A decision-making framework model for design and manufacturing of mechanical transmission system development

Knowledge-based systems are proving to be a powerful tool with great potential for developing intelligent design support environments to improve quality of products and reduce product development costs by eliminating or minimizing many of the trial-and-error iterations involved in product development. This article describes an approach towards the development of intelligent design support environments for mechanical transmission systems, along with implementation details of a distributed knowledge-based gearing design and manufacturing system that is deployed over the Internet. The system embodies the various tasks of the design process, with modules that address: performance evaluation, process optimization, manufacturability analysis, and provides reasoning and decision-making capabilities for reducing the time between gear tooth creation, detailed design and final production. This methodology is highly desirable in that it is able to simulate real working conditions, evaluate and optimize the design effectively, prevent designers from time-consuming iterations and reduce long and expensive test phases.     

Performance of multiclass BCMP model for computer system based on fuzzy set theory

The purpose of this paper is to combine the ability of fuzzy set to represent more realistic situations with the well-established traditional queueing system model problem. We are forced to employ subjective probabilities when there is no information about a model or some parameters of a model are vague. The information and data are very fuzzy, because they are frequently very little, 'and may be sometimes obtained from experts subjectively. We apply fuzzy set theory to the closed multiclass model with the fuzzy queues. thus, we represent the characteristic and performance of the closed multiclass model based on the proposed fuzzy set theory.     

A framework for design of scheduled output feedback model predictive control

We present a stabilizing scheduled output feedback Model Predictive Control (MPC) algorithm for constrained nonlinear systems with large operating regions. We design a set of local output feedback predictive controllers with their estimated regions of stability covering the desired operating region, and implement them as a single scheduled output feedback MPC which on-line switches between the set of local controllers and achieves nonlinear transitions with guaranteed stability. This algorithm provides a general framework for scheduled output feedback MPC design.     

A personal computer based expert system framework for the design of experiments

In the field of industrial engineering, experimental design play a large role in the manufacturing quality. Knowledge based systems for parameter design will provide the quality engineer with a powerful tool to increase quality. Just as the past ten years saw a movement away from inspection to statistical process control, the future will see a shift from statistical process control to system and parameter design. Improvements in quality will increasingly come from products that are robust in design which will perform well in the very variable environment that is the global market.     

A nonlinear model predictive control system based on Wiener piecewise linear models

In this paper a nonlinear model predictive control (NMPC) based on a Wiener model with a piecewise linear gain is presented. This approach retains all the interested properties of the classical linear model predictive control (MPC) and keeps computations easy to solve due to the canonical structure of the nonlinear gain. Some guidelines for the identification of the nominal model as well as the uncertainty bounds are discussed, and two examples that show the possibility of application of this control scheme to real life problems are presented.     

A system integration framework for coupled multiphysics simulations

Multiphysics simulations are playing an increasingly important role in computational science and engineering for applications ranging from aircraft design to medical treatments. These simulations require integration of techniques and tools from multiple disciplines, and in turn demand new advanced technologies to integrate independently developed physics solvers effectively. In this paper, we describe some numerical, geometrical, and system software components required by such integration, with a concrete case study of detailed, three-dimensional, parallel rocket simulations involving system-level interactions among fluid, solid, and combustion, as well as subsystem-level interactions. We package these components into a software framework that provides common-refinement based methods for transferring data between potentially non-matching meshes, novel and robust face-offsetting methods for tracking Lagrangian surface meshes, as well as integrated support for parallel mesh optimization, remeshing, algebraic manipulations, performance monitoring, and high-level data management and I/O. From these general, reusable framework components we construct domain-specific building blocks to facilitate integration of parallel, multiphysics simulations from high-level specifications that are easy to read and can also be visualized graphically. These reusable building blocks are integrated with independently developed physics codes to perform various multiphysics simulations.     

