Manufacturing Knowledge Management Sep Sep 2010 Manufacturing Knowledge Warehouse Development Investigator: Asmaa Alabed Supervisor: Xun Chen Industrial collaborator: Rolls-Royce plc. Aim & Objectives The aim of the research is to facilitate knowledge management process for grinding technology by building a flexible and easy to use knowledge based warehouse (KW), which could manage both explicit and tacit knowledge. The objectives are to design and develop the following modules: Date Interface (DIM) Database (DBM) Problem Solving (PSM) Learning Knowledge Discovery (LKDM) Knowledge warehouse (KWM) Knowledge Analysis (KAM). Methodology The Grinding Knowledge Warehouse (GKW) includes six modules as shown in Figure 1. DIM collects the data through the data collection interface and Community of Practices (CoP’s) members. DBM stores, retrieves, and shares data in various formats. These data will then transfer to PSM and LKDM, which will provide the user a guidance for selecting grinding conditions. KAM facilitates knowledge conversion from tacit to explicit knowledge by directly acquiring the tacit knowledge from knowledge engineers or CoP members. Also, KAM provides the interface for CoP members and knowledge engineers. The core of PSM includes Case Based Reasoning and Rule Based Reasoning. LKDM extracts implicit, previously unknown and potential useful rules and patterns to modify and update existing rules and patterns. The GKW will be integrated into a internet based framework for a wide accessibility. Results The structure of grinding knowledge has been analysed and a framework of a grinding knowledge warehouse is constructed to facilitate knowledge management. In order to acquire an overview and awareness of the grinding knowledge sharing activities in Rolls Royce, several meetings and discussions were carried out. Community of practice is used as a sharing knowledge tool between the employees. Statistical analysis between two different communities was conducted to evaluate their performance as shown in Chart 1 and Chart 2. It has noticed that a knowledge warehouse should make knowledge more accessible for users, should retrieve knowledge more efficiently and quickly, and should facilitate extracting knowledge from CoP. Potential Benefits and Future Plans The new KW will encourage and facilitate the sharing of explicate and tacit knowledge. The grinding cases will be kept in the knowledge warehouse that will support the decision making process for selecting grinding conditions for new processes and optimisation. As a result, it will save the time for CoP members by providing them with most relative answer to their questions. It also helps them sharing up-to-date knowledge. Currently, the database module has been developed using Access 2000 and Visual Basic. The problem solving knowledge discovery module includes Case Bases Reasoning (CBR) and Rule Based Reasoning (RBR). The further work will integrate all the modules into a systems which allow users to access the knowledge warehouse via the internet. Chart 1 Percentage for Group A Chart 2 Percentages for Group BFigure 1 Methodology