Feature extraction and feature based design approaches in the development of design interface for process planning

The quest for completely automated process planning systems has exposed the lack of techniques capable of automatically understanding the stored CAD models in a manner suitable for process planning. Most current generations of process planning systems have used the ability of humans to translate the part drawing requirements into a form suitable for computer aided process planing. Recently, research advances have been made to improve the understanding of computer stored 3-D part models. The two approaches used are feature recognition and feature based design. This paper presents a state of the art review of feature recognition techniques developed and presents feature based design as an alternative. Process planning systems developed using both approaches are presented.     

Design and manufacturing of sheet-metal parts: Using features to aid process planning and resolve manufacturability problems

This paper describes an integrated system for the design and production of sheet-metal parts. We have identified some important features for the sheet-metal bending process. These features are automatically generated as the design progresses. After the designs are complete, our automatic process planning system uses the features and generates new ones to aid the production of plans with near-minimum manufacturing costs. Finally, these plans are used to produce parts on an automatic bending system.Once a plan is generated, it can be used to manufacture the part, and to provide feedback to design and other factory systems. The application of features and the potential feature interaction problems are discussed. Several key manufacturing problems are also considered and the result of planning is used to resolve these problems. By solving these feature interaction problems and often practical manufacturing issues, we are able to plan and manufacture the majority of the parts we have tested less than one hour after the flat patterns are prepared.     

A repository for design, process planning and assembly

This paper provides an introduction to the Design, Planning and Assembly Repository available through the National Institute of Standards and Technology (NIST). The goal of the Repository is to provide a publically accessible collection of 2D and 3D CAD and solid models from industry problems. In this way, research and development efforts can obtain and share examples, focus on benchmarks, and identify areas of research need. The Repository is available through the World Wide Web at URL http://www.parts.nist.gov/parts.     

Data and knowledge modeling for design–process planning integration of sheet metal components

Realizing design–process planning integration is vital to the competitiveness of manufacturing organization and its ability to respond rapidly to market changes. Many attempts have been made in the past proposing the integration of the two activities based on product data models. However, both design and process planning activities are knowledge intensive. An effective integration is possible only if both data and knowledge models form a basis for integration. This paper presents key issues related to data and knowledge modeling for integration of design (CAD) and process planning (CAPP) activities for sheet metal components. Previous attempts to model data and knowledge have concentrated only on either design or process planning and not from an integration point of view. Moreover, in these attempts data and knowledge models have been proposed without attempting to relate the two. The same has been overcome in the present work. An integration framework based on data and knowledge is proposed at the end and discussed for domain of design–process planning integration of sheet metal components.     

Integrated process planning using tool/process capabilities and heuristic search

CAD–CAM integration has involved either design with standard manufacturing features (feature-based design), or interpretation of a solid model based on a set of predetermined feature patterns (automatic feature recognition). Thus existing approaches are limited in application to predefined features, and also disregard the dynamic nature of the process and tool availability in the manufacturing shop floor. To overcome this problem, we develop a process oriented approach to design interpretation, and model the shape producing capabilities of the tools into tool classes. We then interpret the part by matching regions of it with the tool classes directly. In addition, there could be more than one way in which a part can be interpreted, and to obtain an optimal plan, it is necessary for an integrated computer aided process planning system to examine these alternatives. We develop a systematic search algorithm to generate the different interpretations, and a heuristic approach to sequence operations (set-ups/tools) for the features of the interpretations generated. The heuristic operation sequencing algorithm considers features and their manufacturing constraints (precedences) simultaneously, to optimally allocate set-ups and tools for the various features. The modules within the design interpretation and process planner are linked through an abstracted qualitative model of feature interactions. Such an abstract representation is convenient for geometric reasoning tasks associated with planning and design interpretation.     

Integration of product design,process planning,scheduling, and FMS control using XML data representation

An efficient model for communications between CAD, CAPP, and CAM applications in distributed manufacturing planning environment has been seen as key ingredient for CIM. Integration of design model with process and scheduling information in real-time is necessary in order to increase product quality, reduce the cost, and shorten the product manufacturing cycle. This paper describes an approach to integrate key product realization activities using neutral data representation. The representation is based on established standards for product data exchange and serves as a prototype implementation of these standards. The product and process models are based on object-oriented representation of geometry, features, and resulting manufacturing processes. Relationships between objects are explicitly represented in the model (for example, feature precedence relations, process sequences, etc.). The product model is developed using XML-based representation for product data required for process planning and the process model also uses XML representation of data required for scheduling and FMS control. The procedures for writing and parsing XML representations have been developed in object-oriented approach, in such a way that each object from object-oriented model is responsible for storing its own data into XML format. Similar approach is adopted for reading and parsing of the XML model. Parsing is performed by a stack of XML handlers, each corresponding to a particular object in XML hierarchical model. This approach allows for very flexible representation, in such a way that only a portion of the model (for example, only feature data, or only the part of process plan for a single machine) may be stored and successfully parsed into another application. This is very useful approach for direct distributed applications, in which data are passed in the form of XML streams to allow real-time on-line communication. The feasibility of the proposed model is verified in a couple of scenarios for distributed manufacturing planning that involves feature mapping from CAD file, process selection for several part designs integrated with scheduling and simulation of the FMS model using alternative routings.     

