Computer Aided Process Planning Research Articles

A generative process planning system for parts produced by rapid prototyping

This paper presents a generative process planning system for parts produced by the rapid prototyping process (i.e. fused deposition modelling–FDM). The proposed process planning involves optimal selection of orientating the model with a proper support structure and then provides an intelligent slicing methodology, such as direct or adaptive, to minimise the built up time, keeping the geometry and cusp height errors in control. Pre- and post-slicing processes have been used to minimise the sliced data error. The Computer Aided Process Planning (CAPP) model has been arranged into five modules: orientation, support structure generation, slicing, path planning and Numerical Control (NC) program generation, and model build up. The CAPP model has been implemented in C language having a unique methodology consisting of 42 simplified steps. The CAPP model has been tested for several examples and shows satisfactory results.

Development on CAD Software about Slewing Bearing

Based on the analyzing the fact of slewing bearing production, the primary need for software of the corporation is determined. On this condition, it has discussed the main designs, which include the framework of software, key categories, and design of method and so on. Some examples are given. Through using this software, we can not only reduce the workload of design of nonstandard slewing bearing which is repeating and heavy, but also avoid misplay of the designer. This software also provides the precondition for Computer-Aided Process Planning (CAPP). Through the using of the software, we can increase the rate of eligible product, reduce the cost of production and fulfill time limit for client better.

A CAPP framework with optimized process parameters for rotational components

Process planning, as a critical stage integrating the design and manufacturing phase in a manufacturing environment, has been automated to meet the needs for higher productivity and lower production cost. Being an input to various systems such as scheduling and routing, process planning results are of great importance in the manufacturing stage. Though feature extraction and sequence optimization have been given much attention, the process parameters are rarely dealt with. This paper focuses on the development of a new generative computer aided process planning (CAPP) framework for rotational components. The developed framework includes modules for feature extraction based on CAD application programming interfaces, determination of the optimum sequence and generation of optimum process parameters. The optimization of the machining operations is achieved using the evolutionary technique. The approach resulted in the reduction and prediction of machining time and cost. The framework is demonstrated with a case study.

An integrated framework for planning of recycling activities in electrical and electronic sector

In Europe 7.3 million tonnes of waste electrical and electronic equipment (WEEE) were created in 2002, and the fact that the growth rate of WEEE is 3–5% per annum, with a significant amount of this waste used to be dumped into landfills without any pre-treatment, has resulted in the introduction of a European WEEE directive. The directive requires companies who manufacture or import electrical and electronic equipment to take financial and legal responsibility for its environmental-friendly recovery and recycling. The current recycling applications of WEEE are often developed on an ad hoc basis and mainly attributable to the hidden economic value within used products. However, at present the recycling facilities are faced with the challenge to improve WEEE recycling activities to ensure that a larger proportion of components and materials are being recovered at a reasonable cost and yet at the same time legislative requirements are being met. A major assertion made in the research reported in this paper is that a systematic framework is needed to aid the decision making involved in adopting the best possible end-of-life strategies for WEEE. The paper presents one such integrated framework for the planning of the processes involved in the recycling of WEEE. Based on this framework, a computer-aided recycling process planning (CA R PP) system which generates bespoke recycling process plans for WEEE has been developed, which is also described and its functionality demonstrated using a typical WEEE product.

Integrating computer aided design and computer aided process planning

One of the most daunting challenges in Computer Integrated Manufacturing (CIM) is bridging the gap between Computer Aided Design (CAD) and Computer Aided Process Planning (CAPP). Past research into...

Modeling of process parameter selection with mathematical logic for process planning

Process planning is the systematic determination of detailed methods by which workpieces or parts can be manufactured economically and competitively from initial stages to finished stages. One of the key problems of computer-aided process planning (CAPP), however, is the complexity of process knowledge representation of process planning and the diversity of manufacturing background. Process knowledge representation and inference mechanism of process parameter selection is one of the most important issues in the research on CAPP. A proper methodology for modeling inference mechanism of process parameter selection, hence, is essential for selection of process parameters in process planning. The paper presents an atomic inference engine model of process parameter selection in process planning using mathematical logic. The methodology of modeling the inference mechanism of process parameter selection is proposed with backward chaining of mathematical logic that is a form of goal-directed reasoning. An illustrative case has been analyzed using the proposed approach to demonstrate its potential application in the real manufacturing environment, by combining with a practical application of a hole-making in a industrially relevant workpiece. The outcomes of this work provide a process reasoning mechanism for process parameter selection in process planning and thus alleviate automated process reasoning problems in process planning.

