Computer Aided Process Planning Research Articles

The Weight Distribution and Configurability of Process Collaboration

Based on the process reuse, a great number of process chains in a computer aided process planning (CAPP) system can form into a large process network as a collection of process collaborations with a large weight and processes with a larger strength. This paper aims to study the topological structure, weighted connectivity and assortativity, and configurability analysis of a realistic turbine process network. The empirical analysis indicates that the nonequilibrium weight distribution reveals a decaying power-law behavior, whereas the weight assignment of process collaborations behaves randomly, and has an assortative relationship with degrees of quite a few processes. In this paper, an evaluation method of configurability of process couples is proposed based on assortativity, and then the process configurability can be classified into the strong and weak ones.

Study on CAPP System Based on Rough Set Theory

As a significant technology of Computer Integrated Manufacturing System (CIMS), Computer Aided Process Planning (CAPP) is the bridge between Computer Aided Design (CAD) and Computer Aided Manufacturing (CAM). Meanwhile, it is a momentous foundation for building the overall information model of manufacturing of engineering product. By using of which along with the theory of rough set in rule reduction of expert system, the development of CAPP system framework is basis of .net platform, utilizing Visual Studio 2003 to design the system interface and associated structured query language (SQL) allow distributed data processing and data access, which is supported by SQL Server 2000. By designing and running the program, the method of designing is verified.

A Modified Genetic Algorithm(GA) for Optimization of Process Planning

Computer-aided process planning (CAPP) is an important and complex in the computer integrated manufacturing system(CIMS). The expression methods of process knowledge based on manufacturing feature is established based on the analysis of characteristic of process knowledge. According to the constraints mong process knowledge, decision space of process planning based on process constraints is constructed which improved search efficiency of GA. In allusion to the uncertainty of decision of process planning, the multi-objective optimization function is established, and a GA is applied to optimization of process planning. Process planning is optimized using the reasonable coding strategy, fitness function, selection, crossover and mutation algorithm, etc. An case is offered to illustrate the process of optimization of process planing based on GA.

Computer-aided process planning – A critical review of recent developments and future trends

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.

Machining processes time calculating tool integrated in computer aided process planning (CAPP) for small and medium enterprises (SMEs)

The goal of process planning is to propose route sheets for previously designed parts. Process planning provides detailed information about a sequence of operations and parameters (cutting speed, feed rate, etc.). The objective of this work is to present computer-aided software to calculate cutting time and unproductive time when machine operations are designed and its integration in computer-aided process planning (CAPP). Results obtained from this tool application are compared with those results obtained from CAM software and with real times from the machine operation. The aim of the designed system is to be useful for small and medium enterprises (SME) working on machining processes. These kinds of enterprises cannot acquire and maintain standard CAPP systems, which are usually very expensive and difficult to work on. In order to validate the results several parts will be planned and machined and results are compared in order to adjust the designed tool software.

A Cooperative Simulated Annealing Algorithm for the Optimization of Process Planning

Process planning is an essential component of computer aided process planning (CAPP), which involves operations selection from design features and operations sequencing of these selected operations. It makes process planning a complex combinatorial optimization problem to conduct of these two steps simultaneously. In this paper, we propose a cooperative simulated annealing (CoSA) approach for the process planning problem to minimize total manufacturing cost. The proposed CoSA algorithm employed a novel optimization strategy different from all the existing approaches in the literature. Simulated annealing was utilized to optimize the four components of a process plan individually and sequentially. The approach is tested on two parts from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed algorithm.

S141022 多面加工および複数設備による加工を考慮した柔軟な加工工程設計支援の一手法([S14102]生産システムの新展開(基礎・理論) (2))

In low-volume high-mix manufacturing or agile manufacturing, the situation changes dynamically. Computer support technology, which is indispensable to modem manufacturing, should consider variable situations. From this point of view, flexible computer-aided process planning (CAPP) methods have been proposed for rough milling using one machine tool, and their feasibilities and effectiveness have been shown. Considering the above types of manufacturing, it is not reasonable to introduce special equipments but generic equipments. Therefore, those methods should be enhanced considering utilization of multiple kinds of machine tools. Such machining also relates closely to manufacturing scheduling problem, since a machine tool can not simultaneously machine multiple materials. This paper proposes a way of this enhancement.

