Data mining offers an effective solution to product and process diagnosis in that it requires no additional equipment or capital investment and it does not cause interruption to production and operations. The most important role of data mining is the ability to separate data into different classes so that an accurate model can be built for fault detection, recognition and prediction. The propos...

Data mining has burst into the limelight recently, thanks to a series of key application successes [2]. Big business and industry has raised the stakes by investing in this nascent technology, and has laid down high expectations for this emerging area. Although the methods and systems for data mining are based upon and in uenced by years of classical work in statistics, pattern recognition, inf...

Data Mining tools extract knowledge from large databases. The data generated in manufacturing has not been entirely exploited. This chapter discusses applications of Data Mining in a manufacturing environment. A methodology for selection of manufacturing processes is proposed and illustrated with an industrial scenario.

AMd is recognized as one of the most serious environmental problem in the mining industry. the problem of acid mine drainage (AMd) has been present since mining activity began thousands of years ago. Mining activity has disrupted the hydrology of mining areas so badly that it is extremely difficult to predict where water would eventually re-emerge. its causes, treatment have become the focus of...

OBJECTIVE Traditional gold mining is associated with mercury exposure. Especially vulnerable to its neurotoxic effects is the developing nervous system of a child. We aimed to investigate risk factors of mercury exposure among children in a rural mining town in Chile. METHODS Using a validated questionnaire distributed to the parents of the children, a priori mercury risk factors, potential e...

Data mining offers tools for discovery of relationships, patterns, and knowledge in large databases. The knowledge extraction process is computationally complex and therefore a subset of all data is normally considered for mining. In this paper, numerous methods for decomposition of data sets are discussed. Decomposition enhances the quality of knowledge extracted from large databases by simpli...

Business process re-engineering and data mining are currently popular discussion topics in business and industrial environments. One main area for discussion is how organisations can be prepared to facilitate data mining technologies appropriately. Based on the two main phases on business process reengineering, the data mining process, and the involved expertise respectively, a synthesis of bot...