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Strathprints serves world leading Open Access research by the University of Strathclyde, including research by the Strathclyde Institute of Pharmacy and Biomedical Sciences (SIPBS), where research centres such as the Industrial Biotechnology Innovation Centre (IBioIC), the Cancer Research UK Formulation Unit, SeaBioTech and the Centre for Biophotonics are based.

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Recent advances and future challenges in automated manufacturing planning

Bourne, David and Corney, Jonathan and Gupta, Satyandra K. (2011) Recent advances and future challenges in automated manufacturing planning. Journal of Computing and Information Science in Engineering, 11 (2). -. ISSN 1530-9827

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Abstract

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]