适于汽车钣金零件生产的APQP信息管理系统研究<br>APQP Information Management System for Production of Sheet Metal Parts in Automobile

介绍了基于Ruby On Rails 框架开发的钣金零件产品质量先期策划(APQP)信息管理系统，着重研究了系统的基本结构、主要功能及开发中所需要的关键技术。该系统通过与企业计算机辅助工艺设计(CAPP)系统实施信息集成，提高了企业工艺信息管理水平，促进了企业信息一体化建设。 This paper introduces an information management system of Advanced Product Quality Planning (APQP) for sheet metal parts, developed by using Ruby On Rails development framework. Basic structure, main functions of the system and key technology in the development process are presented. The integration between APQP and Computer Aided Process Planning system (CAPP) has realized, that can greatly improve the level of process information management and promote the construction of information integration in the company.

Optimization of operation sequencing in CAPP using simulated annealing technique (SAT)

Computer-aided process planning (CAPP) is an important interface between computer-aided design (CAD) and computer-aided manufacturing (CAM) in computer-integrated manufacturing environment. A problem in traditional CAPP system is that the multiple planning tasks are treated in a linear approach. This leads to an over constrained overall solution space and the final solution is normally far from optimal or even non-feasible. The operation-sequencing problem in process planning is considered to produce a part with the objective of minimizing the sum of machine, setup and tool change costs. In general, the problem has combinatorial characteristics and complex precedence relations, which makes the problem more difficult to solve. In this paper, the feasible sequences of operations are generated based on the precedence cost matrix and reward–penalty matrix using simulated annealing technique (SAT), a meta-heuristic. A number of benchmark case studies are carried out to demonstrate the feasibility and robustness of the proposed algorithm. This algorithm performs well on all the test problems, exceeding or matching the solution quality of the results reported in the literature for most problems. The main contribution of this work focuses on reducing the optimal cost with a lesser computational time along with generation of more alternate optimal feasible sequences. The proposed SAT integrates robustness, convergence and trapping out of local minima.

Generation of Optimal Process Plan Alternatives for Manufacturing Mechanical Components

The focus of this paper is on computer-aided process planning (CAPP) for parts manufacture in systems of definite processing capabilities, involving multi-axis machining centers. A methodical approach is developed to optimally solve for process planning problems, which consists in the identification of process alternatives and sequencing working steps. The approach involves the use of the branch and bound (B&B) concept from the field of artificial intelligence (AI). A conceptual scheme for generation of alternative process plans in the form of a network is developed, based on part design data modeling in terms of machining features. A relevant algorithm is proposed for creating such a network and searching for the optimal process plan solution from the viewpoint of its operational performance, under formulated process constraints. The use of the approach is studied numerically with regard to a real life case study and diverse machine tools with relevant tooling are considered. Generated process alternatives for complex machining with given systems are studied using models programmed in the Matlab environment.

Development of CAPP/CAM System for 5-axis Control Machining

Complicated 3-D parts can be created by using the developed multi-axis control machining centers. 3-D CAD/CAM systems for multi-axis control machining are also developed to save time and labor in preparing NC data. However, operators consume a longtime in process planning since there are few practical computer systems for process planning. It is indispensable to develop CAPP(Computer Aided Process Planning) system for 3-D machining in response to the demands. The study deals with the development of fundamental CAPP/CAM system for multi-axis control 3-D machining. The system developped in the study enables 5-axis control tool path generation in consideration of tool length, the tool posture change and the workpiece fixing direction, based on the tool entrance face concept. From experimental result of creating a micro impeller, it is confirmed that the CAPP/CAM function has the potential of effective multi-axis control machining.

