Periodic reconfiguration of general-purpose fixtures in a dedicated FMS

Fixtures dedicated to a given part type in an FMS can sometimes become bottlenecks to some FMSs as demand variability increases. Past research indicates that the increased operating flexibility associated with general-purpose fixtures may be a key to the efficient scheduling of even those FMSs dedicated to producing a small number of part types over a known planning horizon. However, the increased time required to reconfigure general-purpose fixtures to meet current demand may also create a bottleneck in the loading area. Increases in the defect rate associated with improper fixture assembly and part alignment are also possible. One solution may be to reconfigure general-purpose fixtures off line according to specific demand schedules for the period, and then to treat them as “pseudo-dedicated” fixtures until the next period. This would utilize some of the flexibility associated with general-purpose fixtures, while reducing the negative drawbacks associated with incremental loading time and alignment errors. The research reported in this article simulates an existing FMS, using fixtures dedicated to individual part types, and compares the results to those collected using a group of general-purpose fixtures that are reconfigured each week, based on current demand for each part type, and used in a pseudo-dedicated fashion. Three simulation experiments are run with increasing coefficients of variation in the input distributions used to generate demand. Performance is measured by system throughput, proportion of parts tardy, and average tardiness. The simulation results show that while overall system performance decreases as the level of demand mix variability increases, this negative impact is significantly less severe when using pseudo-dedicated, general-purpose fixtures.     

A fault identification and classification scheme for an automobile door assembly process

A process fault identification and classification scheme for an automobile door assembly process is presented based on multivariate in-line dimensional measurements and principal component factor analysis. First, the door assembly process and the dimensional measurement system are briefly introduced. Second, the technique of principal component factor analysis is presented for process fault identification. Process faults are summarized based on off-line identified case studies. Finally a machine classification scheme based on principal components and principal factors is presented and evaluated, using the pattern knowledge obtained off-line. This scheme is shown to be effective in classifying process faults using production data.     

Monitoring and classification of dimensional faults for automotive body assembly

Sudden process changes occurring during automobile body assembly processes will influence the downstream assembly process and the functionality and final appearance of the vehicle. Furthermore, these faults could result in a decreased production rate and an increase in the cost if sudden process changes are so serious that the production line has to be stopped for investigation. Thus, sudden process changes should be detected and eliminated as soon as possible to prevent defective products from being produced and to reduce the cost of repairs/reworks. A monitoring algorithm is developed to detect, classify, and group process changes by analyzing the dimensional data of car bodies. The results of this monitoring algorithm can help diagnose the root causes of variation according to the locations of measurement points, body structure, assembly sequence, and tooling layout. Measurement data obtained from an optical coordinate measuring machine (OCMM) are used to demonstrate the monitoring technique.     

A study of FMS part type selection approaches for short-term production planning

This research compares seven approaches from the literature to the selection of part types for simultaneous production over the next time horizon. A flexible approach to the selection of part types and the simultaneous determination of their mix ratios so as to balance aggregate machine workloads is presented. Constraints on tool magazine capacity are considered. Simulation studies are conducted on realistic, detailed models of flexible flow systems (FFSs) configured as pooled machines of equal sizes. The simulated settings are constructed to evaluate the impact of such factors as blocking, transportation, buffer utilizations, and fixture requirements and limitations of various types. One of the goals of this study is to encourage industry to relax, for those FMS types for which the procedure is appropriate, what is essentially an artificial constraint: that tool changing be isolated in time, to a period between batches. For other types of FMSs, batching may be appropriate. The results indicate that using the flexible approach enables the system to be more highly utilized. It is also observed that the batching approaches tend to require more fixtures of each type than the flexible approach. The system utilizations for the batching approaches seem to be more sensitive to restrictions on the number of fixtures of each type. Further research needs are also discussed.     

