价值流图析技术——实现精益生产的工具

自从丰田创造了精益生产方式以来,引起了世界汽车工业生产方式的巨大变革。现在它的思想和方法已经被全球汽车界所接受,在美国三大汽车公司制定的“QS-9000质量体系要求”和1999年国际标准化组织颁布的“ISO/TS

基于价值流图析技术的精益改善

要实施精益生产却无从下手，这是很多企业都会遇到的问题。所以了解自己价值流真正的状况，对于企业持续改进，实施精益生产十分重要。文章以某重型汽车公司车身厂车门区精益改善为例，应用价值流图析技术，对车门区的布局、作业、物流等方面存在的问题进行了全面分析，并进行了车门区改善方案的设计。实践证明，企业通过运用图析技术，实施改善后的方案取得了良好的效果。

基于价值流图析技术的精益改善

要实施精益生产却无从下手,这是很多企业都会遇到的问题,所以了解自己价值流真正的状况,对于企业持续改进,实施精益生产来说是十分重要的。文章以某重型汽车公司车身厂车门区精益改善为例,在改善过程中应用价值流图析技术,对车门区进行了布局、作业、物流等方面存在的问题进行了全面分析,并进行了车门区改善方案的设计,通过实施取得良好的效果,旨在为企业提供一种基于现场的实施精益生产的有效途径和方法。希望能帮助企业在实施精益生产过程中更好的发现产生浪费的根源并消除之,以提高企业的竞争力。

现代质量工程方法讲座(八)——第九讲 价值流图析技术

1 基本概念 所谓价值流是指提供一个具体的产品(或服务,或两者的结合)所需的所有具体活动,这些活动包含在三大管理过程之中,即:从概念到生产,从订货到交货,从原材料到顾客手中产品的过程。价值流中存在七种浪费现象(表1中左边一栏),如何来识别这些浪费现象.并采取措施消除,就需要一些方法或手段。这里介绍的几种图析工具(Mapping)

Population-based study of DNA image cytometry as screening method for esophageal cancer

AIM:To explore the DNA image cytometry (DNA-ICM) technique as a primary screening method for esopha-geal squamous precancerous lesions.METHODS:This study was designed as a population-based screening study.A total of 582 local residents aged 40 years-69 years were recruited from Linzhou in Henan and Feicheng in Shandong.However,only 452 subjects had results of liquid-based cytology,DNA-ICM and pathology.The sensitivity and specificity of DNA-ICM were calculated and compared with liquid-based cytology in moderate dysplasia or worse.RESULTS:Sensitivities of DNA-ICM ranging from at least 1 to 4 aneuploid cells were 90.91%,86.36%,79.55% and 77.27%,respectively,which were better than that of liquid-based cytology (75%).Specifici-ties of DNA-ICM were 70.83%,84.07%,92.65% and 96.81%,but the specificity of liquid-based cytology was 91.91%.The sensitivity and specificity of a combination of liquid-based cytology and DNA-ICM were 84.09% and 85.78%,respectively.CONCLUSION:It is possible to use DNA-ICM tech-nique as a primary screening method for esophageal squamous precancerous lesions.

Effects of seasonal water-level fluctuation on soil pore structure in the Three Gorges Reservoir,China

Inundation of the Three Gorges Reservoir has created a 30-m water-level fluctuation zone with seasonal hydrological alternations of submergence and exposure, which may greatly affect soil properties and bank stability. The aim of this study was to investigate the response of soil pore structure to seasonal water-level fluctuation in the reservoir, and particularly, the hydrological change of wetting and drying cycles. Soil pore structure was visualized with industrial X-ray computed tomography and digital image analysis techniques. The results showed that soil total porosity(? 100 ?m), total pore number, total throat number, and mean throat surface area increased significantly under wetting and drying cycles. Soil porosity, pore number and throat numberwithin each size class increased in the course of wetting and drying cycles. The coordination number, degree of anisotropy and fractal dimension were indicating an increase. In contrast, the mean shape factor, pore-throat ratio, and Euler-Poincaré number decreased due to wetting and drying cycles. These illustrated that the wetting and drying cycles made soil pore structure become more porous, continuous, heterogeneous and complex. It can thus be deduced that the water-level fluctuation would modify soil porosity, pore size distribution, and pore morphology in the Three Gorges Reservoir, which may have profound implications for soil processes, soil functions, and bank stability.