Hybrid feature recognition method for setup planning from STEP AP-203

For seamless automation, computer-aided design and manufacturing activities have to be linked by computer-aided process planning (CAPP). An important subtask in CAPP is setup planning, in which a setup plan must be generated ideally from a given 3-D model of the component. In this paper, a hybrid approach that effectively uses volume subtraction and face adjacency graph is proposed to recognize manufacturing features from 3-D model data in STEP AP-203 format. The proposed feature recognition is generic in nature and is capable of recognizing intersecting features also with relative ease. The manufacturing features are clustered based on preferential base for machining and a setup sequence is obtained by alternative rating and ranking. Finally, locating and clamping for each setup are determined considering intermediate shapes of the workpiece. This setup planning method reduces the number of alternatives for evaluation and thereby the computational effort.

Integrated Process Simulation and Die-Design in Sheet Metal Forming

During the recent 10-15 years, Computer Aided Process Planning and Die Design evolved as one of the most important engineering tools in sheet metal forming, particularly in the automotive industry. This emerging role is strongly emphasized by the rapid development of Finite Element Modelling, as well. In this paper, an integrated process simulation and die design system developed at the University of Miskolc, Department of Mechanical Engineering will be introduced. The proposed integrated solution has great practical importance to improve the global competitiveness of sheet metal forming in the very important segment of industry. The concept to be described in this paper may have specific value both for process planning and die design engineers.

Computer-aided process planning support functions

Aiming at automating the different trades intervening in mechanical parts' design activities, one finds the weakest link within the interface linking the computer-aided design (CAD) trade and the computer-aided process planning (CAPP) trade where a huge semantic gap is detected. Works generally tend to optimise the pre-process planning trade (design/CAD) and post-process planning trade (machining/computer-aided manufacturing). So as to bridge in between CAD and CAPP, we present at first support functions that helps a process planner setting a process plan for an aircraft structural part. The proposed functions will be forwarded in the same order the planner questions himself during his first analysis. Each function is justified by presenting the need behind. We end up on the benefits of having such an assistance tool as we mention the future perspectives of our works.

Computer Aided Process Planning in Aircraft Manufacturing

Aircraft structural parts make around 1% of the total aircraft components. At present, the production cycle of several components families is within the range of few hours. Conversely, the production of structural parts is mainly a human-made operation with manufacturing complexity increasing with the part's morphology. The delicate thin elements and the presence of complex surfaces – mainly ruled surfaces which acquires the external aircraft body shape – sets the production time of mechanical structural parts ranging from few hours (for basic parts) up to over 20 days (for complex parts). The main loss of time is identified in the process planning field. This paper presents at first a review of the production numerical chain, and then offers a review of existing CAPP software and their points of failures. We follow with the presentation of the USIQUICK project and the resulting CAPP software functions and prototype. We conclude the paper with a review of the main results setting the domain of our current and future research.

Using data mining in the manufacturing systems for CAD model analysis and classification

The applications of data mining in engineering and manufacturing are enormous and useful for helping in the analysis of large data and information repositories for the discovery of trends, patterns and knowledge. In industrial engineering and manufacturing systems, the data may contain valuable information, or example, in downstream CAM applications such as Computer Aided Process Planning (CAPP). In this paper, we present a new approach for mining large quantities of machining features, Computer-Aided Design (CAD) models and manufacturing data. The approach is based on data mining and uses learning-logic classification techniques for mining 3D CAD data. The proposed approach was evaluated in CAD model analysis, specifically in classification tasks. The experimental results proved that the method is effective in terms of classification accuracy and can be used as an efficient data mining tool for CAD model analysis and classification.

