Construction of Industrial facilities involves a substantial amount of piping. Pipe spools are usually pre-fabricated from a number of raw pipes and pipe fittings (e.g. elbows, flanges, tees, etc.) in fabrication shops. Pipe spool fabrication is often affected by various disruptions from within or outside the shops. Previous research mainly focuses on shop layouts, dispatching rules, buffer location and standardized products. Another critical factor, the sequencing of pipe spool fabrication, is usually overlooked. A pipe spool can be fabricated in several alternative sequences that are often decided by shop foremen based on experience. It is rare that these alternative sequences get compared and evaluated. A simulation experiment shows that shop productivity can be improved by varying spool fabrication sequence. This paper presents an investigation of Artificial Intelligence (AI) planning approach that automatically identifies the optimal fabrication sequence for pipe spools while considering various fabrication logics. Experiments are conducted with different AI planners to evaluate their capabilities. The results indicate that one of the planners is more suitable for solving the sequencing problem than others. However, it requires special pre-processing of the input that may be prohibiting for practical use. Directions of future research to overcome these limitations are discussed.

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Published on 01/01/2012

Volume 2012, 2012
DOI: 10.1061/9780784412329.050
Licence: CC BY-NC-SA license

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