Expert CAPP system for single spindle automats

We report the design and implementation of an expert system (EXTURN) for the process planning of rotationally symmetric components manufactured on single spindle automats. EXTURN essentially comprises an interactive graphical feature modeller (GFM) and process planning modules for operation extraction, sequencing, tool selection, and process plan generation. The feature modeller provides utilities for interactive component synthesis, manufacturability assessment, dimensioning and tolerancing, graphical display, etc. The CAPP module synthesizes a process plan from the part model created by GFM, using rules organized in the knowledge base. EXTURN has been implemented for both the cut-off as well as the turret type of automats and has been tested for a variety of industrial components. It was found to generate consistent process sequences acceptable to industrial shop practices.     

An intelligent process planning system for micro turn-mill parts

An attempt has been made to develop a generalised system for the generation of process plan for the manufacture of micro parts in this work. It has two components; first one deals with automatic part feature extraction from feature-based model and second one performs the execution of process planning activities in accordance with feature using knowledge-based system approach. The proposed system maps extensible markup language (XML) data for the feature based-model and produces the corresponding manufacturing activities needed for the manufacture of micro parts. The process plan modules considered in this work includes process sequence, tools and fixtures, process parameters selection and set-up plan generation. An attempt has been made to develop process parameters selection module based on experimental investigation and optimisation apart from manufacturing catalogues and user manuals. Feature extraction through XML files avoids complex feature extraction process. The application of the developed system has been verified with a case study. The present system is limited to micro turn-mill features. Incorporation of more micro features and consideration of other activities of process plan ensures a complete process planning system for micro-machining processes.     

Processing of 3D sheet metal components in STEP AP-203 format. Part II: feature reasoning system

Both feature recognition and reasoning are needed for automating manufacturing planning activities for 3D sheet metal components. The feature reasoning system proposed here generates manufacturing information (e.g. flat pattern, locations of various features, internal cuts and blank profiles, type of tools required, operation sequence, bending sequence, etc.) for the features recognized in Part I of this paper. The issues related to flat pattern developments as experienced while using commercial software have been addressed in this work. A tool selection approach that uses standard tools for single and multiple blow features in punch presses is suggested. A zigzag method for operation sequencing and a virtual bend sequencing system are included. The system has been tested with various components and the results are compatible with industrial practices.     

Application of fuzzy logic in the selection of part orientation and probe orientation sequencing for prismatic parts

With an increase in complex designs and tighter tolerances, the Coordinate Measuring Machine inspection process has become increasingly more advanced. By inspection planning, design data can be transferred to an inspection system and an entire inspection operation can be carried out with a minimum of time and with reduced uncertainty. The current need is to automate this process completely so that the inspection plan can be generated directly from the design information. Two modules of inspection planning, i.e. selection of part orientation and probe orientation sequencing, have not been dealt with properly. Also, some important factors for the selection of part orientation have been neglected and proper weights have not been given to the probe-orientation sequencing criteria. An attempt was made to overcome these limitations. Both problems have been approached as the ranking of a number of alternatives based on multiple criteria, where each criterion has unequal importance. To get the optimum probe-orientation sequence and stable part orientation, fuzzy logic was applied. Fuzzy sets were obtained and combined using a suitable methodology. To explain and validate the proposed methodology, an example part was taken. As a practical case, an engine block was considered and the results presented.     

Development of an integrated model for process planning and parameter selection for machining processes

The concept of ‘do it right the first time’ in the machining industry not only expects the best quality products but also at the best possible cost. The cost of machining depends on intelligent process planning and selection of machining parameters such as speed, feed, and depth of cut. The problem of machining parameter selection has received great attention by researchers and many techniques have been developed. A review of these techniques reveals that the selection of the machine and cutting tool is done before the process of cutting parameter selection and process sequencing, and often the selection is based on experience. The current research is an attempt to develop an integrated model (ExIMPro: Expert system based Integrated model for Machining Processes) which finds the sequence of operations with set of machines, tools, and other process parameters to minimise the cost of machining for a cylindrical part. This system consists of existing expert system Machining Parameter SELection (MPSEL) for machine and tool selection and a Microsoft Excel® and Visual Basic® based parameter selection model. The present model focuses on turning and cylindrical grinding operations but other processes can be incorporated with little modification to the software.     

Optimal Selection of Machinable Volumes

A brief review of the process planning literature is provided. One of the basic issues in process planning is the feature recognition. In the paper rather than representing a part with features, the representation using machinable volumes is emphasized. A model for the selection of machinable volumes with minimum corresponding machining costs, fixture and tool utilization costs is formulated. The model is illustrated with a numerical example. Computational results for five existing parts are presented.     

