基于装配层的配合尺寸继承与检验

尺寸信息的表达与处理,直接关系到零件的加工成本以及产品质量,文中分析了装配层尺寸的约束与关联,提出了基于装配层的配合尺寸继承与尺寸检验方法,通过配合的识别,尺寸匹配的自组织,实现了不同零件间的配合尺寸的关联,不仅解决了装配层与零件层间具有直接匹配关系的尺寸合理性差别问题,而且可通过尺寸约束与空间基坐标的传递,实现了配合尺寸的不同标注型式的尺寸继承与检验。     

装配体中自顶向下关联设计

一、Top-Down设计法概述一般的机械设计采用的是自下而上的方法。首先,工程人员仔细研究掌握各部件的性能和局限,在这基础上设计出由它们组成的大一点的部件,反复试验后再往上走一层,如此逐步地完成整个设计任务。但如果产品系统复杂程度大大增加,产品具有专业面广、设计更改频繁及各专业间关系密切等特点时,在产品设计过程中,往往存在着外形与结构、结构与系统等三维模型之间的相互影响、相互依赖。自下而上的设计方法在效率及控制设计错误时往往无法满足需要。     

基于约束的装配体位置描述及求解

装配体设计是计算机辅助设计(CAD)的一个重要组成部分,本文就装配体设计中装配体位置的描述及自动求解这两个关键问题进行了深入的探讨,提出了基于约束的装配体相互位置关系的描述方法及自动求解算法.同时本文首次引入奇异矩阵的方法,较好地解决了装配体位置的约束冗余、约束不足以及病态矩阵的问题.     

基于组件技术的ABS综合检测系统的设计与实现

分析了汽车ABS综合检测系统的需求特点,根据组件技术开发软件的优势,提出用组件技术开发汽车ABS综合检测系统.系统层次结构清晰,具有良好的通用性和可维护性,极大地降低了系统研发的难度,是开发汽车ABS检测系统的一个新方案.     

COSMOSWorks使装配体的分析变得简单——接头处理

一、引言 接头是一种用来定义某个面与另一个面或与地之间连接方式的装置.在很多实际设计中经常会遇到接头,并且使用它可以简化建模的过程.     

基于检测数据的大型装配体结构件组合加工新方法

组合加工是一种重要的工艺方法,通常在部件装配或焊接后形成整舱或整星时进行,它可以保证部件上的零件在装配或焊接后相对整舱或整星基准的形位精度.     

基于CT反演的引信装配正确性快速检测技术

引信装配正确性检测是工业生产的关键环节,传统提取人工设计特征匹配的检测方法受装配公差和机械精度等影响,识别鲁棒性较差,而基于深度学习的检测方法虽然可实现引信内部零件的错装、漏装识别,鲁棒性高,但是无法实现零构件分布位置快速检测。针对该问题,结合CT重构空间位置信息和数字成像(DR)检测实时性优点,提出基于CT反演的引信装配正确性快速检测技术。首先,等间隔、多角度采样获取引信投影序列;其次,使用Faster-RCNN检测网络分类定位零构件;最后,根据定位结果进行CT反演,实现零件漏缺和错位检测。实验表明,所提出的方法可以有效解决引信零件分布快速检测问题,有高鲁棒性。     

消防栓控制开关装配体公差分析及设计改进

在新系列消防栓产品控制开关的早期设计过程中,笔者做了CETOL的公差分析和评估,结合实际生产中可能产生的问题,进行早期设计改进和优化,并结合试生产的验证,对设计做出了有益的提示。一、引言目前,在很多产品设计过程中,根据装配性能要求,在CAD系统中采用自顶向下的建模方法,依次创建装配体的零件模型。在CAD可视化的装配环境下,需要对装配性能尺     

Pro/ECHANICA与ANSYS在装配体结构分析中的应用比较

本文首先以一个形状简单且受简单约束和外力的装配体为例．分别利用ANSYS和Pro／MECHANICA进行分析，从而说明Pro／MECHANICA在进行装配体结构分析时比ANSYS更简便高效。[编者按]     

基于多组件智能体技术的布局问题求解方法研究

在简要介绍组件智能体技术的基础上,提出基于多组件智能体技术的布局问题协同求解方法模型。详细描述了模型中各组件智能体的定义和功能,通过它们之间的协同工作,克服传统求解方法的缺点,使其具有较强的问题求解能力和环境适应能力。     

Geometric and form feature recognition tools applied to a design for assembly methodology

The paper presents geometric tools for an automated Design for Assembly (DFA) assessment system. For each component in an assembly a two step features search is performed: firstly (using the minimal bounding box) mass, dimensions and symmetries are identified allowing the part to be classified, according to DFA convention, as either rotational or prismatic; secondly form features are extracted allowing an effective method of mechanised orientation to be determined. Together these algorithms support the fuzzy decision support system, of an assembly-orientated CAD system known as FuzzyDFA.     

