Computer Aided Process Planning System Research Articles

A Branch and Bound Algorithm Based Process-Planning System for Plastic Injection Mould Bases

This paper describes the use of artificial intelligence in the process planning of plastic injection mould bases. The computer-aided process-planning system, developed for IMOLD will extract and identify the operations required for machining. These operations are considered together with their precedence constraints and the available machines before the process plan for the mould base plate is generated. The process plan is optimised by a branch and bound based algorithm. Overall machining time has been proposed as the objective function for optimisation. The ability of this algorithm to search intelligently for a feasible optimised solution is illustrated by an industrial case study. A brief comparison with a genetic algorithm based process planning system is also made. The result of this development will allow users to optimise process plans easily for any given mould base, with options to suit dynamic changes on the manufacturing shop floor.

Object-oriented knowledge-based computer-aided process planning system for bare circuit boards manufacturing

The manufacturing industry is time, quality and information driven. In the current highly competitive international marketplace, these factors are especially crucial to the electronics industry. In this paper, an object-oriented model of a computer-aided process planning (CAPP) system for the manufacturing of bare circuit boards is proposed. Process constraints and planning knowledge are all represented and modelled by respective constraints objects. The system is then implemented for the automatic process planning of double-sided circuit boards. The performance of the system is then compared with that of experienced process planners. The advantages in the use of the constraint and knowledge objects approach in a computer-aided process planning system are revealed.

A Case-Based Computer-Aided Process-Planning System for Machining Prismatic Components

This article deals with a process-planning system that uses case-based reasoning methodology. Briefly, case-based reasoning is an intelligent problem-solving technique which works by searching through a database for previously solved problems for one or more cases whose identifying features closely resemble the current problem. The case-based reasoning system used in this article to develop a process plan, typically consists of three modules, i.e. the part input and representation module, the case retrieval, and case adoption module. In this paper, new approaches have been proposed in all three modules. By incorporating a multiparametric and absolute-matching technique, the case retrieval module especially has become more powerful. A practical approach has been suggested in this research to compute the similarity between part input and case. An illustrative example is included to demonstrate the proposed system.

A genetic algorithm based process planning system for mould base

With the growing importance of the plastic injection industry, traditional computer aided process planning (CAPP) methods that optimise plans in a linear manner have not been able to keep up with the need for flexible planning. This paper focuses on the development of a CAPP system to concurrently optimise the operation selections and sequences for mould bases. The system first identifies the machining features automatically. All possible combinations of processes (machine, machining direction and cutting tool) are then generated based on available machining resources. By considering the multi-selection tasks simultaneously, a specially designed genetic algorithm searches through the entire solution space to identify the optimal plan. This planner is expected to assist users in optimising process plans for the whole mould base.

Exact Tool Sizing for Feature Accessibility

This paper presents an algorithm for calculating the volume of a 2D-profile, accessible by a given diameter of milling cutter. The method is independent of the generation of cutter tool paths, and exploits facilities commonly found in kernel modellers. Exact results are obtained despite the simplicity of the procedure. As a proof of the concept, the algorithms have been implemented in the Heriot-Watt University feature recogniser as a pre-processor for a part programming system. The aim of these algorithms is to assist and optimise the selection of multiple tools for the machining of complex components. The methodology has applications in process planning research where it is currently common to assume that a single tool will machine each feature. Although cutter selection is a critical step in planning the manufacture of components, computer-aided process planning (CAPP) systems rarely make any attempt to analyse the tradeoffs involved. Perhaps this is because, traditionally, exact tool accessibility calculations have been viewed as a side effect of generating a cutter tool path. Consequently, accessibility calculations are not carried out explicitly but they appear implicitly in the results of a complex geometric algorithm (i.e. cutter path generation). Because this implicit checking of tool accessibility is carried out, downstream from the higher-level reasoning about set-up and sequencing, the results are generally available only after a detailed process plan has been generated.