Study on Computer-Aided Process Planning of Mold Part Machining

Large molds with very deep shape are used in producing bumpers and inner panels of automobiles. In order to realize the precise and stable machining of such deep molds, 3-axis milling with inclined cutters is often applied. 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. We propose a new algorithm for automatically subdividing the machining region. A machining region is represented as a set of cubic blocks in our study. For each block, all accessible directions of a cutter are computed. Neighboring blocks with similar cutter accessible directions are then combined, and some groups of blocks with similar cutter accessible directions are obtained. Proposed algorithm is implemented and an experimental process planning assistance program using this technology is demonstrated.

STEP-compliant process planning system for compound sheet metal machining

Compound punch-cutting machines are referred as machines that perform both punching and laser-cutting operations. Such machines can greatly increase the efficiency and flexibility of sheet metal manufacturing. Though there are computer-aided design (CAD) systems developed to take care of product design, and computer-aided process planning (CAPP) systems to generate optimal tool paths and plans and computer-aided manufacturing (CAM) systems for various manufacturing requirements, according to our literature search, there is no platform or system dedicated to compound sheet metal machining, which lead to problems such as low efficiency and high cost due to lack of optimal scheduling methods for the compound machining methods. This research attempts to develop a prototype STEP-compliant process planning system for supporting the compound punch-cutting machines. The system has interfaces to input CAD product data and output machine control codes. It integrates software modules for nesting optimization, cutting/punch path optimization and planning, simulation, and machining parameters set up. The focus of the paper is placed on investigating the problems and solutions of compound machining, the structure of the STEP-compliant system, and the definition of STEP-compliant product data models and interfaces for creating a STEP-compliant programming environment, where the above mentioned software modules are integrated.

A new software platform to support feature-based process planning for interoperable STEP-NC manufacture

Computer numerical control (CNC) manufacturing has evolved with the use of faster, more precise and more capable CNC controllers and machine tools. The enhancements in machine tools however have not been integrated under a common platform to support computer aided design (CAD)/computer aided manufacturing (CAM)/CNC software interoperability and as a result a plethora of standards are being used for these systems. ISO 10303 (STEP) and ISO 14649 (STEP-NC) seek to eliminate the barriers in the exchange of information in the CNC manufacturing chain and enable interoperability throughout the manufacturing software domain. With the progress on standardization and implementation, computer systems in the manufacturing process chain require evolution to support the STEP-compliant planning and manufacture. The current paper introduces a novel software platform entitled the Integrated Platform for Process Planning and Control (IP3AC) to support STEP-NC compliant process planning (computer aided process planning (CAPP)/CAM). A prototype process planning system (PPS) based on the platform is then presented as a sample application in the light of future interoperable planning and manufacture. The PPS has been developed with the application of a two-stage strategy for STEP-NC part program generation, namely general workplan generation and specific workplan generation. The work is verified through the use of case study components.

A decision logic schema of process planning using backward chaining reasoning

Decision logic of process planning is one of the most difficult issues in the research on computer-aided process planning (CAPP), and also a bottleneck hampering the process of pragmatization and commercialization of CAPP. A proper methodology for decision logic of process planning is essential for describing or specifying the various decisions associated with combinations of conditions in process planning. This paper presents a decision logic schema of process planning using backward chaining reasoning in mathematical logic to address process reasoning formalization in automated process planning, which is based on a meta-modeling paradigm of the manufacturing resources [19]. The meta-modeling paradigm combines mapping theory with the first- & second-order logic in mathematical logic to address modeling the manufacturing resources and to provide a methodology for the extraction of specific process knowledge. The meta-modeling paradigm lays the foundation for the proposed decision logic schema with specific process knowledge while the decision logic schema is the extension and application of the results from the meta-modeling paradigm. The decision logic schema provides a systematic methodology for the decision-making process and inference mechanism in process planning from the global viewpoint, which can be applied to eliminate the variability from the planners’ judgement and experience. Finally, an application example is used to illustrate the decision logic schema.

