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Collecting and representing manufacturing knowledge
Published in Justyna Patalas-Maliszewska, Managing Manufacturing Knowledge in Europe in the Era of Industry 4.0, 2023
The preparation of a project and its implementation in manufacturing in accordance with the mass customisation strategy requires the use of knowledge about both the technical feasibility of the project and the client's requirements. A knowledge base is a collection of related and linked data and information; it also stores formalised expert knowledge. Building knowledge bases in enterprises is a response to the problem of limited access to the knowledge held, allowing one to organise the process of reaching the necessary knowledge by an employee while searching for an answer to a specific problem.
Knowledge-Based Expert System
Published in C.S. Krishnamoorthy, S. Rajeev, Artificial Intelligence and Expert Systems for Artificial Intelligence Engineers, 2018
C.S. Krishnamoorthy, S. Rajeev
The process of collecting, organising and compiling the knowledge and implementing it in the form of a knowledge base is a labourious task. It does not end with the development of the system. The knowledge base has to be continuously updated and/or appended depending on the growth of knowledge in the domain. A knowledge acquisition facility, which will act as an interface between the expert/knowledge engineer and the knowledge base, can form an integral component of an expert system. As it is not an on-line component, it can be implemented in many ways.
Business Improvement through Innovation in Construction Firms: The ‘Excellence’ Approach
Published in Ben Obinero Uwakweh, Issam A. Minkarah, 10th Symposium Construction Innovation and Global Competitiveness, 2002
Herbert S. Robinson, Patricia M. carrillo, Chimay J. Anumba, Ahmed M. Al-Ghassan
Very often two databases are maintained. One of the data bases functions on a permanent basis and is used by the consumers, whereas the other one is being updated. Consumers can have access to the updated database. Every day consumers can also use the knowledge base with the experts’ system providing assistance in solving their own various problems. The knowledge base may contain various articles, recommendations, standard documentation and more information.
Development of an intelligent knowledge base for identification of accident causes based on Fu et al.’s model
Published in International Journal of Occupational Safety and Ergonomics, 2022
Nine unsafe acts, 15 unsafe conditions, 19 flaws in safety knowledge, safety awareness, safety habits, four deficiencies in the safety management system, 12 deficiencies in safety culture and no external factor were detected according to the results of the first case study for the test. Since all unsafe acts are found in the created knowledge base, the success rate for this category is 100%. Twelve out of 15 unsafe conditions were identified and a success rate of 80% was achieved. As 18 of the 19 flaws in safety knowledge, safety awareness, safety habits were found in the knowledge base, a high success rate of 95% was achieved. Four latent failures were found in the category of deficiencies in the safety management system, three of them were identified by the generated knowledge base via the case studies and 75% success was accomplished in this category. Since no external factors contributing to this accident were found, the data of external factors category in the knowledge base were not used. The overall success of the knowledge base can be calculated using the weighted average of category achievements. Accordingly, the knowledge base achieved 89.47% success in finding the accident causes in the test of the first case study.
Recommended layer thickness to the powder-based additive manufacturing using multi-attribute decision support
Published in International Journal of Computer Integrated Manufacturing, 2021
The possibilities of geometric controlling and editing offer complete flexibility in design freedom and innovations, but sometimes it does not satisfy all manufacturing aspects and rules. Understanding all manufacturing aspects and rules implies an upgrade of AM knowledge to all design phases (Bikas, Lianos, and Stavropoulos 2019). Problems that have arisen in the design evaluation process belong to the initial design phases, so the process has been limited by information-knowledge. It is crucial to develop a mechanism for parameters definition that guarantees quality production. An intelligent advisory application, as the knowledge-based decision support system provides an environment for mechanism setup. The system effectiveness depends on the quality of the knowledge base and its comprehensiveness. Therefore, the knowledge base is created in line with the following acquisitions: By studying relevant literature in the domain of DfAM,By collecting information from experts in the domain of DfAM,By using weighs in the product design evaluation.