Process control in CNC manufacturing for discrete components: A STEP-NC compliant framework

With today's highly competitive global manufacturing marketplace, the pressure for right-first-time manufacture has never been so high. New emerging data standards combined with machine data collection methods, such as in-process verification lead the way to a complete paradigm shift from the traditional manufacturing and inspection to intelligent networked process control. Low-level G and M codes offer very limited information on machine capabilities or work piece characteristics which consequently, results in no information being available on manufacturing processes, inspection plans and work piece attributes in terms of tolerances, etc. and design features to computer numerically controlled (CNC) machines. One solution to the aforementioned problems is using STEP-NC (ISO 14649) suite of standards, which aim to provide higher-level information for process control. In this paper, the authors provide a definition for process control in CNC manufacturing and identify the challenges in achieving process control in current CNC manufacturing scenario. The paper then introduces a STEP-compliant framework that makes use of self-learning algorithms that enable the manufacturing system to learn from previous data and results in eliminating the errors and consistently producing quality products. The framework relies on knowledge discovery methods such as data mining encapsulated in a process analyser to derive rules for corrective measures to control the manufacturing process. The design for the knowledge-based process analyser and the various process control mechanisms conclude the paper.     

Case based reasoning method for computer aided welding fixture design

This paper presents a case-based reasoning (CBR) method for welding fixture design, a critical issue in the manufacturing of large and complicated equipment. However, previous fixture design research has mainly focused on machining fixtures rather than welding fixtures. In this paper, an approach of data abstraction for fixture design information representation is proposed, first to systemize and manage myriads of fixture related resources, e.g., past fixture design solutions, fixture units depository. Based on this approach, a multi-level CBR method for welding fixture design is then presented. This method could help designers, by referencing previous design cases, to make a conceptual fixturing solution quickly and, finally, finish the detailed solution of fixture design.     

A process control system for cryogenic CNC elastomer machining

The application of cryogenics in manufacturing has previously received significant attention in supporting manufacturing processes. This paper explores the continued application of cryogenic manufacturing for producing personalised products. This paper presents the novel concept of cryogenic CNC machining of elastomers and the development of a process control system for cryogenic CNC machining. The control process is illustrated alongside material dependent machining data and example soft elastomer machined parts. An enhancement to the process is also detailed within a closed loop thermally monitored cryogenic CNC machining facility.     

A distributed collaborative product design environment based on semantic norm model and role-based access control

With the boom of Internet Technology, it becomes possible to combine designers from different disciplines into one team to support product design globally. In this paper, a distributed collaborative product design environment is presented to support top-down process oriented product design. In conceptual design stage, the artifact is managed by semantic norm model (SNM). In SNM, the designers can define virtual components at early design stage and instantiate those components at later detailed design stage. By role-based access control (RBAC), different roles with corresponding permissions could be assigned to distributed designers, and the designers could concurrently modify different components of the product relevant to his or her roles. Based on the SNM and RBAC system, a distributed collaborative product design environment is developed and the top-down oriented product design process is demonstrated.     

Patch programming: The integration of motion planning into numerical control

The conventional input of a CNC, a sequence of data points, describing the tool motion necessary for machining free-form curves and surfaces, represent a huge amount of information. Usually these are stored on papertape, and are difficult to handle and occupy an unacceptable amount of storage. As sculptured surfaces are usually described as sets of bicubic patches, it is a straightforward solution to extend the CNC-s capabilities with cubic interpolations. The tool path is calculated real time, during the cutting process. Figures are given to underline the advantages of the system.     

A stamp based exploration framework for numerical weather forecast

Numerical weather simulation data usually comprises various meteorological variables, such as precipitation, temperature and pressure. In practical applications, data generated with several different numerical simulation models are usually used together by forecasters to generate the final forecast. However, it is difficult for forecasters to obtain a clear view of all the data due to its complexity. This has been a great limitation for domain experts to take advantage of all the data in their routine work. In order to help explore the multi-variate and multi-model data, we propose a stamp based exploration framework to assist domain experts in analyzing the data. The framework is used to assist domain experts in detecting the bias patterns between numerical simulation data and observation data. The exploration pipeline originates from a single meteorological variable and extends to multiple variables under the guidance of a designed stamp board. Regional data patterns can be detected by analyzing distinctive stamps on the board or generating extending stamps using the Boolean set operations. Experiment results show that some meteorological phenomena and regional data patterns can be easily detected through the exploration. These can help domain experts conduct the data analysis efficiently and further guide forecasters in producing reliable weather forecast.     

