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Civil-Comp Proceedings
ISSN 1759-3433 CCP: 81
PROCEEDINGS OF THE TENTH INTERNATIONAL CONFERENCE ON CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING COMPUTING Edited by: B.H.V. Topping
Paper 28
Retrieving Knowledge for Falsework Safety Inspection C.C. Huang, N.S. Al-Kaabi and F.C. Hadipriono
Department of Civil and Environmental Engineering and Geodetic Science, The Ohio State University, Columbus, Ohio, United States of America C.C. Huang, N.S. Al-Kaabi, F.C. Hadipriono, "Retrieving Knowledge for Falsework Safety Inspection", in B.H.V. Topping, (Editor), "Proceedings of the Tenth International Conference on Civil, Structural and Environmental Engineering Computing", Civil-Comp Press, Stirlingshire, UK, Paper 28, 2005. doi:10.4203/ccp.81.28
Keywords: safety inspection, worker safety, database, concreting.
Summary
This paper treats safety issues related to safety knowledge of falsework for concreting
operations, which is a part of almost all concreting construction projects. In doing so, the
authors focus on safety issues unique to this operation, such as the stability of the
concreting forms and their supports.
Concreting operations are the most important and critical steps in the reinforced concrete construction cycle. Falsework is used to temporarily support the concrete until sufficient concrete strength has developed. Substantial research efforts have been devoted to assure safety of workers and the structure during the falsework operations. An earlier study on falsework collapse during the construction stage shows that significant causes could result in falsework collapse [1]. Though the causes of the collapse varied and are often unclear, most of these causes could have been eliminated proactively through a proper safety inspection. In a conventional construction practice, safety inspection of concreting falsework is conducted during the concreting operation cycle using a preprinted, general purpose checklist that covers the most significant items of the target operations. The inspector makes and records his or her comments on each inspection item on the preprinted checklist. This commonly used paper-based inspection checklist has been accepted industry-wide as a means of improving construction safety and quality. However, construction is a very unique manufacturing industry by nature. The magnitude of projects could range from very small projects to very huge structures. Each construction project is often a one of a kind product with unique characteristic. The falsework activities involved in the concreting operations also vary from one project to another. Conventional paper based inspection checklists are designed to fit numerous construction projects regardless of the variation among different projects. Hence, from adaptability aspects, the conventional paper-based checklist has its limitation. As a result, consistency of the conventional pre-printed checklists is often difficult to maintain. Therefore, it is necessary to come up with an approach of generating a checklist that is suitable for various types of concreting falsework inspection. Besides the limitation of adaptability, paper based checklists lack the accessibility for safety knowledge. To perform a high-quality safety inspection of concreting falsework, an inspector should rely on a comprehensive safety knowledge, which includes not only the articulated safety codes and regulations but also experience and the ability to recognize hazards. Paper based checklist can only provide very limited safety knowledge. The development of an appropriate methodology that helps safety inspectors access comprehensive and well organized safety knowledge is therefore essential. In addition, safety requirements and regulations are frequently not clear or specific, yet they are useful. Therefore fuzzy logic is applied to treat the vagueness and ambiguity contained in the safety inspection processes [2]. This paper introduces a methodology that uses query process and fuzzy operations to retrieve safety inspection knowledge of concreting falsework from a database. The motivation of using fuzzy set theory to the safety knowledge database is to deal with the imprecise nature of safety issues. The potential benefit of safety knowledge database is that it can store both precise safety regulations and imprecise information like expert experience, judgments, or linguistic values. When implemented, the model created by the authors will generate a safety inspection checklist that is suitable for a particular type of falsework operation by querying safety knowledge database through an application program. References
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