Image Analysis on Detachment Process of Dust Cake on Ceramic Candle Filter

Based on the analysis of high-speed video images, the detachment behavior of dust cake from the ceramic candle filter surface during pulse cleaning process is investigated. The influences of the dust cake loading,the reservoir pressure, and the filtration velocity on the cleaning effectiveness are analyzed. Experimental results show that there exists an optimum dust cake thickness for pulse-cleaning process. For thin dust cake, the patchy cleaning exists and the cleaning efficiency is low; if the dust cake is too thick, the pressure drop across the dust cake becomes higher and a higher reservoir pressure may be needed. At the same time there also exists an optimum reservoir pressure for a given filtration condition.

High densities of serotonin and peptide YY cells in the colon of patients with lymphocytic colitis

AIM： TO investigate colonic endocrine cells in lympho- cytic colitis （LC） patients. METHODS： Fifty-seven patients with LC were in- cluded. These patients were 41 females and 16 males, with an average age of 49 years （range 19-84 years）. Twenty-seven subjects that underwent colonoscopy with biopsies were used as controls. These subjects underwent colonoscopy because of gastrointestinal bleeding or health worries, where the source of bleed- ing was identified as haemorrhoids or angiodysplasia. They were 19 females and 8 males with an average age of 49 years （range 18-67 years）. Biopsies from the right and left colon were obtained from both patients and controls during colonoscopy. Biopsies were fixed in 4% buffered paraformaldehyde, embedded in paraffin and cut into 5 μm-thick sections. The sections immunostained by the avidin-biotin-complex method for se- rotonin, peptide YY （PYY）, pancreatic polypeptide （PP） enteroglucagon and somatostatin cells. The cell densi- ties were quantified by computerised image analysis using Olympus software. RESULTS： The colon of both the patient and the control subjects were macroscopically normal. Histo- pathological examination of colon biopsies from con- trols revealed normal histology. All patients fulfilled the diagnosis criteria required for of LC： an increase in intraepithelial lymphocytes （〉 20 lymphocytes/100 epithelial cells） and surface epithelial damage with increased lamina propria plasma cells and absent or minimal crypt architectural distribution. In the colon of both patients and control subjects, serotonin-, PYY-, PP-, enteroglucagon- and somatostatin-immunoreac- tive cells were primarily located in the upper part of the crypts of Lieberk0hn. These cells were basket- or flask-shaped. There was no statistically significant dif- ference between the right and left colon in controls with regards to the densities of serotonin- and PYY- immunoreactive cells （P = 0.9 and 0.1, respectively）. Serotonin cell density in the right colon in controls was 28.9 ± 1.8 and in LC patients 41.6±2.6 （P = 0.008）. In the left colon, the corresponding figures were 28.5± 1.9 and 42.4± 2.9, respectively （P = 0.009）. PYY cell density in the right colon of the controls was 10.1 ± 1 and of LC patients 41 ± 4 （P = 0.00006）. In the left colon, PYY cell density in controls was 6.6± 1.2 and in LC patients 53.3 ± 4.6 （P = 0.00007）. CONCLUSION： The change in serotonin cells could be caused by an interaction between immune cells and serotonin cells, and that of PYY density might be sec- ondary.

Dissolution rate determination of alumina in molten cryolite-based aluminum electrolyte

Determination of dissolution rate of alumina is one of the classical problems in aluminum electrolysis. A novel method which can measure the dissolution rate of alumina was presented. Effect of factors on dissolution rate of alumina was studied intuitively and roundly using transparent quartz electrobath and image analysis techniques. Images about dissolution process of alumina were taken at an interval of fixed time from transparent quartz electrobath of double rooms. Gabor wavelet transforms were used for extracting and describing the texture features of each image. After subsampling several times, the dissolution rate of alumina was computed using these texture features in local neighborhood of samples. Regression equation of the dissolution rate of alumina was obtained using these dissolution rates. Experiments show that the regression equation of the dissolution rate of alumina is y=-0.000 5x^3＋0.024 0x^2-0.287 3x＋ 1.276 7 for Na3AIF6-AIF3-Al2O3-CaF2-LiF- MgF2 system at 920 ℃.

