Turning is the most commonly available and least expensive machining operation, in terms of both machine-hour rates and tool insert prices. A practical CNC process planner has to maximize the utilization of turning, not only to attain precision requirements for turnable surfaces, but also to minimize the machining cost, while non-turnable features can be left for other processes such as milling. Most existing methods rely on separation of surface features and lack guarantees when analyzing complex parts with interacting features. In a previous study, we demonstrated successful implementation of a feature-free milling process planner based on configuration space methods used for spatial reasoning and AI search for planning. This paper extends the feature-free method to include turning process planning. It opens up the opportunity for seamless integration of turning actions into a mill-turn process planner that can handle arbitrarily complex shapes with or without a priori knowledge of feature semantics.
For the past three decades, computer-aided process planning (CAPP) has attracted a large amount of research interest. A huge volume of literature has been published on this subject. Today, CAPP research faces new challenges owing to the dynamic markets and business globalisation. Thus, there is an urgent need to ascertain the current status and identify future trends of CAPP. Covering articles published on the subjects of CAPP in the past 10 years or so, this article aims to provide an up-to-date review of the CAPP research works, a critical analysis of journals that publish CAPP research works, and an understanding of the future direction in the field. First, general information is provided on CAPP. The past reviews are summarised. Discussions about the recent CAPP research are presented in a number of categories, i.e. feature-based technologies, knowledge-based systems, artificial neural networks, genetic algorithms, fuzzy set theory and fuzzy logic, Petri nets, agent-based technology, Internet-based technology, STEP-compliant CAPP and other emerging technologies. Research on some specific aspects of CAPP is also provided. Discussions and analysis of the methods are then presented based on the data gathered from the Elsevier's Scopus abstract and citation database. The concepts of 'Subject Strength' of a journal and 'technology impact factor' are introduced and used for discussions based on the publication data. The former is used to gauge the level of focus of a journal on a particular research subject domain, whereas the latter is used to assess the level of impact of a particular technology, in terms of citation counts. Finally, a discussion on the future development is presented. 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. Summary The present survey is intended to give a comprehensive picture of the actual knowledge 1n the field of computer-aided process planning systems. In a first part, a methodic analysis of the process planning function 1s carried out on the basis of a typical example. Possible areas of computer utilization are identified and problems in computer Introduction are analyzed. In a second part, a systematic review of typical existing systems is performed with an effort to classify systems according to their basic characteristics. Some examples of interesting outputs obtained with the help of computer-aided process planning are reviewed in more details. Abstract Modern manufacturing is characterized by low volume, high variety production and close tolerance high quality products. Computer Integrated Manufacturing (CIM) is recognized as an effective platform for increasing manufacturing competitiveness. Computer Aided Process Planning is an essential key for achieving CIM. The integration of design, computer aided process planning (CAPP) and production planning and control (PPC) is becoming essential especially in a concurrent engineering environment where many product life cycle factors are of concern. An overview of the major development thrust in CAPP is presented along with some of the evolving trends and challenges such as rapid, generic, dynamic and or distributed process planning. Related issued of quality and evolving standards are also discussed. Methods for automated process planning and NC programming are surveyed and classified into generic categories. Aspects of CAPP investigated include part definition methods, reasoning and search techniques used to generate process plans, both Al-based and traditional, and process planning languages. NC programming techniques have been categorised into those based on cell decomposition, volume delta volume decomposition, sectioning and geometric reasoning. Methods for simulation and verification of NC programs are also surveyed. The current state of the technology and the advantages and shortcomings of each of the CAPP and NC programming generic methods are also discussed. Automated feature recognition (AFR) has provided the greatest contribution to fully automated CAPP system development. The objective of this paper is to review various approaches for solving three major AFR problems: (i) extraction of geometric primitives from a CAD model; (ii) defining a suitable part representation for form feature identification; and (iii) feature pattern matching recognition. A novel, detailed classification of developed AFR systems has been introduced. This paper also provides a thorough investigation of methods for geometric feature extraction, emphasizing STEP standard application and, finally, a review of recent research reports in the field of AFR with rule-based feature pattern recognition. We discuss potentials and limitations of these approaches and emphasize directions for further research work.