The main objective of manufacturing companies is to achieve increased productivity, high plant availability, high quality rate, and increased safety, at the most competitive cost. Data collected by only one condition monitoring parameter are, sometimes, insufficient to achieve effective assessment of the condition of a machine due to its limited ability to cover the required information and the inherent uncertainty in the acquired data. The problem addressed in this paper, is how to keep availability, quality, and productivity at high levels through utilizing a common database, i.e. integrating the database of condition-based maintenance system with the main plant IT-system, for an innovative expert system. It was found that most research is focused on tool and process monitoring, using various types of condition monitoring parameters, to predict tool wear and tool life. Intelligent manufacturing systems techniques, e.g. Expert System, Fuzzy Logic and Neural Networks, are being used to integrate and interpret data from multiple sensors. But less attention was devoted to the development of integrated condition monitoring systems, which enable the user to evaluate a multi-variant system based on the data collected from, e.g. maintenance, quality, production and accountancy. The major conclusion is that; using an innovated expert system, based on a common database having better data coverage and quality, and a continuously improved knowledge base with intelligent inference engine, one can enhance the reliability of data, certainty of decision making, remove the redundancy in the monitoring system, and allow the user to detect and eliminate reasons behind variations through effective diagnosis and prognosis. This leads to continuous improvement in quality, productivity and availability at a reduced cost, and improved effectiveness of the manufacturing system