Process and knowledge management in a collaborative maintenance planning system for high value machine tools

Product manufacturers are extending their responsibilities in the whole life cycle by providing services to their customers. In recent years, product service system has become an important research topic to address the special requirements in the new service driven business model. High value machine tools in modern manufacturing factories are special products: they are regarded as 'products' from maintenance point of view, and they also manufacture other products. In the new business model, the quality and behavior of a machine tool not only affect the quality of the parts it manufactures, but also affect the profits of the machine tool's manufacturer. However, in the research area of product service systems and related computerized maintenance systems, there is a lack of investigation into the special nature, problems and requirements of high value machine tool maintenance, which are very important in modern digitized manufacturing systems. Therefore, this research investigated the various relationships between different stakeholders in the machine tools' lifecycle, focusing on knowledge management, communication and the decision-making processes. This research also explored the potential application of advanced content management systems, which are widely implemented in the financial, business and government organizations, in the manufacturing engineering domain which has been dominated by traditional engineering information systems. A prototype collaborative maintenance planning system is proposed, developed and evaluated using an example machine tool, which indicated that significant improvement could be achieved and the content management technology has a number of advantages over the traditional engineering information systems, such as computer aided engineering, product data and lifecycle management, and enterprise resource planning systems, in managing machine tool maintenance and service information including dynamic and unstructured knowledge. (C) 2016 Elsevier B.V. All rights reserved.