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Title: A survey on smart automated computer-aided process planning (ACAPP) techniques
Authors: Al-wswasi, M
Ivanov, A
Makatsoris, H
Keywords: automatic CAPP;smart manufacturing;automatic feature recognition;process selection
Issue Date: 13-Apr-2018
Publisher: Springer
Citation: International Journal of Advanced Manufacturing Technology, 2018, 97 (1-4), pp. 809 - 832
Abstract: © 2018, The Author(s). The concept of smart manufacturing has become an important issue in the manufacturing industry since the start of the twenty-first century in terms of time and production cost. In addition to high production quality, a quick response could determine the success or failure of many companies and factories. One the most effective concepts for achieving a smart manufacturing industry is the use of computer-aided process planning (CAPP) techniques. Computer-aided process planning refers to key technology that connects the computer-aided design (CAD) and the computer-aided manufacturing (CAM) processes. Researchers have used many approaches as an interface between CAD and CAPP systems. In this field of research, a lot of effort has been spent to take CAPP systems to the next level in the form of automatic computer-aided process planning (ACAPP). This is to provide complete information about the product, in a way that is automated, fast, and accurate. Moreover, automatic feature recognition (AFR) techniques are considered one of the most important tasks to create an ACAPP system. This article presents a comprehensive survey about two main aspects: the degree of automation in each required input and expected output of computer-aided process planning systems as well as the benefits and the limitations of the different automatic feature recognition techniques. The aim is to demonstrate the missing aspects in smart ACAPP generation, the limitations of current systems in recognising new features, and justifying the process of selection.
ISSN: 0268-3768
Appears in Collections:Dept of Mechanical Aerospace and Civil Engineering Research Papers

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