wealth and prosperity.

Goldsmiths'-Kress no. 25475.11.

Current developments in deep seabed mining : hearing before the Subcommittee on Minerals, Materials, and Fuels of the Committee on Interior and Insular Affairs, United States Senate, Ninety-fourth Congress, first session, on briefing by ocean mining industry, November 7, 1975

Bibliography: p. 244-245

The Work crew performance model : a method for evaluating training and performance in the mining industry /

Includes bibliographical references.

Roughing it in Siberia, with some account of the Trans-Siberian railway, and the gold-mining industry of Asiatic Russia,

Mode of access: Internet.

West Australian mining practice; a description of the mining methods followed by the principal gold mines of Western Australia,

Mode of access: Internet.

The mining industry in that part of northern ontario

Mode of access: Internet.

Summary of selected injury experience and worktime for the mining industry in the United States, 1931-77 /

Chiefly tables.

An evolutionary economic perspective on technical change and adjustment in cane harvesting systems in the Australian sugar industry

Australian sugar-producing regions have differed in terms of the extent and rate of incorporation of new technology into harvesting systems. The Mackay sugar industry has lagged behind most other sugar-producing regions in this regard. The reasons for this are addressed by invoking an evolutionary economics perspective. The development of harvesting systems, and the role of technology in shaping them, is mapped and interpreted using the concept of path dependency. Key events in the evolution of harvesting systems are identified, which show how the past has shaped the regional development of harvesting systems. From an evolutionary economics perspective, the outcomes observed are the end result of a specific history.

The productivity-inflation nexus: The case of the Australian mining sector

This paper examines the causal links between productivity growth and two price series given by domestic inflation and the price of mineral products in Australia's mining sector for the period 1968/1969 to 1997/1998. The study also uses a stochastic translog cost frontier to generate improved estimates of total factor productivity (TFP) growth. The results indicate negative unidirectional causality running from both price series to mining productivity growth. Regression analysis further shows that domestic inflation has a small but adverse effect on mining productivity growth, thus providing some empirical support for Australia's 'inflation first' monetary policy, at least with respect to the mining sector. Inflation in mineral price, on the other hand, has a greater negative effect on mining productivity growth via mineral export growth.

Quantification of geological uncertainty and risk using stochastic simulation and applications in the coal mining industry

Stochastic simulation is a recognised tool for quantifying the spatial distribution of geological uncertainty and risk in earth science and engineering. Metals mining is an area where simulation technologies are extensively used; however, applications in the coal mining industry have been limited. This is particularly due to the lack of a systematic demonstration illustrating the capabilities these techniques have in problem solving in coal mining. This paper presents two broad and technically distinct areas of applications in coal mining. The first deals with the use of simulation in the quantification of uncertainty in coal seam attributes and risk assessment to assist coal resource classification, and drillhole spacing optimisation to meet pre-specified risk levels at a required confidence. The second application presents the use of stochastic simulation in the quantification of fault risk, an area of particular interest to underground coal mining, and documents the performance of the approach. The examples presented demonstrate the advantages and positive contribution stochastic simulation approaches bring to the coal mining industry