Applying a fusion of wearable sensors and a cognitive inspired architecture to real-time ergonomics analysis of manual assembly tasks

High value manufacturing systems still require ergonomically intensive manual activities. Examples include the aerospace industry where the fitting of pipes and wiring into confined spaces in aircraft wings is still a manual operation. In these environments, workers are subjected to ergonomically awkward forces and postures for long periods of time. This leads to musculoskeletal injuries that severely limit the output of a shopfloor leading to loss of productivity. The use of tools such as wearable sensors could provide a way to track the ergonomics of workers in real time. However, an information processing architecture is required in order to ensure that data is processed in real time and in a manner that meaningful action points are retrieved for use by workers.In this work, based on the Adaptive Control of Thought—Rational (ACT-R) cognitive framework, we propose a Cognitive Architecture for Wearable Sensors (CAWES); a wearable sensor system and cognitive architecture that is capable of taking data streams from multiple wearable sensors on a worker’s body and fusing them to enable digitisation, tracking and analysis of human ergonomics in real time on a shopfloor. Furthermore, through tactile feedback, the architecture is able to inform workers in real time when ergonomics rules are broken. The architecture is validated through the use of an aerospace case study undertaken in laboratory conditions. The results from the validation are encouraging and in the future, further tests will be performed in an actual working environment.     

Path dependent stochastic models to detect planned and actual technology use: A case study of OpenOffice

Context

Adopting IT innovation in organizations is a complex decision process driven by technical, social and economic issues. Thus, those organizations that decide to adopt innovation take a decision of uncertain success of implementation, as the actual use of a new technology might not be the one expected. The misalignment between planned and effective use of innovation is called assimilation gap.

Objective

This research aims at defining a quantitative instrument for measuring the assimilation gap and applying it to the case of the adoption of OSS.

Method

In this paper, we use the theory of path dependence and increasing returns of Arthur. In particular, we model the use of software applications (planned or actual) by stochastic processes defined by the daily amounts of files created with the applications. We quantify the assimilation gap by comparing the resulting models by measures of proximity.

Results

We apply and validate our method to a real case study of introduction of OpenOffice. We have found a gap between the planned and the effective use despite well-defined directives to use the new OS technology. These findings suggest a need of strategy re-calibration that takes into account environmental factors and individual attitudes.

Conclusions

The theory of path dependence is a valid instrument to model the assimilation gap provided information on strategy toward innovation and quantitative data on actual use are available.     

Texture analysis of poly-adenylated mRNA staining following global brain ischemia and reperfusion

Texture analysis provides a means to quantify complex changes in microscope images. We previously showed that cytoplasmic poly-adenylated mRNAs form mRNA granules in post-ischemic neurons and that these granules correlated with protein synthesis inhibition and hence cell death. Here we utilized the texture analysis software MaZda to quantify mRNA granules in photomicrographs of the pyramidal cell layer of rat hippocampal region CA3 around 1 h of reperfusion after 10 min of normothermic global cerebral ischemia. At 1 h reperfusion, we observed variations in the texture of mRNA granules amongst samples that were readily quantified by texture analysis. Individual sample variation was consistent with the interpretation that animal-to-animal variations in mRNA granules reflected the time-course of mRNA granule formation. We also used texture analysis to quantify the effect of cycloheximide, given either before or after brain ischemia, on mRNA granules. If administered before ischemia, cycloheximide inhibited mRNA granule formation, but if administered after ischemia did not prevent mRNA granulation, indicating mRNA granule formation is dependent on dissociation of polysomes. We conclude that texture analysis is an effective means for quantifying the complex morphological changes induced in neurons by brain ischemia and reperfusion.