Time-Based Competition in Multistage Manufacturing: Stream-of-Variation Analysis (SOVA) Methodology—Review

Frequency of model change and the vast amounts of time and cost required to make a changeover, also called time-based competition, has become a characteristic feature of modern manufacturing and new product development in automotive, aerospace, and other industries. This paper discusses the concept of time-based competition in manufacturing and design based on a review of on-going research related to stream-of-variation (SOVA or SoV) methodology. The SOVA methodology focuses on the development of modeling, analysis, and control of dimensional variation in complex multistage assembly processes (MAP) such as the automotive, aerospace, appliance, and electronics industries. The presented methodology can help in eliminating costly trial-and-error fine-tuning of new-product assembly processes attributable to unforeseen dimensional errors throughout the assembly process from design through ramp-up and production. Implemented during the product design phase, the method will produce math-based predictions of potential downstream assembly problems, based on evaluations of the design and a large array of process variables. By integrating product and process design in a pre-production simulation, SOVA can head off individual assembly errors that contribute to an accumulating set of dimensional variations, which ultimately result in out-of-tolerance parts and products. Once in the ramp-up stage of production, SOVA will be able to compare predicted misalignments with actual measurements to determine the degree of mismatch in the assemblies, diagnose the root causes of errors, isolate the sources from other assembly steps, and then, on the basis of the SOVA model and product measurements, recommend solutions.     

Semiconductor fault detection and classification for yield enhancement and manufacturing intelligence

Process monitoring and profile analysis are crucial in detecting various abnormal events in semiconductor manufacturing, which consists of highly complex, interrelated, and lengthy wafer fabrication processes for yield enhancement and quality control. To address real requirements, this study aims to develop a framework for semiconductor fault detection and classification (FDC) to monitor and analyze wafer fabrication profile data from a large number of correlated process variables to eliminate the cause of the faults and thus reduce abnormal yield loss. Multi-way principal component analysis and data mining are used to construct the model to detect faults and to derive the rules for fault classification. An empirical study was conducted in a leading semiconductor company in Taiwan to validate the model. Use of the proposed framework can effectively detect abnormal wafers based on a controlled limit and the derived simple rules. The extracted information can be used to aid fault diagnosis and process recovery. The proposed solution has been implemented in the semiconductor company. This has simplified the monitoring process in the FDC system through the fewer key variables. The results demonstrate the practical viability of the proposed approach.     

Towards robust cell culture processes — Unraveling the impact of media preparation by spectroscopic online monitoring

Biopharmaceutical manufacturing processes can be affected by variability in cell culture media, e.g. caused by raw material impurities. Although efforts have been made in industry and academia to characterize cell culture media and raw materials with advanced analytics, the process of industrial cell culture media preparation itself has not been reported so far. Within this publication, we first compare mid‐infrared and two‐dimensional fluorescence spectroscopy with respect to their suitability as online monitoring tools during cell culture media preparation, followed by a thorough assessment of the impact of preparation parameters on media quality. Through the application of spectroscopic methods, we can show that media variability and its corresponding root cause can be detected online during the preparation process. This methodology is a powerful tool to avoid batch failure and is a valuable technology for media troubleshooting activities. Moreover, in a design of experiments approach, including additional liquid chromatography–mass spectrometry analytics, it is shown that variable preparation parameters such as temperature, power input and preparation time can have a strong impact on the physico‐chemical composition of the media. The effect on cell culture process performance and product quality in subsequent fed‐batch processes was also investigated. The presented results reveal the need for online spectroscopic methods during the preparation process and show that media variability can already be introduced by variation in media preparation parameters, with a potential impact on scale‐up to a commercial manufacturing process.     

磁共振成像对乳腺肿瘤的诊断价值

乳腺癌是危及女性健康的常见恶性肿瘤之一,病死率较高,且发病年龄呈年轻化趋势。目前临床对乳腺疾病的检查方法很多,既往检查主要包括钼靶、超声等,因价格便宜、操作方便,已成为常规的乳腺疾病检查方法,但两者的敏感性和特异性较低并有自身的局限性。CT软组织分辨率较高,但检查过程中的X线剂量较大,并且动态增强时间较长,故作为乳腺钼靶的补充检查手段。这些检查方法对乳腺疾病均有不同的诊断意义,在当前众多诊断乳腺疾病方法中,具有无辐射,较高软组织分辨力及可多方位多层面成像的乳腺磁共振(MRI)成像有其独到的优势,某些方面能弥补超声和钼靶检查的局限性,乳腺磁共振可提供病灶形态学和增强血流动力学表现,可用于常规检查方法不能确诊病灶的鉴别诊断。乳腺肿瘤MRI成像对临床诊断、鉴别诊断及手术方案的选择有着极其重要的作用。本文就乳腺MRI影像技术、MRI影像学表现及其临床应用予以综述,探讨MRI在乳腺肿瘤中的应用。     

