Use of Patterns for Knowledge Management in the Ceramic Tile Design Chain

Knowledge Management (KM) is a complex objective, especially in the instance of extended enterprises consisting of SMEs, and critical in new product design and development (NPD). The use of patterns is essential to get KM in collaborative NPD processes. This paper presents the use of patterns adopted in the CE-TILE project to standardize information and knowledge in collaborative work. The different types of patterns and models established for the knowledge capture, formalization and configuration are also described

An efficient phased mission reliability analysis for autonomous vehicles

Autonomous systems are becoming more commonly used, especially in hazardous situations. Such systems are expected to make their own decisions about future actions when some capabilities degrade due to failures of their subsystems. Such decisions are made without human input, therefore they need to be well-informed in a short time when the situation is analysed and future consequences of the failure are estimated. The future planning of the mission should take account of the likelihood of mission failure. The reliability analysis for autonomous systems can be performed using the methodologies developed for phased mission analysis, where the causes of failure for each phase in the mission can be expressed by fault trees. Unmanned Autonomous Vehicles (UAVs) are of a particular interest in the aeronautical industry, where it is a long term ambition to operate them routinely in civil airspace. Safety is the main requirement for the UAV operation and the calculation of failure probability of each phase and the overall mission is the topic of this paper. When components or sub-systems fail or environmental conditions throughout the mission change, these changes can affect the future mission. The new proposed methodology takes into account the available diagnostics data and is used to predict future capabilities of the UAV in real-time. Since this methodology is based on the efficient BDD method, the quickly provided advice can be used in making decisions. When failures occur appropriate actions are required in order to preserve safety of the autonomous vehicle. The overall decision making strategy for autonomous vehicles is explained in this paper. Some limitations of the methodology are discussed and further improvements are presented based on experimental results

Integrating VR and knowledge-based technologies to facilitate the development of operator training systems and scenarios to improve process safety

Process safety can be regarded of paramount importance since any malfunction or mal-operation of a hazardous processing plant may lead to accidents that will cause damage to properties, injury to people and may even result in fatalities. This project investigates how Virtual Reality (VR) and knowledge-based (in particular rule-based) technologies may be combined to provide an effective tool for implementing operator training systems to deal with different scenarios for any given plant. VR is one of the fastest developing visualisation technologies. Through VR, a trainee can be immersed in the realistic simulated environment, which is helpful in providing operating experience without having to worry about causing any accidents or operational difficulties of the real plant. However, it is necessary to provide flexible ways of capturing and specifying the expertise for evaluating the action of the trainee without hard coding everything into the simulation system. The proposed solution is to couple the VR simulation tool with a knowledge-based tool, or more specifically a rule-based tool. The VR tool is responsible purely for the user interaction and updating the state of the simulated plant. On the other hand, a set of expert rules is specified in the rule-base in a high level declarative format. Every time the plant changes state, the rule-based tool will check the new state of the plant against its set of rules. If the plant is in an undesirable or unsafe state then an appropriate warning will be issued or an appropriate message will be passed to the VR tool. Different training scenarios can be easily developed by changing the plant description and/or the rule set. This paper describes the overall system architecture and provides some details about the separate tools. An example is used to illustrate the working of the system. On-going research issues will also be highlighted and discussed. © 2006 Taylor & Francis Grou

HAZID, a computer aid for hazard identification:3. The fluid model and consequence evaluation systems

The hazard and operability, or HAZOP, study is a prime method for the identification of hazards on process plants. This is the third in a series of papers which describes progress in the emulation of hazard identification in the style of HAZOP. The work reported is embodied in a computer aid for hazard identification, or HAZOP emulator, HAZID. The HAZID code is one of a suite of codes developed as part of the STOPHAZ project. The present paper describes the fluid model system and the evaluation of consequences.Companion papers describe: an overview of HAZID, with an account of HAZOP and HAZOP emulation, and of the issues underlying it; the unit model system; the evaluation and improvement of HAZID using case studies and other methods; some development topics. Conclusions from the work are given in the final paper