Analysis of closed loop supply chain using genetic algorithm and particle swarm optimisation

This paper describes a relational database system for semi-generative process planning for sheet metal parts that emulates expert system capabilities. The system integrates a feature-based relational database for the parts, a forward chaining rule-based strategy for machine selection, both global and feature-specific execution of the rules and a graph theoretic cost optimization model for optimal process plan selection. This system, which is currently being developed for a sheet metal fabrication company, suggests that, using the experience of shopfloor personnel, an efficient integration of feature-based process planning and expert system strategies can be accomplished.     

求解带AGV柔性作业车间调度问题的改进灰狼算法

针对带AGV的柔性作业车间调度问题,以最小化完工时间为目标,考虑AGV在装载站、机器、卸载站之间的有效负载时间和空载时间,构建了数学规划模型。其次,提出一种有效的灰狼算法进行求解,基于该问题特征,设计机器选择、工序排序和AGV搬运的3段编码,有效地保证每个个体均可产生可行解;灰狼算法中改进了关键参数a和E设定方式,有效平衡了算法的勘探能力和局部搜索能力;为进一步提升算法跳出局部最优解的能力,该算法融合了领域搜索等方法。最后,案例测试结果表明,改进灰狼算法在求解带AGV柔性作业车间调度问题中具有优越的性能。     

Enriched machining feature-based reasoning for generic machining process sequencing

This paper presents an enriched machining feature (EMF)-based reasoning approach to generic machining process sequencing for distributed process planning (DPP). An EMF is represented by combining its machining volume with surface, geometric and volume features, as well as other technological information needed to machine the feature. The information embedded in the EMF is retrieved progressively for machining sequence generation. Following an introduction of EMF and its representation scheme, the problems in determining machine-independent feature groups (set-ups) in DPP and their machining sequences to be followed for a given part are investigated. Based on the EMF concept, five reasoning rules are formulated and the algorithms developed. As the set-ups and sequences are generated based on manufacturing constraints and datum references but separated from specific resources, they are generic and applicable to machine tools with varying configurations and capabilities. This approach is further validated through a case study.     

Adaptive and dynamic process planning using neural networks

Although feature-based process planning plays a vital role in automating and integrating design and manufacturing for efficient production, its off-line properties prevent the shop floor controller from rapidly coping with dynamic shop floor status such as unexpected production errors and rush orders. This paper proposes a conceptual framework of the adaptive and dynamic process planning system that can rapidly and dynamically generate the needed process plans based on shop floor status. In particular, the generic schemes for constructing dynamic planning models are suggested. The dynamic planning models are constructed as neural network forms, and then embedded into each process feature in the process plan. The shop floor controller will execute them to determine machine, cutting tools, cutting parameters, tool paths and NC codes just before the associated process feature is machined. The dynamic nature of process planning enables the shop floor controller to increase flexibility and efficiency in unexpected situations.     

Reverse engineering of machining operation planning

Computer-aided process planning (CAPP) is becoming increasingly crucial to today's computer-integrated manufacturing (CIM) and rapid production. To automate the process planning, feature-based operation planning systems have been suggested and studied extensively. In such a system, given a machining feature, the operator requires practical machining operation data for the feature. In this research, a system of reverse engineering is proposed to extract machining features and their associated machining operation data. Furthermore, a machining know-how database containing the extracted data is created for future operation planning. Since successful NC programs contain the machining know-how of skilled workers, the system is aimed at extracting the machining know-how data from the NC programs through reverse engineering. The extraction of the machining features and feature topologies has been addressed previously. The present paper deals with the extraction of machining operation data, including operation sequence, cutting conditions, machining type and cutting mode. A prototype of the system is developed and a machining know-how database is generated. The extraction of machining features and their associated machining operations has been verified through a variety of NC programs.     

基于PDM的工艺设计与管理系统的研究及实现

介绍了一个基于PDM的工艺信息及工艺卡片设计管理系统 ,阐述了系统的主要功能、系统结构及软件组织和特点 .该系统通过产品树结构不仅实现了零件工艺的设计 ,还更好地实现了零件图纸、工艺卡片等各类工艺图文信息的有效管理及快速的检索 .     

Integrating CAD and CAM through automated process planning

Computer-aided process planning is an important function in the integration of CAD and CAM. There are two approaches in computer-aided process planning— variant and generative. The generative is more suitable to CAD/CAM integration because it can synthesize a process plan. The success of developing a generative process planning system is dependent on the CAD interface and process capability analysis, The direct interface with CAD eliminates the tedious data preparation for a process planning system (i.e., it eliminates coding). The process capability analysis provides an information base for process and sequence selection. This paper presents a generative process planning system—TTPPS (Totally Integrated Process Planning System). TIPPS uses a boundary representation from a CAD database for a part. A user applies the crosshair cursor on a graphics terminal and a menu display to specify surfaces to be machined. The system then utilizes the information stored in a process knowledge base to determine manufacturing processes, sequence, cutting parameters and time estimation. The geometric modelling, process modelling, decision mechanism and a planning example are discussed.     