Using Landsat images to monitor changes in the snow-covered area of selected glaciers in northern Pakistan

Landsat satellite images were used to map and monitor the snow-covered areas of four glaciers with different aspects(Passu: 36.473°N, 74.766°E;Momhil: 36.394°N, 75.085°E; Trivor: 36.249°N,74.968°E; and Kunyang: 36.083°N, 75.288°E) in the upper Indus basin, northern Pakistan, from 1990-2014. The snow-covered areas of the selected glaciers were identified and classified using supervised and rule-based image analysis techniques in three different seasons. Accuracy assessment of the classified images indicated that the supervised classification technique performed slightly better than the rule-based technique. Snow-covered areas on the selected glaciers were generally reduced during the study period but at different rates. Glaciers reached maximum areal snow coverage in winter and premonsoon seasons and minimum areal snow coverage in monsoon seasons, with the lowest snow-covered area occurring in August and September. The snowcovered area on Passu glacier decreased by 24.50%,3.15% and 11.25% in the pre-monsoon, monsoon and post-monsoon seasons, respectively. Similarly, the other three glaciers showed notable decreases in snow-covered area during the pre-and post-monsoon seasons; however, no clear changes were observed during monsoon seasons. During pre-monsoon seasons, the eastward-facing glacier lost comparatively more snow-covered area than the westward-facing glacier. The average seasonal glacier surface temperature calculated from the Landsat thermal band showed negative correlations of-0.67,-0.89,-0.75 and-0.77 with the average seasonal snowcovered areas of the Passu, Momhil, Trivor and Kunyang glaciers, respectively, during pre-monsoon seasons. Similarly, the air temperature collected from a nearby meteorological station showed an increasing trend, indicating that the snow-covered area reduction in the region was largely due to climate warming.

Speed-up for N-FINDR algorithm

N-FINDR is a very popular algorithm of endmember (EM) extraction for its automated property and high efficiency. Unfortunately, innumerable volume calculation, initial random selection of EMs and blind searching for EMs lead to low speed of the algorithm and limit the applications of the algorithm. So in this paper two measures are proposed to speed up the algorithm. One of the measures is substituting distance calculation for volume calculation. Thus the avoidance of volume calculation greatly decreases the computational cost. The other measure is resorting dataset in terms of pixel purity likelihood based on pixel purity index (PPI) concept. Then, initial EMs can be selected well-founded and a fast searching for EMs is achieved. Numerical experiments show that the two measures speed up the original algorithm hundreds of times as the number of EMs is more than ten.

Micromechanical analysis of damage evolution in splitting test of asphalt mixtures

A methodology was presented relating the microstructure of asphalt mixtures to their damage behavior. Digital image techniques were used to capture the asphalt mixture microstructure, and the finite element method was used to simulate the damage evolution of asphalt mixture through splitting test. Aggregates were modeled to be linearly elastic, and the mastics were modeled to be plastically damaged. The splitting test simulation results show that the material heterogeneity, the properties of aggregates and air voids have significant effects on the damage evolution approach. The damage behavior of asphalt mixture considering material heterogeneity is quite different from that of the conventional hypothesis of homogeneous material. The results indicate that the proposed method can be extended to the numerical analysis for the other micromechanical behaviors of asphalt concrete.

A Closed Form Solution to Segment 3D Motion Using Straight-line Optical Flow

A closed form solution to the problem of segmenting multiple 3D motion models was proposed from straight-line optical flow. It introduced the multibody line optical flow constraint (MLOFC), a polynomial equation relating motion models and line parameters. The motion models can be obtained analytically as the derivative of the MLOFC at the corresponding line measurement, without knowing the motion model associated with that line. Experiments on real and synthetic sequences were also presented.

Image Analysis of Fabric Pilling Based on Light Projection

The objective assessment of fabric pilling based on light projection and image analysis has been exploited recently.The device for capturing the cross-sectional images of the pilled fabrics with light projection is elaborated.The detection of the profile line and integration of the sequential cross-sectional pilled image are discussed.The threshold based on Gaussian model is recommended for pill segmentation.The results show that the installed system is capable of eliminating the interference with pill information from the fabric color and pattern.

Texture Image Segmentation Based on Nonlinear Diffusion

A texture image segmentation based on nonlinear diffusion is presented. The scale of texture can be measured during the process of nonlinear diffusion. A smooth 5-channel vector image with edge preserved, which is composed of intensity, scale and orientation of texture image, can be achieved by coupled nonlinear diffusion. A multi-channel statistical region active contour is employed to segment this vector image. The method can be seen as a kind of unsupervised segmentation because parameters are not sensitive to different texture images. Experimental results show its high efficiency in the semiautomatic extraction of texture image.

