This paper presents the results obtained for the initial application of a management evaluation system whose objective is to provide a continuous improvement tool for construction companies through benchmarking management practices. The outlined system seeks to support a benchmarking system that has been recently established in the Chilean construction industry by incorporating qualitative management aspects in addition to performance indicators. Different analyses were made to determine trends in the sector and to establish correlations between qualitative aspects coming from surveys and quantitative aspects coming from performance indicators. Thirteen construction companies participated in the initial application of the benchmarking system. A correlation analysis found that safety performance was strongly related to companies having superior planning and control, quality management, cost control, and subcontractor management policies. A factor analysis found that central office priorities focus on strategic management policies having longer-term competitive impact, while site management emphasizes tactical management dimensions having short-term impact. There is scope to elevate the profile of continuous improvement initiatives to strategic significance at the central office level.

Pareto histograms are commonly used to determine maintenance priorities by ranking equipment failure codes according to their relative cost or downtime contribution. However, such histograms do not readily enable identification of the dominant variables influencing downtime and repair costs, namely the failure frequency, mean downtime and mean repair cost associated with each failure code. Advances an alternative method for analysing equipment downtime and repair costs using logarithmic (log) scatterplots. By applying limit values, log scatterplots can be divided into four quadrants enabling failures to be classified according to acute or chronic characteristics and facilitating root cause failure analysis. Log scatterplots permit the identification of frequently occurring failures that consume relatively little repair cost or downtime yet cause frequent operational disturbances leading to production losses. In addition, by graphing the trend of failure data over successive time periods, log scatterplots provide a useful visual means of evaluating the performance of maintenance improvement initiatives. Provides examples of the practical application of log scatterplots by a number of mining companies and mining equipment suppliers in Chile. Practical implicationsPareto histograms of equipment failure codes ranked according to downtime or repair costs do not enable the influence of the failure frequencies or the mean downtime or repair cost to be clearly identified. Logarithmic scatterplots enable failures to be classified according to acute or chronic characteristics, and provide a better means of establishing maintenance priorities. In addition, logarithmic plots can be used to graph trends in maintenance performance.

No abstract

Maximising value is the main objective when developing long term mine production schedules. These results provide input for the development of a short term schedule that aims to meet process plant feed requirements so as to produce a quality saleable product. This paper reviews previous work on optimised short-and long term production scheduling and real time fleet management systems. A new dynamic mathematical model using mixed integer programming is proposed to optimise short term production scheduling and machine allocation for application in sublevel stoping operations. The objective of the model is to minimise deviation from targeted metal production. The dynamic nature of the model not only optimises the shift based schedule but also allows rapid equipment reassignment to take place as underground operating conditions change. Optimal results are generated in less than 1 min when trialled on a conceptual sublevel stoping dataset.