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Geometric-physical modeling and simulation of tool machining processes is an effective realization for manufacturing prediction and verification. By integrating the scheme of CNC code analysis, process planning and optimization, cutting mechanism model, and other related aspects, micro cutting details were implemented to be simulated in advance, detected and monitored in the process, and analyzed afterwards, to achieve the purpose of "Verification IS Production." Pursuant to this purpose, this paper proposed a research framework of micro geometric modeling and physical simulation for machine tool cutting. On the basis of continuous improvements in 3D modules for cutting geometry simulation, the physical simulation research and verification was carried out with several typical scenes, in which the mappings between real occasions and simulation system were established. With the cutting physical models, this paper deeply investigated the simulation calculation and correction for various factors affecting the cutting performance and indicators and finally verifies, analyzes, and optimizes them through actual machining environments. The purpose of this paper is to explore a feasible and novel way for richer scenes and further research through the multi-element modeling of several comprehensive cutting cases and in-depth micro geometry and physics investigation. [ABSTRACT FROM AUTHOR]

Turning is the one of the most commonly available and least expensive machining operations. Confronted with the increased number of part variants and the requirement for fast system responsiveness in dynamic environments, traditional methods for building a computer-aided process planning (CAPP) system for turning are infeasible due to the fixed feature library and hard-coded heuristic rules. In this paper, a customizable approach for automatic process planning of rotational parts is proposed to boost the productivity of enterprises by realizing multi-level machining feature recognition and knowledge-based machining activity/resource selection. First, from the decomposed cells of the turning area, basic turning features are successively recognized based on a novel cell machinability analysis. The high-level custom features are define based on the directed acyclic graph and recognized from the basic feature precedence graph using the subgraph matching algorithm. To facilitate the knowledge-based process planning, a knowledge base is then established utilizing ontology, in which the taxonomies, properties, and causal relationships among the core concepts, namely, machining feature, machining operation, cutting tool, and machine tool, are formally defined. Finally, a five-step procedure is proposed to automatically infer manufacturing activity/resource for multi-level features through rule-based reasoning. The effectiveness and extensibility of the proposed approach are validated through two case studies on complex rotational parts. [ABSTRACT FROM AUTHOR]

Traditional adaption of CAD geometry, which plays an important role in generating effective and fit-for-purpose finite element models, is usually carried out manually and optionally with excessive dependence on engineer's experience. Automatic and efficient geometry modification before simulation evidently improves design efficiency and quality, and cuts down product life cycle. This paper represents an automatic approach to generate simplified and idealized geometry models for CAE simulation, which consists of hybrid model simplification criteria, feature-based model simplification, and simulation intent driven geometry modification. Hybrid adaption criteria takes detailed features geometric dimension, geometry topology, design intent into consideration synthetically. Simulation intent-driven modification with the help of virtual topology operators helps to deal with geometry at a higher level to get an ameliorative boundary for mesh without perturbing the original design model with constructing history for down-stream manufacture-oriented application, such as machining feature recognition and process planning. Development of plug-in toolkit guarantees automation of the simplification process and helps generate simulation-fitted geometry for subsequent analysis and simulation process. Prototype system and cases are implemented to demonstrate the result and efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

Quick quotations for customised parts are one of the effective ways for enterprises to win the market opportunities and also play important roles in production plan. Current researches have made great advancements in this field, while most of them place emphases on the technologies for a higher accuracy as for certain category of parts. In this paper, a framework for part quotations is proposed for customised parts through rough requests, in which several published algorithms are directly implanted. First, the input parts are automatically categorised according to their shapes. Next, corresponding algorithms are invoked to estimate their prices respectively, which is transparent to users. Finally, the quoting results are presented in a uniform output. Most processes including the geometric operations can be directly handled on the website, which provides the users a convenient platform. To further improve the evaluated accuracy, relevance feedback is adopted to optimise the embedded calculating mechanisms with the gradual accumulation of cases and manual corrections. For better flexibility and extendibility, the built-in algorithms are deployed in the plug-and-play manner with the uniform data input-output interface. Later experiments validate this conception and the online system performs well especially for rod parts, box parts and mould sets, which will bring a novel way to the manufacturing enterprises in their order processing. [ABSTRACT FROM AUTHOR]