A clustering-based modeling scheme of the manufacturing resources for process planning

Process planning determines how a product is to be manufactured and, therefore, is one of the key elements in the manufacturing process. The basic crux of computer-aided process planning (CAPP), however, is the diversity of manufacturing background and the complexity of process planning. Since the process plans are generated on demand with the manufacturing resources on a shop floor, modeling method of the manufacturing resources is one of most important issues in computer-aided process planning. Hence, the major objective of this research is to create a clustering-based modeling scheme of the manufacturing resources for process planning. This modeling scheme combines clustering method with averaging method so as to reasonably partition and classify the manufacturing resources on a shop floor. The proposed approach provides one of search strategies of machine tools for process planning, especially for the selection of machine tools. Finally, an illustrative example is applied to describe the clustering-based modeling scheme.

Generation of machine configurations based on product features

A computer-aided process planning (CAPP) and machine assignment system, capable of coping with the changes in products and system, are required for reconfigurable manufacturing systems (RMS) or other dynamic manufacturing environments. The capabilities of the machines and manufacturing systems in RMS change with each configuration. An approach is presented for selecting the different types of machine(s) and their appropriate configurations to produce different types of parts and features, according to the required machine capabilities. The structure of the machine tool is represented in a kinematic chain-like format that captures the number, type and order of different axes of motion on both the tool or workpiece side for the machine. The proposed method is illustrated with an example. More than one minimum machine configuration may be generated for a single-operation cluster, which increases the flexibility in machine tool selection. The developed approach is general in nature and not limited to RMS. It is applicable to any manufacturing system where dynamic and flexible process planning and machine assignments are required. It could serve as an important tool in aiding the machine assignment/selection and process planning activities at the initial stages of manufacturing systems design and subsequent changes in products scope, and facilities expansion, downsizing and modification.

CAD/CAPP Integration using Feature Ontology

In a collaborative computer-supported engineering environment, the interoperation of various applications will need a representation that goes beyond the current geometry-based representation, which is inadequate for capturing semantic information. The primary purpose of this study is to discuss a semantically based information exchange protocol that will facilitate seamless interoperability among current and next generation computer-aided design systems (CAD) and between CAD and other systems that use product data. An ontological approach is described to integrating computer-aided design (CAD) and computer-aided process planning (CAPP). Two commercial software applications are used to demonstrate the approach. This involves the development of a shared ontology and domain specific ontologies in the Knowledge Interchange Format (KIF) language. Domain specific ontologies — which are feature-based — are developed after a detailed analysis of the CAD and the CAPP software. Mapping between the domain ontologies and the shared ontology is achieved by several mapping rules. The approach is validated by using a variety of parts.

The integration of manufacturing systems using visualised CAPP for agile manufacturing

Agile manufacturing embedded in an integrated manufacturing system can drive the business for quick response to the market changes. Computer-Aided Process Planning (CAPP) has been an effective tool of integrated manufacturing systems. Existing CAPP systems were proposed generally based on traditional manufacturing systems, which cannot meet the requirement of customised production in dynamic manufacturing environments. This paper presents a visualised CAPP system to improve users' interactive ability in process planning to enhance the integration of manufacturing systems. The system is implemented using VRML, Java language and Database (DB). Structured Query Language (SQL) management module is developed to manage the customised DB. It is an enhanced CAPP system in an integrated manufacturing system for agile manufacturing. Based on the developed approach in this research, an efficient and dynamic process plan can be generated.

Knowledge Management in Process Planning

Considerable research and development efforts have been devoted to Computer Aided Process Planning (CAPP). Nevertheless, because the CAPP problem is complex and is characterized by many interdependent technical and business parameters and variables, no viable off-the-shelf solution is yet available that can be easily or widely implemented in industry. This paper presents an overview of the CAPP field and describes a holistic component manufacturing process planning model based on an integrated approach combining technological and business considerations. The model was derived based on available literature, an overview of the state-of-the-art in Digital Manufacturing, Product Lifecycle Management (PLM) and CAPP solution providers, and a survey of Small Medium Enterprise (SME) manufacturers. This model will form the basis for developing improved decision support and knowledge management capabilities to enhance available CAPP solutions.