Exact Solutions to a (3+1)-Dimensional Variable-Coefficient Kadomtsev-Petviashvilli Equation via the Bilinear Method and Wronskian Technique

By truncating the Painleve expansion at the constant level term,the Hirota bilinear form is obtainedfor a (3+1)-dimensional variable-coefficient Kadomtsev-Petviashvili equation.Based on its bilinear form,solitary-wavesolutions are constructed via the ε-expansion method and the corresponding graphical analysis is given.Furthermore,the exact solution in the Wronskian form is presented and proved by direct substitution into the bilinear equation.

Weed Recognition Using Image-Processing Technique Based on Leaf Parameters

Weeds normally grow in patches and spatially distributed in field. Patch spraying to control weeds has advantages of chemical saving, reduced cost and environmental pollution. Advent of electro-optical sensing capabilities has paved the way of using machine vision technologies for patch spraying. Machine vision system has to acquire and process digital images to make control decisions. Proper identification and classification of objects present in image holds the key to make control decisions and use of any spraying operation performed. Recognition of objects in digital image may be affected by background, intensity, image resolution, orientation of the object and geometrical characteristics. A set of 16, including 11 shape and 5 texture-based parameters coupled with predictive discriminating analysis has been used to identify the weed leaves. Geometrical features were indexed successfully to eliminate the effect of object orientation. Linear discriminating analysis was found to be more effective in correct classification of weed leaves. The classification accuracy of 69% to 80% was observed. These features can be utilized for development of image based variable rate sprayer.

A syncretic representation for image classification and face recognition

For representation based image classification methods, it is very important to well represent the target image. As pixels at same positions of training samples and test samples of an object usually have different intensities, it brings difficulty in correctly classifying the object. In this paper, we proposed a novel method to reduce the effects of this issue for image classification. Our method first produces a new representation （i.e. virtual image） of original image, which can enhance the importance of moderate pixel intensities and reduce the effects of larger or smaller pixel intensities. Then virtual images and corresponding original images are respectively used to represent a test sample and obtain two rep- resentation results. Finally, this method fuses these two results to classify the test sample. The integration of original image and its virtual image is able to improve the accuracy of image classification. The experiments of image classification show that the proposed method can obtain a higher accuracy than the conventional classification methods.

Detecting Forest Fire Prone Areas Using Object-Based Image Analysis and GIS Techniques： A Case Study in Kayer Khola, Nepal

Every year during summer, natural and human-induced forest fires threaten the environment in the largely forested areas of the Himalayan region and the local population living near these forests. Nepal, with its multitude of forests, is one of the most forest fire-prone areas in the region. This study examines the possibility of averting forest fires, minimizing their frequency and the damage they cause, through advanced mapping of forest fire prone areas using a VHSR （very-high spatial resolution） satellite image of GeoEye-1, DEM （digital elevation data） created from topographic maps and additional data layers （e.g., precipitation, settlements）. The study was conducted in Kayer Khola, Chitwan district, Nepal. The classification of the satellite image has been performed using OBIA （object-based image analysis） techniques taking into account spectral, spatial and context information as well as hierarchical properties. The land cover classification result was thereafter combined with additional data in ArcGIS, where the input layers were reclassified and all classes of the input layers ranked according to their proneness to forest fires. Fire prone areas were delineated in five classes ranging from very high to very low. The study revealed that 82% of fires occur in forest areas. This case study in Kayer Khola shows that OBIA and GIS modeling techniques can be used to successfully identify forest fire-prone areas. The mapping of forest fire-prone areas will enable forest departments in countries of the Himalayan region to delineate forest fire prone areas, which can guide the forest departments set up appropriate fire-fighting infrastructure in these areas and thus help, minimize or avert forest fires.

价值流技术在企业业务流程重组中的应用

BPR理论体系的不成熟,建模分析工具的不完善,是导致企业进行业务流程重组优化时失败的重要原因。价值流技术以往只用于精益生产中,但是它还可以作为一种有效的流程分析工具应用于流程重组优化中。分析并通过示例阐述了价值流技术在BPR中的意义,应用的步骤和改进后的效果,即流程总周期由3700秒减少到1620秒。