An Intelligent Optimization Method of Reinforcing Bar Cutting for Construction Site

Abstract

To meet the requirements of specifications, intelligent optimization of steel bar blanking can improve resource utilization and promote the intelligent development of sustainable construction. As one of the most important building materials in construction engineering, reinforcing bars (rebar) account for more than 30% of the cost in civil engineering. A significant amount of cutting waste is generated during the construction phase. Excessive cutting waste increases construction costs and generates a considerable amount of CO 2 emission. This study aimed to develop an optimization algorithm for steel bar blanking that can be used in the intelligent optimization of steel bar engineering to realize sustainable construction. In the proposed algorithm, the integer linear programming algorithm was applied to solve the problem. It was combined with the statistical method, a greedy strategy was introduced, and a method for determining the dynamic critical threshold was developed to ensure the accuracy of large-scale data calculation. The proposed algorithm was verified through a case study; the results confirmed that the rebar loss rate of the proposed method was reduced by 9.124% compared with that of traditional distributed processing of steel bars, reducing CO 2 emissions and saving construction costs. As the scale of a project increases, the calculation quality of the optimization algorithm for steel bar blanking proposed also increases, while maintaining high calculation efficiency. When the results of this study are applied in practice, they can be used as a sustainable foundation for building informatization and intelligent development.

An Automatic Extraction Method of Rebar Processing Information Based on Digital Image

“…Based on the above values, the variance σ 2 0 of the foreground region and the variance σ 2 1 of the background region can be calculated.…”

“…At this stage, the processing of steel bars is mainly based on manual processing. Even the most advanced semi-automatic numerical control processing (CNC) equipment still needs manual extraction of the processing information of steel bars from the detail drawing of the rebar [1][2][3]. The main reason is that the steel bar processing information is stored in the form of the detail drawing of the rebar, but the equipment cannot directly identify the detail drawing to extract the steel bar's processing information, resulting in low processing efficiency of the steel bar.…”

Special Length Priority Optimization Model: Minimizing Wall Rebar Usage and Cutting Waste

“…Minimizing steel usage at the source is the most impactful approach to reducing material resource use and carbon emissions within the industry, and is itself a central tenet of sustainable construction practices [22][23][24][25]. Building structures consist of diverse elements, such as foundations, columns, beams, floors, walls, and stairs.…”