Fault diagnosis of a benchmark fermentation process: a comparative study of feature extraction and classification techniques

This paper investigates fault diagnosis in batch processes and presents a comparative study of feature extraction and classification techniques applied to a specific biotechnological case study: the fermentation process model by Birol et al. (Comput Chem Eng 26:1553–1565, 2002), which is a benchmark for advanced batch processes monitoring, diagnosis and control. Fault diagnosis is achieved using four approaches on four different process scenarios based on the different levels of noise so as to evaluate their effects on the performance. Each approach combines a feature extraction method, either multi-way principal component analysis (MPCA) or multi-way independent component analysis (MICA), with a classification method, either artificial neural network (ANN) or support vector machines (SVM). The performance obtained by the different approaches is assessed and discussed for a set of simulated faults under different scenarios. One of the faults (a loss in mixing power) could not be detected due to the minimal effect of mixing on the simulated data. The remaining faults could be easily diagnosed and the subsequent discussion provides practical insight into the selection and use of the available techniques to specific applications. Irrespective of the classification algorithm, MPCA renders better results than MICA, hence the diagnosis performance proves to be more sensitive to the selection of the feature extraction technique.     

A diabetic retinopathy detection method using an improved pillar K-means algorithm

The paper presents a new approach for medical image segmentation. Exudates are a visible sign of diabetic retinopathy that is the major reason of vision loss in patients with diabetes. If the exudates extend into the macular area, blindness may occur. Automated detection of exudates will assist ophthalmologists in early diagnosis. This segmentation process includes a new mechanism for clustering the elements of high-resolution images in order to improve precision and reduce computation time. The system applies K-means clustering to the image segmentation after getting optimized by Pillar algorithm; pillars are constructed in such a way that they can withstand the pressure. Improved pillar algorithm can optimize the K-means clustering for image segmentation in aspects of precision and computation time. This evaluates the proposed approach for image segmentation by comparing with Kmeans and Fuzzy C-means in a medical image. Using this method, identification of dark spot in the retina becomes easier and the proposed algorithm is applied on diabetic retinal images of all stages to identify hard and soft exudates, where the existing pillar K-means is more appropriate for brain MRI images. This proposed system help the doctors to identify the problem in the early stage and can suggest a better drug for preventing further retinal damage.     

Involvement of the portal at an early step in herpes simplex virus capsid assembly

DNA enters the herpes simplex virus capsid by way of a ring-shaped structure called the portal. Each capsid contains a single portal, located at a unique capsid vertex, that is composed of 12 UL6 protein molecules. The position of the portal requires that capsid formation take place in such a way that a portal is incorporated into one of the 12 capsid vertices and excluded from all other locations, including the remaining 11 vertices. Since initiation or nucleation of capsid formation is a unique step in the overall assembly process, involvement of the portal in initiation has the potential to cause its incorporation into a unique vertex. In such a mode of assembly, the portal would need to be involved in initiation but not able to be inserted in subsequent assembly steps. We have used an in vitro capsid assembly system to test whether the portal is involved selectively in initiation. Portal incorporation was compared in capsids assembled from reactions in which (i) portals were present at the beginning of the assembly process and (ii) portals were added after assembly was under way. The results showed that portal-containing capsids were formed only if portals were present at the outset of assembly. A delay caused formation of capsids lacking portals. The findings indicate that if portals are present in reaction mixtures, a portal is incorporated during initiation or another early step in assembly. If no portals are present, assembly is initiated in another, possibly related, way that does not involve a portal.     