产品设计规划问题建模及遗传算法求解

针对目前产品设计过程规划研究中存在的不足,在充分考虑实际设计过程中存在的各种不确定因素的基础上,以产品开发过程中的全体任务为规划对象,以设计迭代时间和成本为目标,将设计过程规划问题描述为基于仿真的随机优化问题进行处理。提出一种模型求解的混合遗传算法,该算法引入最优计算量分配技术进行样本分配,极大地提高了算法的搜索效率,有效地改善了遗传算法搜索的可靠性。以汽轮机轴承转子系统的设计为例,对提出的方法的有效性进行了验证,仿真结果表明,该建模方法有效且算法求解效率高。该方法可推广应用于各种产品设计过程的规划,具有普遍意义。     

Preliminary design and manufacturing planning integration using web-based intelligent agents

Software agents have been increasingly used in the product and process development in industry over the past years due to the rapid evolvement of the Internet technology. This paper describes agents for the integration of conceptual design and process planning. Agents provide mechanisms to interact with each other. This mechanism is important since both of those processes involve negotiations for optimization. A set of design and planning software agents has been developed. These agents are used in a computer-based collaborative environment, called a multi-agent platform. The main purpose of developing such a platform is to support product preliminary design, optimize product form and structure, and reduce the manufacturing cost in the early design stage. The agents on the platform have access to a knowledge base that contains design and planning rules. These rules are derived from an analysis of design factors that influence process and resource planning, such as product material, form, shape complexity, features, dimension, tolerance, surface condition, production volume, and production rate. These rules are used by process planning agents to provide process planners with information regarding selecting preliminary manufacturing processes, determining manufacturing resources, and constructing feedback information to product designers. Additionally, the agents communicate with WEB servers, and they are accessible by users through Internet browsers. During performing design and planning tasks, agents access the data pertinent to design and manufacturing processes by the programming interfaces of existing computer-aided design (CAD) and manufacturing system. The agents are supported by a developed prototype agent platform. The agents and the platform enable the information exchange among agents, based on a previously developed integrated design and manufacturing process object model.     

Prospects for process selection using artificial intelligence

On problem facing modern industry is the lack of a skilled labor force to produce machined parts as has been done in the past. In the near future, this problem may become acute for a number of manufacturing tasks. One such task is process planning. Since process planning requires intelligent reasoning and considerable experiential knowledge, almost all existing computer aided process planning systems require a significant amount of supervision by an experienced human being.There is some prospect that “expert computer system” techniques from the field of Artificial Intelligence may be successfully used to automate (at least partially) several of the reasoning activities involved with process planning. This paper discusses some current prospects for automating a process planning task known as process selection. These ideas are currently being considered for use int he Automated Manufacturing Research Facility project at the U.S. National Bureau of Standards, and steps are being taken to implement them in an expert computer system.     

A framework for extending computer aided process planning to include business activities and computer aided design and manufacturing (CAD/CAM) data retrieval

Computer aided process planning (CAPP) systems have had limited success in integrating business functions and product manufacturing due to the inaccessibility and incompatibility of information residing in proprietary software. While large companies have developed or purchased complex order management and engineering applications, smaller manufacturers continue to use semi-automated and manual methods for managing information throughout the lifecycle of each new product and component. There is a need for reconfigurable and reprogrammable systems that combine advances in computer aided design (CAD/Computer Aided Manufacturing (CAM) technology and intelligent machining with product data management for documentation and cost control. The goal of this research is to demonstrate an architecture in which customer service, CAPP and a costing methodology known as activity based costing (ABC) are incorporated into a single system, thereby allowing companies to monitor and study how expenditures are incurred and which resources are being used by each job. The material presented in this paper is the result of a two year university and industry sponsored research project in which professors and students at the Costa Rica Institute of Technology developed a software application for FEMA Industrial S.A., a local machining and fabrication shop with sixty five employees and both conventional and CNC capabilities. The final results represent not only a significant contribution to local industry and to the students’ education but, also to the continuing growth of CAPP. Implementing better decision making tools and standardizing transactions in digital format would reduce the workload on critical personnel and archive valuable knowledge for analyzing company methods and expertise.     

Development of an object-oriented blackboard model for stamping process planning in progressive die design

This paper reports preliminary work to investigate the suitability of using a blackboard framework as a problem-solving model for stamping process planning in progressive die design. The model is described at two levels: knowledge level and computational level. The knowledge level describes how the stamping process planning domain is represented in a blackboard architecture. The computational level describes how the blackboard architecture is modeled and implemented using object technology. A software prototype has been developed using CLIPS and C++ interfaced with Solid Edge CAD system. An example is presented to illustrate the feasibility and practicality of the proposed approach.     

浅议信息系统建设中的网络规划与设计

科学的网络规划与设计是信息系统能够成功建设的前题和保障,本文结合工作实践,从网络规划、综合布线设计、设备选型三方面讨论了网络具体实施中应用遵守的原则和注意的事项,以保证网络先进性、实用性,可扩展性及安全性和可管理性。     

Acquiring,storing and utilizing process planning knowledge using neural networks

An approach is formulated for the automated acquisition of process selection and within-feature process sequencing knowledge from examples using neural networks. Network architecture, problem representation and performance issues are discussed.