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Celik, T (1989) Improving concrete quality by using an expert system, Unpublished PhD Thesis, Department of Civil Engineering, Loughborough University of Technology.
- Type: Thesis
- Keywords: case study; concrete; experiment; expert system; prototype development; quality; workmanship
- URL: https://hdl.handle.net/2134/11154
There is great scope for problems and deficiencies in the workmanship of concreting operations, namely: batching, mixing, transporting, placing, compacting, finishing and curing. These problems will adversely affect the quality of the finished concrete. Improving the knowledge and experience of the supervisory staff and workmen on construction sites is essential if these deficiencies are to be minimized. It has been observed that specifications for concreting activities contain insufficient information regarding workmanship. This causes difficulties in controlling the concreting operations. This thesis addresses the problems associated with the transfer of knowledge from acknowledged experts in concreting operations to site practitioners. It is proposed that an appropriate tool for this information transfer is the use of computer based expert systems. Therefore, an expert system, called ESCON, has been developed to advise on concreting activities. The knowledge of this system was acquired from technical literature, site visits, self experience, and by interviewing experts in the domain. ESCON is capable of: 1) defining and diagnosing concreting problems; 2) giving expert recommendations for the solution of these problems. including the reasons behind the solution; 3) educating inexperienced staff by improving their appreciation of the domain; 4) preparing comprehensive specifications including information on the. workmanship requirements of concreting procedures; 5) calculating the expected loss in the strength of concrete when recommendations are ignored. Experimental work was undertaken at CITB (Construction Industry Training Board), Bircham Newton, Norfolk, to assist in the verification of the model. The model was tested by undertaking five evaluation methods, including comparison of the result with an objective standard, sensitivity analysis, expert’s experience, novice users, and a real life case study.