Recent Advances and Future Challenges in Automated Manufacturing Planning

被引:7
|
作者
Bourne, David [3 ]
Corney, Jonathan [4 ]
Gupta, Satyandra K. [1 ,2 ]
机构
[1] Univ Maryland, Dept Mech Engn, College Pk, MD 20742 USA
[2] Univ Maryland, Syst Res Inst, College Pk, MD 20742 USA
[3] Carnegie Mellon Univ, Inst Robot, Pittsburgh, PA 15213 USA
[4] Univ Strathclyde, Dept Design Manufacture & Engn Management, Glasgow G1 1XJ, Lanark, Scotland
关键词
UNDERCUT FEATURE RECOGNITION; PARTING DIRECTIONS; MOLD DESIGN; GEOMETRIC ALGORITHMS; GENERATION; DIE; INTELLIGENT; SYSTEM; 3D; ACCESSIBILITY;
D O I
10.1115/1.3593411
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The effective planning of a product's manufacture is critical to both its cost and delivery time. Recognition of this importance has motivated over 30 years of research into automated planning systems and generated a large literature covering many different manufacturing technologies. But complete automation has proved difficult in most manufacturing domains. However, as manufacturing hardware has evolved to become more automated and computer aided design software has been developed to support the creation of complex geometries; planning the physical fabrication of a virtual model is still a task that occupies thousands of engineers around the world, every day. We intend for this paper to be useful to newcomers in this field, who are interested in placing the current state-of-the-art in context and identifying open research problems across a range of manufacturing processes. This paper discusses the capabilities, limitations and challenges of automated planning for four manufacturing technologies: machining, sheet metal bending, injection molding, and mechanical assembly. Rather than presenting an exhaustive survey of research in these areas, we focus on identifying the characteristics of the planning task in different domains, current research directions, and open problems in each area. Our key observations are as following. First, the incorporation of AI techniques, geometric modeling, computational geometry, optimization, and physics-based modeling has led to significant advances in the automated planning area. Second, commercial tools are available to aid the manufacturing planning process in most manufacturing domains. Third, manufacturing planning is computationally challenging and still requires significant human input in most manufacturing domains. Fourth, advancement in several emerging areas has the potential to create, in the near future, a step-change in the capabilities of automated planning systems. Finally, we believe that deploying fully automated planning systems can lead to significant productivity benefits. [DOI: 10.1115/1.3593411]
引用
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页数:10
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