应用架构技术设计与开发电子商务系统

目前,Struts,Spring,Hibernate作为轻量级的企业计算方案已渐渐被业界所接受.通过一个校园内区域化电子商务平台的研发,充分说明了这些架构技术的优点.对Struts Spring Hibernate架构下电子商务系统的技术实现进行了详细说明,并给出了相关构造功能描述和部分核心代码及其说明.经现场运行表明,所用技术的新特性提高了实际系统的安全性和稳定性.该架构不但使资源得到最大限度的节省和利用,也使得项目开发简洁.结构清晰,并且具备了更好的可扩展性和可维护性.     

基于构件模型的系统框架设计研究

研究利用Web Service技术思想和构件的强装拆性思想,将可复用的、基于构件的应用系统框架同内部的业务构件实现分离开来,研究目的是提高系统框架的可复用性.给出了一种对构件概念模型的定义,并命名为EC构件,同时定义了系统内部标准的构件概念模型;在分析基于构件的系统框架同构件模型之间关系的基础上,证明利用该系统框架可以实现构件的管理和互操作,从而使系统具有良好的可移植性、可复用性和可维护性.     

基于计算机视觉的数字刀具测量系统研究

刀具的几何参数是影响数控机床加工精度和生产效率的重要因素。研究了基于计算机视觉检测技术的高精度刀具测量系统,分析了运行原理和功能模块,对关键技术做了论述。系统实现了对刀具的刀尖切削特征点、圆弧半径和切削角参数的自动精确测量,并将数值反馈到数控机床刀具数据库,具有较高的效率、精度和自动化程度。实验结果证明,系统测量重复性精度可达3μm。     

A data-based approach for multivariate model predictive control performance monitoring

An intelligent statistical approach is proposed for monitoring the performance of multivariate model predictive control (MPC) controller, which systematically integrates both the assessment and diagnosis procedures. Model predictive error is included into the monitored variable set and a 2-norm based covariance benchmark is presented. By comparing the data of a monitored operational period with the “golden” user-predefined one, this method can properly evaluate the performance of an MPC controller at the monitored operational stage. Characteristic direction information is mined from the operating data and the corresponding classes are built. The eigenvector angle is defined to describe the similarity between the current data set and the established classes, and an angle-based classifier is introduced to identify the root cause of MPC performance degradation when a poor performance is detected. The effectiveness of the proposed methodology is demonstrated in a case study of the Wood-Berry distillation column system.     

A general framework for 3D model co-alignment

3D model alignment is a fundamental step in many shape analysis processes, and various algorithms have been proposed to solve this problem. However, to the best of our knowledge, they are effective only on specific categories of models. Therefore, we present a novel framework that can align general categories by combining different features together. In order to align given groups of models, multiple features are evaluated first in this framework, according to three types of quantified characteristics, i.e., the intensity, the uniqueness and the consistency. Then, the quantified characteristics are combined into scores and a data-driven model is learned to predict the alignment errors according to the scores. Finally, the features with the minimum predicted alignment errors are selected to align the given groups. Experimental results show that our framework can generate consistent alignments on general categories, which are much better than those generated using single features.     

A framework for automatic DFA system development

Deisgn for assembly (DFA) evaluation has proved to be a systematic approach is determining how well a product is designed from an assembly point of view. Proposed here is a framework for automating DFA evaluation procedure, a key step in achieving a concurrent design environment. Five modules required for this development are: assembly sequence generation; assembly features extraction; assembly code and other necessary operations generation; data manipulation and computation; and re-design suggestion. Partial implementation (linking DFA evaluation procedure with a feature based CAD system) of the framework is also presented.