Search Results (2)

In the field of scheduling, complex products with a tree structure often exhibit inherent asymmetric characteristics, while their processing resources are usually provided by symmetric workshops with functionally equivalent and interchangeable processing equipment. Aiming at the complex product integrated scheduling problem with due date constraints, this paper proposes a reverse integrated scheduling algorithm considering the workpieces’ time urgency degree and migration cost. Firstly, internet-connected equipment with the same function as the main workshop and the lowest transportation cost is virtualized as symmetrical outsourcing workshop equipment. Secondly, the workpiece scheduling strategy and distributed integrated scheduling strategy are proposed. Taking each workpiece as the trial scheduling unit, under the premise of meeting the delivery time, the quasi-scheduling scheme with the minimum total migration cost for the current workpiece is selected as the workpiece scheduling scheme. If not unique, the scheme with the minimum outsourcing processing time is selected. Finally, the algorithm in this paper is compared with other algorithms in the same research field. The experimental results show that the algorithm in this paper reduces the total cost of workpiece migration by 25% and the total time of outsourcing processing by 20% while meeting the order delivery time. It is proven that the symmetric processing resource scheduling system constructed by the algorithm in this paper can achieve the parallel scheduling optimization of workpiece processing, assembly, and migration for both symmetric-structure and asymmetric-structure complex products. Full article

The application of CAD/CAM technologies in modern production has revolutionized manufacturing processes, leading to significant improvements in precision, efficiency, and flexibility. These technologies enable the design and manufacturing of complex geometries with high accuracy, reducing errors and material waste. CAD/CAM integration streamlines workflows, enhances productivity, and facilitates rapid prototyping, accelerating the time-to-market for new products. Additionally, it supports customization and scalability in production, allowing for cost-effective small-batch and large-scale manufacturing. Without a 3D model of the product, it is not possible to use the advantages of applying advanced CAD/CAM technologies. Recognizing 3D models from engineering drawings is essential for modern production, especially for outsourcing companies in fluctuating market conditions, where the production process is organized with 2D workshop drawings on paper. This paper proposes a novel methodology for reconstructing 3D models from 2D engineering drawings, specifically those in DXF file format, leveraging a genetic algorithm. A core component of this approach is the representation of the 2D drawing as a symmetric adjacency matrix. This matrix serves as the foundational data structure for the genetic algorithm, enabling the evolutionary process to effectively optimize the 3D reconstruction. The experimental evaluation, conducted on multiple engineering drawing test cases (including both polyhedral and cylindrical geometries), demonstrated consistent convergence of the proposed GA-based method toward topologically valid and geometrically accurate 3D wireframe models. The approach achieved successful reconstruction in all cases, with fitness scores ranging from 1.1 to 112.2 depending on model complexity, and average execution times from 2 to 100 s. These results confirm the method’s robustness, scalability, and applicability in real-world CAD environments, while establishing a new direction for topology-driven 3D reconstruction using evolutionary computation. Full article