This review article provides a comprehensive analysis of nesting optimization algorithms in the shipbuilding industry,emphasizing their role in improving material utilization,minimizing waste,and enhancing production ...
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This review article provides a comprehensive analysis of nesting optimization algorithms in the shipbuilding industry,emphasizing their role in improving material utilization,minimizing waste,and enhancing production *** shipbuilding process involves the complex cutting and arrangement of steel plates,making the optimization of these operations vital for cost-effectiveness and *** algorithms are broadly classified into four categories:exact,heuristic,metaheuristic,and *** algorithms ensure optimal solutions but are computationally *** contrast,heuristic algorithms deliver quicker results using practical rules,although they may not consistently achieve optimal *** algorithms combine multiple heuristics to effectively explore solution spaces,striking a balance between solution quality and computational *** algorithms integrate the strengths of different approaches to further enhance *** review systematically assesses these algorithms using criteria such as material dimensions,part geometry,component layout,and computational *** findings highlight the significant potential of advanced nesting techniques to improve material utilization,reduce production costs,and promote sustainable practices in *** adopting suitable nesting solutions,shipbuilders can achieve greater efficiency,optimized resource management,and superior overall *** research directions should focus on integrating machine learning and real-time adaptability to further enhance nesting algorithms,paving the way for smarter,more sustainable manufacturing practices in the shipbuilding industry.
In the process of cement equipment manufacturing, the demand of rectangle pieces of steel structure is very large. The traditional manual nesting, which is simply cutting by hand-making according to the arrangement of...
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In the process of cement equipment manufacturing, the demand of rectangle pieces of steel structure is very large. The traditional manual nesting, which is simply cutting by hand-making according to the arrangement of the number and size, causes the low efficiency and material wasting. To solve the problem above, this paper proposes an optimizing model for nesting problem of rectangle pieces. Firstly, with the aim of the maximum utilization ratio of the sheet, the optimization mathematical model for nesting problem of rectangle pieces is established. The lowest horizontal line searching algorithm is described in detail. Secondly, the mathematical model is solved to get the optimal solution by the combination of genetic algorithm and the lowest horizontal line searching algorithm. In the solution process, this paper presents the methods of gene encoding and decoding, definition of fitness function, the design of genetic operators and the design of algorithm operating parameters. Finally, we use one sheet as an example to illustrate the proposed model and algorithm process. Experimental results have shown that the proposed approach is able to achieve rectangle pieces nesting with the maximum material utilization ratio.
According to integration requirements of design, process and manufacturing in railway vehicle manufacturing enterprises, an integration solution centered at material quota and key technologies are proposed, which incl...
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ISBN:
(纸本)9780878492435
According to integration requirements of design, process and manufacturing in railway vehicle manufacturing enterprises, an integration solution centered at material quota and key technologies are proposed, which includes the data integration technology between PDM, CAPP, FastCut/Nest, ERP on the server layer;the Data Pre-process technology for design and process integration: the automatic nesting optimization technology meeting practical production requirements;the method to calculate material quota based on nesting optimized layouts;and the sharing of general NC codes. Considering automatic nesting optimization and material quota computing, a solution for split/combination data pre-processing and post-processing is proposed and implemented. And practical production conditions are taken into account in the nesting algorithm. All these technologies and solutions support the integration centered at material quota for design, process and manufacturing.
In rail-vehicle manufacturing enterprises, material costs are main part of total costs, so nesting optimization and material quota is important for enterprise's cost control and supply chain management. Because mo...
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ISBN:
(纸本)9783540927181
In rail-vehicle manufacturing enterprises, material costs are main part of total costs, so nesting optimization and material quota is important for enterprise's cost control and supply chain management. Because most parts are rectangular, rectangular object layout is solved first in nesting optimization. Rectangular object layout is not a simple NP (nondeterministic polynomial) optimization problem because of the practical production rules, such as guillotine. Under certain situations, the guillotine is even more important than the pure using ratio of metal sheets. The purpose of this paper is to construct the model of genetic algorithm and design the genetic operators for a practical case. Combined with the lowest-horizontal-line search algorithm, Genetic algorithm model is applied into rectangular object layout optimization. Results show that the model can satisfy not only the practical production requirements of guillotine, but also the requirement for production convenience. In this way, users can get optimal layout results and a higher material using ratio for practical production effectively and quickly.
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