Application of genetic algorithm to computer-aided process planning in preliminary and detailed planning

Computer-aided process planning (CAPP) is an important interface between computer-aided design (CAD) and computer-aided manufacturing (CAM) in the computer integrated manufacturing (CIM) environment. A good process plan of a part is built up based on two elements: (1) optimized sequence of the operations of the part; and (2) optimized selection of the machine, cutting tool and tool access direction (TAD) for each operation. On the other hand, two levels of planning in the process planning is suggested: (1) preliminary and (2) secondary and detailed planning. In this paper for the preliminary stage, the feasible sequences of operations are generated based on the analysis of constraints and using a genetic algorithm (GA). Then in the detailed planning stage, using a genetic algorithm again which prunes the initial feasible sequences, the optimized operations sequence and the optimized selection of the machine, cutting tool, and TAD for each operation are obtained. By applying the proposed GA in two levels of planning, the CAPP system can generate optimal or near-optimal process plans based on a selected criterion. A number of case studies are carried out to demonstrate the feasibility and robustness of the proposed algorithm. This algorithm performs well on all the test problems, exceeding or matching the solution quality of the results reported in the literature for most problems. The main contribution of this work is to emerge the preliminary and detailed planning, implementation of compulsive and additive constraints, optimization sequence of the operations of the part, and optimization selection of machine, cutting tool and TAD for each operation using the proposed GA, simultaneously.

Digital manufacturing: History, perspectives, and outlook

Digital manufacturing has been considered, over the last decade, as a highly promising set of technologies for reducing product development times and cost as well as for addressing the need for customization, increased product quality, and faster response to the market. This paper describes the evolution of information technology systems in manufacturing, outlining their characteristics and the challenges to be addressed in the future. Together with the digital manufacturing and factory concepts, the technologies considered in this paper include computer-aided design, engineering, process planning and manufacturing, product data and life-cycle management, simulation and virtual reality, automation, process control, shopfloor scheduling, decision support, decision making, manufacturing resource planning, enterprise resource planning, logistics, supply chain management, and e-commerce systems. These technologies are discussed in the context of the digital factory and manufacturing concepts.

Analysis of Computer Aided Process Planning Techniques

Computer Aided Process Planning ( CAPP) has been recognized as playing a key role in Computer Integrated Manufacturing ( CIM ). It was used as a bridge to link CAD with CAM systems, in order to give the possibility of full integration in agreement with computer engineering to introduce CIM. The benefits of CAPP in the real industrial environment are still to be achieved. Due to different manufacturing applications, many different CAPP systems have been developed. The development of CAPP techniques needs to a summarized classification and a descriptive analysis. This paper presents the most important and famous techniques for the available CAPP systems, which are based on the variant, generative or semi-generative methods, and a descriptive analysis of their application possibilities.

Automated setup and fixture planning system for box-shaped parts

The topic of the research is related to the domain of computer-aided manufacturing process planning. This paper deals with the problem of setup and fixture planning for the machining of box-shaped parts on the horizontal machining centres. The setup and fixture planning involves the definition of setups, the setup sequence and conceptual design of fixtures for each setup. The central topic of this research is the automation of the conceptual design of fixtures. This topic is interconnected with the setup planning, and accordingly, the aim of the author has been the integrated handling of tasks of setup and fixture planning and the finding of solution in an integrated system. Based on the workpiece model, the developed system automatically determines the setup sequence, the content of setups and the conceptual solution of fixture for each setup. The paper presents the problems of fixture solutions and the partial tasks of workpiece holding, the typical solution of partial tasks and the conditions of their application and finally offers a new method, which makes the integrated handling of tasks of setup and fixture planning and finding solution in an integrated system possible.

The complexity analysis of a machining error propagation network and its application

There are some complicated interactions among different stages in multistage machining processes (MMPs), so it is important and necessary to explore the inherent mechanism of machining error propagation for improving product quality. With respect to this issue, a machining error propagation network (MEPN) of MMPs is proposed and its complexity is discussed. In order to establish this MEPN, the machining form feature (MFF) of the workpiece, machine tool, fixture, and cutting tool (i.e. machining element, ME) are defined as different network nodes. The associated relationship among different nodes is mapped by graph theory, according to the computer aided process planning (CAPP) information of the workpiece. Based on this, complex networks theory is introduced to analyse the characteristics of the established MEPN, and several measuring indices of error propagation at different nodes are proposed to quantify the interactions among different nodes. The synthesized propagation index (SPI) is then established to identify the key nodes and the SPI variation curve is used to quantify these key nodes' influences on the MEPN. Finally, a box part of a missile launcher is used to illustrate the proposed methods.

