A knowledge based machine tool maintenance planning system using case-based reasoning techniques - Wan, Shan; Li, Dongbo; Gao, James; Li, Jing (Robotics and computer-integrated manufacturing, 2019)
•This paper is focused on knowledge classification and modelling, knowledge is classified into three dimensions and maintenance case is represented by description units.•Adaptation guided case-based reasoning is researched in this paper, in which both concept relevancy and concept similarity are considered in the retrieving stage.•Industrial example is illustrated to show the effectiveness of the proposed method in this paper.•A prototype maintenance planning system has been implemented by using an open source content management system to further verify the proposed method. In advanced manufacturing systems, Computer Numerical Control (CNC) machine tools are important equipment to manufacture product components of high precision, whilst from equipment maintenance point of view, they are regarded as the ‘products’ provided by machine tool manufacturers. Therefore, the reliability of CNC machine tools affects not only the quality of the components they manufacture, but also the reputation and profits of equipment suppliers. This paper presents a novel knowledge based maintenance planning system to facilitate information and knowledge sharing between all stakeholders including machine tool manufacturers, users (manufacturing systems), maintenance service providers and part suppliers (for machine tools), in the emerging ‘Product-Service’ business model. Case Based Reasoning principles have been implemented to improve the efficiency of maintenance planning. Ontologies were adopted to represent field knowledge using adaptation guided retrievals based on semantic similarity and correlation. The adaption algorithm has been developed based on the Casual Theory and the dependence relationship to generate the solution for required maintenance problems. The proposed system was implemented using Content Management technologies and has been verified using an example CNC machine tool. The results were commented by industrial collaborators as very promising and further exploitation in industry was recommended.