An Integrated Design and CAPP System for Cold or Hot Forging Products

This paper deals with an automated computer-aided process planning system by which designers can determine operation sequences even if they have little experience in process planning of bulk metal products by press working. The approach to the system is based on knowledge-based rules and a process knowledge base consisting of design rules is built. Knowledge for the system is formulated from plasticity theories, empirical results and the empirical knowledge of field experts. Programs for the system have been written in AutoLISP for the AutoCAD using a personal computer. An attempt is made to link programs incorporating a number of expert design rules to form a useful package for process planing. This integrated design and computer-aided process planning (CAPP) system is composed of two main modules and nine submodules. It is designed considering several factors, such as the complexities of blank geometry, punch and die profiles, the availability of press equipment, and standard parts. Results obtained using the modules enable the designer and manufacturer of cold forging or hot forging dies to be more efficient in this field.

A Novel Methodology for Computer-Aided Process Planning

A well-constructed generative computer-aided process planning (CAPP) system is suitable for computer-integrated manufacturing systems and intelligent manufacturing systems. Most generative CAPP systems developed in the last decade employed a linear and batch approach as their underlying methodology, but because of low efficiency and quality, many such systems cannot be applied effectively to industrial enterprises. To overcome these weaknesses, a novel methodology, called prototype-based incremental process planning (PIPP), is presented for CAPP in this paper which offers a new approach for increasing the efficiency and quality of process planning, and for fully supporting concurrent engineering. Based on this methodology, an experimental CAD/CAPP concurrent design system (HFCAD/CAPP) has been built, and a case study is presented to illustrate the characteristics of this system.

Incorporated tool selection system using object technology

Tool selection is perhaps one of the most important functions in a process planning system because the selection of a tool affects the selection of machining parameters, jig and fixture selection, production rate, cost of the product, and the resulting accuracy. Therefore computer-aided tool selection (CATS) is an essential element within a computer-aided process planning (CAPP) system (C. Koulamas, Tool requirements in multi-level machining systems, International Journal of Production Research, 29 (2) (1991) 417–437.), and in turn in a Computer Integrated Manufacturing (CIM) environment. This paper proposes an object–oriented methodology for selecting the tooling parameters for parts in a CIM environment. As this system can be incorporated into both static and dynamic process planning systems, it is termed as Incorporated Tool Selection Systems (ITSS). The steps of the methodology are discussed in detail, together with an example.

Selection of optimal conditions in multi-pass face-milling using a genetic algorithm

In a Computer-Aided Process Planning (CAPP) system, one of the important steps is the selection of machining parameters which yield optimum results. In this paper, a face-milling operation has been considered. The machining parameters such as number of passes, depth of cut in each pass, speed and feed are obtained using a genetic algorithm, to yield minimum total production cost while considering technological constraints such as allowable speed and feed, dimensional accuracy, surface finish, tool wear and machine tool capabilities.

Object-oriented analysis and design of computer aided process planning systems

Computer aided process planning (CAPP) systems in the real world are usually large and complex. The creation of a correct analysis and model of a CAPP system before implementation is a crucial step in the successful generation and operation of computer-integrated systems for today's highly competitive and dynamic environment. Few reports describe a rigorous approach to the object-oriented analysis and design of such systems. This paper presents an object-oriented analysis and design strategy for CAPP systems. It then illustrates in detail how such a strategy can be carried out in a specific domain for process planning: The printed circuitboard (PCB) industry. The studyis believed to be one of the pioneer efforts in CAPP systems analysis and design using the object-oriented approach. The authors' experience justifies the use of the object-oriented approach to create a CAPP system, as the resultant model can be used almost as a direct mapping during implementation.

An integrated artificial intelligent computer-aided process planning system

This paper presents an integrated artificial intelligent (IAI) system for dynamic computer-aided process planning (CAPP). The system, IAI-CAPP, integrates fuzzy logic (FL) and artificial neural networks (ANN) to perform the dynamic recognition and adaptive-learning tasks of the workpieces and process plans. Also, it adopts the idea of important (critical) feature concept for evaluating the suitability of existing process plans for incoming product designs. In addition, the technique of expert system (ES) is utilized. The system combines variant and generative CAPP and is capable of generating plans that are suitable for workpieces that either are similar to existing workpieces or new. The proposed system described has been realized on a computer prototype program. An illustrative example is also provided.