Extraction of manufacturing information from design-by-feature solid model through feature recognition

Feature recognition is the key to the computer-aided design (CAD) and computer-aided manufacturing (CAM) integration to build a computer-integrated manufacturing system. There are two approaches to CAD feature recognition: platform-dependent and platform-independent. In the platform-independent approach, the part’s geometrical data are extracted from a neutral file such as DXF, IGES, or STEP. In contrast, the platform-dependent approach extracts the information of the design features directly from a design-by-feature solid model through the object-oriented model of a part. This paper explains a platform-dependent approach which is implemented to translate design features into manufacturing information. This approach begins with simplification using the suppression of fillets, and clustering non-intersecting design features is done. Then, the rule-based method is employed in order to recognize machining features. Finally, the needed manufacturing information such as tool accessing direction, dimensions, material removal regions, and geometrical and topological data is recognized. The application of the proposed system would be exhibited in generating machine path code for rapid prototyping and CNC machines and providing a database for computer-aided process planning. The proposed system was implemented on Autodesk Inventor and successfully tested for many complex 3D models.

A contemporary study into the application of neural network techniques employed to automate CAD/CAM integration for die manufacture

In recent years, collaborative research between academia and industry has intensified in finding a successful approach to take the information from a computer generated drawings of products such as casting dies, and produce optimal manufacturing process plans. Core to this process is feature recognition. Artificial neural networks have a proven track record in pattern recognition and there ability to learn seems to offer an approach to aid both feature recognition and process planning tasks. This paper presents an up-to-date critical study of the implementation of artificial neural networks (ANN) applied to feature recognition and computer aided process planning. In providing this comprehensive survey, the authors consider the factors which define the function of a neural network specifically: the net topology, the input node characteristic, the learning rules and the output node characteristics. In additions the authors have considered ANN hybrid approaches to computer aided process planning, where the specific capabilities of ANN’s have been used to enhance the employed approaches.

Process Auxiliary Decision-making Based on Rough Sets and Regulation Distance Computing

Computer aided process planning(CAPP) is an important content of computer integrated manufacturing,and intelligentizing is the orientation of development of CAPP. Process planning has characters of empirical and time-consuming to finalize,and the same technical aim always can be achieved by different process schemes,so intelligentizing of process decision making always be a difficult point of CAPP and computer integrated manufacturing (CIM). For the purpose of intelligent aided process decision making and reuse of process resource,this paper proposed a decision making method based on rough sets(RS) and regular distance computing. The main contents and methods of process planning decision making are analyzed under agile response manufacturing environment,the concept of process knowledge granule is represented,and the methods of process knowledge granule partitioning and granularity analysis are put forward. Based on the theory of RS and combined the method of process attributes importance identification,the paper brought forward a computing model for process scheme regulation distance under the same attribute conditions,and conflict resolution strategy was introduced to acquire process scheme fit for actual situation of enterprise's manufacturing resources,so as to realize process resources' conflict resolution and quick excavate and reuse of enterprises' existing process knowledge,to advance measures of process decision making and improve the rationality and capability of agile response of process planning.

Study on Computer-Aided Process Planning of Mold Part Machining

Large molds with very deep shape are used in producing plastic parts such as bumpers and inner panels of automobiles. In order to realize the precise and stable machining of the deep mold, 3-axis milling with inclined cutters is often applied in Japanese manufactures. Some machining regions are difficult to process with a cutter in a single orientation. Such regions must be subdivided into several smaller regions, so that each region can be processed with a single orientation cutter. The authors propose a new algorithm for automatically subdividing a machining region. A machining region is represented as a set of points covering the region. For each point, all accessible directions of a cutter are computed. Points are then classified into some groups based on the distribution pattern of accessible directions using our improved cluster analysis method. The classification result corresponds to the milling region subdivision.