植物群落构建机制研究进展

群落构建研究对于解释物种共存和物种多样性的维持是至关重要的,因此一直是生态学研究的中心论题。尽管近年来关于生态位和中性理论的验证研究已经取得了显著的成果,但对于局域群落构建机制的认识仍存在很大争议。随着统计和理论上的进步使得用功能性状和群落谱系结构解释群落构建机制变为可能,主要是通过验证共存物种的性状和谱系距离分布模式来实现。然而,谱系和功能性状不能相互替代,多种生物和非生物因子同时控制着群落构建,基于中性理论的扩散限制、基于生态位的环境过滤和竞争排斥等多个过程可能同时影响着群落的构建。所以,综合考虑多种方法和影响因素探讨植物群落的构建机制,对于预测和解释植被对干扰的响应,理解生物多样性维持机制有重要意义。试图在简要回顾群落构建理论及研究方法发展的基础上,梳理其最新研究进展,并探讨整合功能性状及群落谱系结构的研究方法,解释群落构建和物种多样性维持机制的可能途径。在结合功能性状和谱系结构研究群落构建时,除了考虑空间尺度、环境因子、植被类型外,还应该关注时间尺度、选择性状的种类和数量、性状的种内变异、以及人为干扰等因素对群落构建的影响。     

What are we dealing with? An explicit test reveals different levels of taxonomical diagnosability in the Sylvia cantillans species complex

Diagnosability is the ability to discriminate between similar taxa, including sibling or cryptic taxa. We have developed an explicit test of diagnosability, using the Sylvia cantillans species complex as a model, which compares an identification based on phenotype with that based on genotype. Individual warblers sampled during their migration in central Italy were first identified to the (sub)species level using putatively diagnostic plumage traits. Nucleotide sequences of a (598-bp) fragment of the mitochondrial (mt)DNA cytochrome b were then used to assign each individual to distinct phylogenetic clades, as determined by reference haplotypes that had been sequenced in breeding individuals. This resulted in the construction of clearly distinct clades corresponding to known taxa of the complex. The new haplotypes were assigned to one of the previously identified groups (corresponding to three different taxa); no sample was assigned outside of them. In contrast, when plumage traits were used to assign the birds into distinct phylogenetic clades, 11 of 58 birds were classified as ‘uncertain/intermediate’ among two taxa, while five were classified differently with the two methods. A perfect agreement between the two methods was found for only for one taxon (Sylvia subalpina, syn. S. moltonii). For the other two taxa of the complex, diagnosability is therefore not guaranteed, and their field identification by hand should be carefully addressed. We provide here an example of an explicit test for establishing the diagnosability of taxa in which two or more ‘markers’ can be used for determining discordant identification and/or unambiguous diagnosability. Our results outline the importance of considering different features for taxa diagnosis and illustrate the weakness of visual appearance-based identification (currently widely used for taxa determination) in our study complex.     

Change In Cycle Length During Narrow Complex Tachycardia: What Is The Mechanism?

Major spontaneous variation in cycle length during supraventricular tachycardia is quite an uncommon phenomenon, which sometimes can mislead a correct diagnosis. We describe a patient who developed spontaneous variation in cycle length during electrophysiologic study in whom the coronary sinus cannulation was extremely difficult. In this situation, careful inspection of the mechanisms associated with this variation and classic pacing maneuvers are important to make a correct diagnosis of the supraventricular tachycardia.     

Incorporating intraspecific variation in tests of trait-based community assembly

Environmental filtering and niche differentiation are processes proposed to drive community assembly, generating nonrandom patterns in community trait distributions. Despite the substantial intraspecific trait variation present in plant communities, most previous studies of trait-based community assembly have used species mean trait values and therefore not accounted for intraspecific variation. Using a null model approach, I tested for environmental filtering and niche differentiation acting on three key functional traits??vegetative height, specific leaf area (SLA), and leaf dry matter content (LDMC)??in old-field plant communities. I also examined how accounting for intraspecific variation at the among-plot and individual levels affected the detection of nonrandom assembly patterns. Tests using fixed species mean trait values provided evidence of environmental filtering acting on height and SLA and niche differentiation acting on SLA. Including plot-level intraspecific variation increased the strength of these patterns, indicating an important role of intraspecific variation in community assembly. Tests using individual trait data indicated strong environmental filtering acting on all traits, but provided no evidence of niche differentiation, although these signals may have been obscured by the effects of dispersal limitation and spatial aggregation of conspecific individuals. There was also strong evidence of nonrandom assembly of individuals within single species, with the strength of environmental filtering varying among species. This study demonstrates that, while analyses using fixed species mean trait values can provide insights into community assembly processes, accounting for intraspecific variation provides a more complete view of communities and the processes driving their assembly.     