A cooperative agent modelling approach for process planning

A well designed computer-aided process planning (CAPP) system bridges the gap between CAD and CAM. A number of systems have recently been developed relying on a standalone expert system. However, because of over-complexity, many such systems cannot be effectively applied to industrial enterprises in practice. Moreover, the modern computer integrated manufacturing system (CIM) requires the CAPP system to be extendible and flexible for practical industrial applications. It is hardly possible to develop the extensive industrial CAPP system by using only one large expert system. To overcome these weaknesses, a new cooperative agent model is presented for process planning in this paper that satisfies five major requirements: Autonomy, Flexibility, Interoperability, Modularity and Scalability. In accordance with this framework proposed, a machining cooperative process planning system (Machining CoCAPP) is specifically developed for demonstration purpose. The system modelling, agent structure design, cooperation and coordination mechanism, and case study of the Machining CoCAPP are presented.

Computer-aided process planning in virtual one-of-a-kind production

This paper reports a framework for computer-aided process planning (CAPP) in virtual One-of-a-Kind Production (OKP). The emphasis will be placed on the particular problems of developing a CAPP system in virtual OKP company. A virtual manufacturing company or a manufacturing network normally consists of geographically dispersed master company's branches, sub-contractors, joint ventures, and partners. In this paper, we will address issues raised from highly customised products, the concurrent approach of product development and production through a manufacturing network, incomplete product and production data in OKP, the need for quickly capturing marketing opportunities and early response to the customer's demands, continuous customer influence upon production, the optimal selection of partners, and partner synthesis in virtual manufacturing. The CAPP framework proposed in this paper includes a reference architecture for structuring a CAPP system in virtual OKP, a new CAPP method which is named the `incremental process planning (IPP)', and an optimal/rational cost analysis model. It also includes three data models for data modelling and structuring of the product, the process, and manufacturing plants used in virtual OKP.

A hybrid intelligent inference model for computer aided process planning

Computer aided process planning (CAPP) is generally acknowledged as a significant activity to achieve computer‐integrated manufacturing (CIM). In coping with the dynamic changes in the modern manufacturing environment, the awareness of developing intelligent CAPP systems has to be raised, in an attempt to generate more successful implementations of intelligent manufacturing systems. In this paper, the architecture of a hybrid intelligent inference model for implementing the intelligent CAPP system is developed. The detailed structure for such a model is also constructed. The establishment of the hybrid intelligent inference model will enable the CAPP system to adapt automatically to the dynamic manufacturing environment, with a view to the ultimate realization of full implementation of intelligent manufacturing systems in enterprises.

CAPP and its integration with tolerance charts for machining of aircraft components

Computer-aided process planning (CAPP), indispensable for industry automation, is credited the technical index for the aerospace industry. The objective of this research lies in developing a CAPP system to co-operate with fabrication of aircraft components, which are complicated and manifold in geometric shapes and manufacturing processes. Process charts are sheets output from a CAPP system and are typically used in the aerospace industry to assist machine operators in carrying out workshop machining tasks. Its contents include part name, part number, operation number, machining department, machining tool, machining operation, operation illustration, etc. Among these, operation illustration is the most tedious, yet important, data to make in illustrating the part machining processes. As a result, the CAPP system addressed in this paper possesses a special feature of integrating operation illustration with process database. In this paper, the development of a variant process planning system will first be addressed. The methodology for automatic generation of operation illustration, and its integration with process planning, is then discussed.