Feature-based metal stamping part and process design. Part II: stamping process planning

In metal stamping development, stamping process planning plays quite an important role for the related die design. As mentioned in Part-I [Feature-based metal stamping part and process design. Part 1: stampability evaluation, 2007, 45, 2673–2695], the feature can encapsulate comprehensive engineering information; this paper proposes to realize stamping process planning based on feature mapping. A feature mapping system, between a stamping design feature space and a stamping process feature space, has been presented. The inherent mechanism of such feature mapping has been investigated with formal representations. The substance of feature mapping is the processing of related knowledge and information. Mapping rules are established to generate the stamping operation and stamping direction. Four mapping manners (direct mapping, conjugate mapping, syncretic mapping, and sequential mapping) are presented for generating the form of process feature, through geometrical information transformation from design features. Meanwhile, considering a stamping process plan as an ordered tree, this paper has introduced how to build a stamping process plan through organizing the stamping operations mapped from design features, and an illustrative example is demonstrated.     

从CAD／CAPP集成看轴类零件的产品模型合理表示

本课题组在开发CIMS特征造型软件过程中试作了CAD与CAPP的直接接口,从中发现CAD与CAPP对于零件的特征建模表示方法有不同的理解和要求。本文列举这些差异,以供CIMS和并行工程环境下建立更完善的集成产品信息模型作参考。     

基于KBE的汽车覆盖件冲压工艺方案设计

汽车覆盖件的冲压工艺方案设计是一个复杂且经验性强的创造性过程,需要一种支持多种知识表达模式和多智能决策技术的方法,解决工艺方案决策问题.通过以工艺特征为核心来表达知识,建立了基于KBE的覆盖件工艺知识模型,采用基于知识驱动决策树表达模式的特征转换机制来实现设计特征到工艺特征的映射,在工艺知识库的支持下完成工艺方案设计.实现了知识的多种描述形式及其应用,有效地解决了工艺方案设计中基于图形、规则及经验知识的决策判断,提高了汽车覆盖件工艺方案设计的智能化程度.     

几何约束下曲面场景的立体匹配迭代算法

使用对极约束和同形映射两种几何约束,通过采用面积检测、一致性约束误差检测、概率筛选规则和对称优化等策略,成功地实现了曲面场景图像的特征点匹配.该方法未使用任何与灰度相关的信息和与场景相关的约束,极大地提高了方法的实用性和鲁棒性.整个匹配过程快速有效,并在不同的弱标定关系已知的真实图像数据上成功地得到实现.     

A simulated annealing-based optimization algorithm for process planning

Computer-aided process planning (CAPP) in the past typically employed knowledge-based approaches, which are only capable of generating a feasible plan for a given part based on invariable machining resources. In the field of concurrent engineering, there is a great need for process planning optimization. This paper describes an approach that models the constraints of process planning problems in a concurrent manner. It is able to generate the entire solution space by considering multiple planning tasks, i.e. operations (machine, tool and tool approach direction), selection and operations sequencing simultaneously. Precedence relationships among all the operations required for a given part are used as the constraints for the solution space. The relationship between an actual sequence and the feasibility of applying an operation is also considered. An algorithm based on simulated annealing (SA) has been developed to search for the optimal solution. Several cost factors including machine cost, tool cost, machine change cost, tool change cost and set-up change cost can be used flexibly as the objective function. The case study shows that the algorithm can generate highly satisfying results.     

Expert process planning system with solid model interface

Artificial intelligence (AI) techniques provide various tools for use in the development of automated process planning systems. AI can be utilized for automated reasoning about the shape, features and relationship between features and for development of expert systems for creating the process plan itself. Most of the previous work on AI in process planning deals with one specific application. This paper presents an integrated hierarchical framework of a process planning system with a CAD interface. The objective of the project discussed in the paper is to integrate design with process planning using AI techniques. The development of a CAD interface is discussed with respect to automated feature recognition, determination of tool approach direction and deciding the precedence relationship between the features. Sample results from the CAD interface are presented. The expert system for the process planning module is discussed with the part representation and knowledge base and the plan generation procedure. The module uses hierarchically organized frames for both part representation and the knowledge base. Some initial results are presented from the process planner to demonstrate the current capability of the system.