A survey on smart automated computer-aided process planning (ACAPP) techniques

  • Mazin Al-wswasi
  • Atanas Ivanov
  • Harris Makatsoris
Open Access


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.


Automatic CAPP Smart manufacturing Automatic feature recognition Process selection 



The authors of the paper would like to sincerely thank the Republic of Iraq Ministry of Higher Education & Scientific Research and the University of Technology, Baghdad for funding the project.


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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • Mazin Al-wswasi
    • 1
  • Atanas Ivanov
    • 1
  • Harris Makatsoris
    • 2
  1. 1.Department of Mechanical, Aerospace and Civil Engineering (MACE)Brunel University LondonUxbridgeUK
  2. 2.School of Aerospace, Transport and ManufacturingCranfield UniversityBedfordUK

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