A cooperative framework for process planning

Tremendous efforts have been made to develop computer-aided process planning (CAPP) systems. However, most of the systems are based on standalone expert systems which are hard to extend and are inflexible for practical industrial applications. This paper introduces a cooperative process planning system named CoCAPP ( Cooperative Computer-Aided Process Planning) which has been developed by the authors, utilizing cooperative agent technology. The system is based on the five requirements: Autonomy, Flexibility, Interoperability, Modularity and Scalability, in order to minimize currently available system's weakness and improve applicable characteristics. The framework, the modeling of agents, and the cooperative planning mechanism are detailed. A case study of a machining CoCAPP system is also introduced to illustrate the implementation of CoCAPP concept.

Feature-based modelling and neural networks-based CAPP for integrated manufacturing

The integration of various technical activities in a manufacturing organization using computer-based systems is very effective in improving its competitiveness. ComputerAided Process Planning (CAPP) is an essential function in Computer-Integrated Manufacturing (CIM). During process planning, the design information is interpreted and appropriate manufacturing operations specified, and this activity requires a significant amount of expertise. In this paper, a methodology of integrating the design and planning aspects of manufacturing is proposed which utilizes the concepts of Feature-Based Modelling (FBM) and Artificial Neural Networks (ANNs). Important process planning activities are identified for the application of neural networks in realizing intelligent CAPP systems. An intelligent CAPP methodology is developed to suggest the appropriate manufacturing operations and their subdivisions. It is then integrated with an FBM shell, which is used to represent the design aspects of the component from a manufacturing point of view. An example is presented. The use of ANNs approach has enabled the development of a very flexible CAPP methodology that can easily be trained to handle new types of components.

A PDES/STEP-based information model for computer-aided process planning

Computer Aided Process Planning (CAPP) constitutes one of the most essential elements in Computer Integrated Manufacturing (CIM). Although many CAPP systems have been reported in literature during the last two decades, few of them are compatible enough to integrate easily with other systems in the CIM environment. One major reason is the lack of an effective method to represent the information required by CAPP, and to unify such information with the information of other systems in the CIM environment. Indeed, this problem has received relatively inadequate attention in the recent research of CAPP systems. In this paper, an information model for CAPP is developed by using the object-oriented modeling and the Product Data Exchange Step / STandard of Exchange Product data (PDES/STEP) techniques. The model consists of the part information model, the process plan information model, and the production resource information model. The EXPRESS language or the EXPRESS-G diagram is used to represent these models. Indeed, the proposed information model will greatly improve the CAPP system’s capability of effective integration with other systems in the CIM environment, and, ultimately, to facilitate the implementation of the whole CIM strategy in manufacturing enterprises.

A modular architecture for rapid development of CAPP systems for agile manufacturing

Current manufacturing planning software systems, such as computer aided process planning (CAPP) systems, are general and in a closed form. It is very difficult to modify these systems to respond to a user's dynamically changing needs. These systems are no longer suitable for agile manufacturing. This paper presents research aimed at developing a novel architecture for the rapid development of CAPP systems. The architecture supports the construction of CAPP systems from prepackaged, plug-compatible software components. Specifications of the architecture and its building blocks are defined. Several important issues in architecture implementation are discussed, and an experimental system is illustrated. Finally, an Internet-based distributed CAPP system architecture is presented as a preview of next generation CAPP system development.

Computer‐Aided Process Planning for CNC Pumped‐Concrete Placement

Computer‐aided process planning (CAPP) is a key step in the integration of computer‐aided design and computer‐aided construction. The focus of our research is on the development of a CAPP system that will enable automated placement (i.e., pouring) of pumped concrete on a structural floor using computer numerically controlled (CNC) equipment. In this paper we describe the algorithms and methodologies comprising the CAPP system, including (1) algorithms for geometric reasoning (with the CAD model of a given floor) to recognize areas to be concreted and to extract features (such as elevator shafts) that are to be avoided during concrete placement and (2) combinatorial optimization procedures for identification of an efficient sequence of floor slabs to be concreted and the generation of a corresponding area‐covering, obstacle‐avoiding path plan for the pumped‐concrete placement pipe.