Simulations Show that Virus Assembly and Budding Are Facilitated by Membrane Microdomains

For many viruses, assembly and budding occur simultaneously during virion formation. Understanding the mechanisms underlying this process could promote biomedical efforts to block viral propagation and enable use of capsids in nanomaterials applications. To this end, we have performed molecular dynamics simulations on a coarse-grained model that describes virus assembly on a fluctuating lipid membrane. Our simulations show that the membrane can promote association of adsorbed subunits through dimensional reduction, but it also introduces thermodynamic and kinetic effects that can inhibit complete assembly. We find several mechanisms by which membrane microdomains, such as lipid rafts, reduce these effects, and thus, enhance assembly. We show how these predicted mechanisms can be experimentally tested. Furthermore, the simulations demonstrate that assembly and budding depend crucially on the system dynamics via multiple timescales related to membrane deformation, protein diffusion, association, and adsorption onto the membrane.     

Information, discrimination and divergence in cytology. I. Theoretical aspects and definitions

The results of medical tests update the probability of diagnosis (diagnosability) of a patient from the population prevalence of a disease. This paper demonstrates a method of combining several mutually dependent tests as the sum of log odds ratios, and of separating the log odd ratios of the test results and those of prevalences. Extending Kullback's discriminant function between two states to m states (m greater than or equal to 2), it is shown that the information of a test can be measured by discrimination and divergence, which are well-defined measures in information theory and test theory. The performance of diagnostic cytology can then be compared to the results of histopathologic diagnoses or to a peer-reviewed consensus without the use of arbitrarily given scores or without unfounded assumptions about underlying continuous variables. They can also provide a way to optimize the categorization (classification) of Papanicolaou smears and a means of quality control for morphologic tests. These methods can be used to evaluate the performances of cytology laboratories that use two classifications consisting of different numbers of categories (classes) and states.     

Succinct data structures for assembling large genomes

MOTIVATION: Second-generation sequencing technology makes it feasible for many researches to obtain enough sequence reads to attempt the de novo assembly of higher eukaryotes (including mammals). De novo assembly not only provides a tool for understanding wide scale biological variation, but within human biomedicine, it offers a direct way of observing both large-scale structural variation and fine-scale sequence variation. Unfortunately, improvements in the computational feasibility for de novo assembly have not matched the improvements in the gathering of sequence data. This is for two reasons: the inherent computational complexity of the problem and the in-practice memory requirements of tools. RESULTS: In this article, we use entropy compressed or succinct data structures to create a practical representation of the de Bruijn assembly graph, which requires at least a factor of 10 less storage than the kinds of structures used by deployed methods. Moreover, because our representation is entropy compressed, in the presence of sequencing errors it has better scaling behaviour asymptotically than conventional approaches. We present results of a proof-of-concept assembly of a human genome performed on a modest commodity server.     

The effect of test methodology on apparent compressive stiffness of tibiofemoral joint specimens

Several investigators have analysed the compressive load bearing properties of the knee. Careful review of these force/displacement data showed considerable variation, with some investigators reporting displacements 12-15 x higher than others for nearly identical testing conditions using the same animal model. In this study, we sought to determine if this variability was inherent in the tibiofemoral joint or if differences in experimental methodology explained the variation. Compressive force/displacement curves were obtained from 39 normal canine tibiofemoral specimens mounted in a universal testing machine. Two commonly reported methods of measuring compressive displacement were used simultaneously. The testing machine crosshead displacement was used as one measure of displacement of the joint. The other method consisted of extensometers mounted to bone at the joint line. Resultant joint rotation in the parasagittal plane was also measured. Using either approach, we found comparatively little variation among the 39 specimens tested. However, the crosshead displacement measurements diverged from the extensometer measurements as the compressive load increased. At 770 N, the crosshead measurement was nearly twice the extensometer displacement. Further analysis showed that the compliances differed by a uniform amount. Parasagittal joint rotation, as measured by the extensometers, was minimal--less than one half of one degree. Although our loading fixtures were expected to be rigid under the loads used, these data suggest that the deformation of the bone and loading fixtures was responsible for the differences we observed, and may be responsible for the variation in compressive displacement results among several published studies. A model is presented which uses a simple elastic element to represent this deformation.