Intelligent 3D packing using a grouping algorithm for automotive container engineering

Abstract

Storing, and the loading and unloading of materials at production sites in the manufacturing sector for mass production is a critical problem that affects various aspects: the layout of the factory, line-side space, logistics, workers' work paths and ease of work, automatic procurement of components, and transfer and supply. Traditionally, the nesting problem has been an issue to improve the efficiency of raw materials; further, research into mainly 2D optimization has progressed. Also, recently, research into the expanded usage of 3D models to implement packing optimization has been actively carried out. Nevertheless, packing algorithms using 3D models are not widely used in practice, due to the large decrease in efficiency, owing to the complexity and excessive computational time. In this paper, the problem of efficiently loading and unloading freeform 3D objects into a given container has been solved, by considering the 3D form, ease of loading and unloading, and packing density. For this reason, a Group Packing Approach for workers has been developed, by using analyzed truck packing work patterns and Group Technology, which is to enhance the efficiency of storage in the manufacturing sector. Also, an algorithm for 3D packing has been developed, and implemented in a commercial 3D CAD modeling system. The 3D packing method consists of a grouping algorithm, a sequencing algorithm, an orientating algorithm, and a loading algorithm. These algorithms concern the respective aspects: the packing order, orientation decisions of parts, collision checking among parts and processing, position decisions of parts, efficiency verification, and loading and unloading simulation. Storage optimization and examination of the ease of loading and unloading are possible, and various kinds of engineering analysis, such as work performance analysis, are facilitated through the intelligent 3D packing method developed in this paper, by using the results of the 3D model.

Mathematical and computer modelling of optimiza-tion 3D packing problem

“…Огляд робіт, присвячених роз в'я занню тривимірних задач упаковки, свідчить, що дослідники використовують велику кількість різноманітних методів. Ці методи можна розпо-ділити на такі групи: евристичні методи [4][5][6][7]; традиційні методи оптимізації [8,9]; змішані підходи [10,11]. В них використовують евристики і методи нелінійної оптимізації.…”

PackIt: A Virtual Environment for Geometric Planning

“…Packing without learning: There has been work done in the engineering design literature that uses genetic algorithms to search a solution for luggage packing problems (Tiwari et al, 2010;Joung & Do Noh, 2014;Fadel & Wiecek, 2015).…”

Packing optimization of practical systems using a dynamic acceleration methodology

“…Packing problems have been a topic of interest in literature and academia for decades. Due to their widespread applicability, it is not surprising that they have found applications in various fields such as biology [6,7], material science [8,9], engineering [10,11], and manufacturing [12,13]. Packaging problems are often attempted to be solved using non-gradient, heuristic, and stochastic-based optimization methods used to simplify the problem and relax the design space.…”