John H. Williams – författare

Condition-based monitoring is an accepted feature of many industries: petro-chemical, power generation, coal mining and steel-making, for instance. In manufacturing, its application has been somewhat muted.This text attempts to present the fundamental justification for condition-based maintenance together with enough analytic and practical guidance for its implementation. There are chapters on the two dominant techniques of vibration and debris analysis. Also, basic diagnostic methods are given along with a presentation of the systems approach to condition monitoring. A detailed case study shows the practical application of the techniques presented. Finally, future developments in the use of expert systems and A1 techniques are highlighted.Condition-based Maintenance and Machine Diagnostics gives details of both off-the-shelf solutions and analytic diagnostic techniques to enable a bespoke solution to be developed.It is suitable for senior undergraduates and postgraduates in the field of manufacturing and industrial engineering, and it furnishes managers in industry with sufficient information to judge the usefulness of the techniques for their particular application.

Data mining is a technique used to discover and present data in useful form to support decision making. This work responds to the need for a multi-disciplinary research resource, offering various perspectives on the social construction of reality and how different people make sense of the same information at different times. For example, in the section addressing information retrieval, subject relevance - chosen based upon the user's construction or pertinence - is contrasted with objective relevance, a system-based relationship that is measured by aspects of the subject matter and its universe. Format, use, currency, relevance, reliability, and validity are all basic elements of information quality that are explored in the research presented. Other strands include information architecture, Text Retrieval Conferences (TREC), machine learning, biometric technologies, computer interfaces, the interoperability of networked retrieval systems, and other research topics related to information retrieval.