Determination of machinable volume for finish cuts in CAPP

Identification of machinable volume for finish cut is a complex task as it involves the details not only of the final product but also the intermediate part obtained from rough machining of the blank. A feature recognition technique that adopts a rule-based methodology is required for calculating this small, complex shaped finish cut volume. This paper presents the feature recognition module in a CAPP system that calculates the intermediate finish cut volume by adopting a rule based syntactic pattern recognition approach. In this module, the interfacer uses STEP AP203/214, a CAD neutral format, to trace the coordinate point information and to calculate the machinable volume. Two illustrative examples are given to explain the proposed syntactic pattern approach for prismatic parts

STEP based Finish Machining CAPP system

This research paper presents various methodologies developed in a STEP based Computer Aided Process Planning (CAPP) system named "Finish Machining – CAPP" (FM-CAPP). It is developed to generate automatic process plans for finish machining prismatic parts. It is designed in a modular fashion consisting of three main modules, namely (i) Feature Recognition module (FRM) (ii) Machining Planning Module (MPM) and (iii) Setup Planning Module (SPM). The FRM Module analyses the geometrical and topological information of the inputted part in STEP AP 203/AP214 formats, and generates a text file with full dimensional details of features and machinable volumes. It is then passed on to the MPM for the selection of best suited machining process. Here, the selection is based on a 7 stage elimination strategy considering major manufacturing factors. After machining planning, the task of selecting the best suited setup is implemented in the SPM module. When these tasks are completed, the system generates the process-planning sheet containing the details of feature, finish cut machinable volume, machining processes with the cutting tool/ media, process parameters and the setup required for machining

Process capability modelling: a review report of feature representation methodologies

Approximately 150 technical papers on the features methodology have been carefully studied and some selected papers have been commented upon. The abstracts of the comments are documented and attached to this report. The methodologies reviewed are mainly divided into two approaches, ie. feature recognition and design by features. Papers which deal with some specific topics such as feature taxonomies, dimensions and tolerances, feature concepts, etc. are also included in the document

Development of a manufacturing feature-based design system

Traditional CAD systems are based on the serial approach of the product development cycle: the design process is not integrated with other activities and thus it can not provide information for subsequent phases of product development. In order to eliminate this problem, many modern CAD systems allow the composition of designs from building blocks of higher level of abstraction called features. Although features used in current systems tend to be named after manufacturing processes, they do not, in reality, provide valuable manufacturing data. Apart from the obvious disadvantage that process engineers need to re-evaluate the design and capture the intent of the designer, this approach also prohibits early detection of possible manufacturing problems. This research attempts to bring the design and manufacturing phases together by implementing manufacturing features. A design is composed entirely in a bottom-up manner using manufacturable entities in the same way as they would be produced during the manufacturing phase. Each feature consists of parameterised geometry, manufacturing information (including machine tool, cutting tools, cutting conditions, fixtures, and relative cost information), design limitations, functionality rules, and design-for-manufacture rules. The designer selects features from a hierarchical feature library. Upon insertion of a feature, the system ensures that no functionality or manufacturing rules are violated. If a feature is modified, the system validates the feature by making sure that it remains consistent with its original functionality and design-for-manufacture rules are re-applied. The system also allows analysis of designs, from a manufacturing point of view, that were not composed using features. In order to reduce the complexity of the system, design functionality and design-for manufacture rules are organised into a hierarchical system and are pointed to the appropriate entries of the feature hierarchy. The system makes it possible to avoid costly designs by eliminating possible manufacturing problems early in the product development cycle. It also makes computer-aided process planning feasible. The system is developed as an extension of a commercially available CAD/CAM system (Pro/Engineer), and at its current stage only deals with machining features. However, using the same principles, it can be expanded to cover other kinds of manufacturing processes

On Cognitive Preferences and the Plausibility of Rule-based Models

It is conventional wisdom in machine learning and data mining that logical models such as rule sets are more interpretable than other models, and that among such rule-based models, simpler models are more interpretable than more complex ones. In this position paper, we question this latter assumption by focusing on one particular aspect of interpretability, namely the plausibility of models. Roughly speaking, we equate the plausibility of a model with the likeliness that a user accepts it as an explanation for a prediction. In particular, we argue that, all other things being equal, longer explanations may be more convincing than shorter ones, and that the predominant bias for shorter models, which is typically necessary for learning powerful discriminative models, may not be suitable when it comes to user acceptance of the learned models. To that end, we first recapitulate evidence for and against this postulate, and then report the results of an evaluation in a crowd-sourcing study based on about 3.000 judgments. The results do not reveal a strong preference for simple rules, whereas we can observe a weak preference for longer rules in some domains. We then relate these results to well-known cognitive biases such as the conjunction fallacy, the representative heuristic, or the recogition heuristic, and investigate their relation to rule length and plausibility.Comment: V4: Another rewrite of section on interpretability to clarify focus on plausibility and relation to interpretability, comprehensibility, and justifiabilit

A design-with-features approach for rotational machined components

A major problem in integrating Computer Aided Design (CAD) and Computer Aided Manufacturing (CAM) arises from the difference in thinking between the design and manufacturing people. Designers think of designing a new product in terms of its intended function whereas manufacturing engineers think in terms of decomposing a product design into a set of manufacturing operations. Feature Recognition and Designing with Features have been recognised as alternative approaches to the integration of design and manufacturing functions. In this thesis the second approach has been investigated by developing a feature-based front-end to a CAD solid modeller. This produces the geometric representation of the component in terms of manufacturing features and processes, and simultaneously captures this information in a form suitable for an outline process plan. [Continues.