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ABSTRACT: This paper presents a knowledge-based customization system (KBCS) which provides an indispensable tool for the customization and integration of various manufacturing enterprise applications. Business processes and business objects are standardized and packaged into components with the object technology. All components are deployed independently to one another using the object-oriented modeling method. With the aid of the artificial intelligence technique in component selections and integration, the users can generically and rapidly customize their enterprise applications that best fit the business process flow of the enterprise by configuration of those required components only. Therefore, the time and the cost needed for developing complex enterprise applications can be significantly reduced. The capability of the KBCS has been evaluated through a trial implementation in a selected reference site and satisfactory results are obtained.
Expert Systems with Applications.
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ABSTRACT: The fabrication of high-quality freeform surfaces is based on ultra-precision raster milling, which allows direct machining of the freeform surfaces with sub-micrometric form accuracy and nanometric surface finish. Ultra-precision raster milling is an emerging manufacturing technology for the fabrication of high-precision and high-quality components with a surface roughness of less than 10 nm and a form error of less than 0.2 μm without the need for any additional post-processing. Moreover, the quality of a raster milled surface is based on a proper selection of cutting conditions and cutting strategies.Due to different cutting mechanics, the process factors affecting the surface quality are more complicated, as compared with ultra-precision diamond turning and conventional milling, such as swing distance and step distance. This paper presents a theoretical and experimental analysis of nano-surface generation in ultra-precision raster milling. Theoretical models for the prediction of surface roughness are built. An optimization system is established based on the theoretical models for the optimization of cutting conditions and cutting strategy in ultra-precision raster milling. A series of experiments have conducted and the results show that the theoretical models predict well the trend of the variation of surface roughness under different cutting conditions and cutting strategies.
International Journal of Machine Tools and Manufacture.
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ABSTRACT: Concept maps have been widely put to educational uses. They possess a number of appealing features which make them a promising tool for teaching, learning, evaluation, and curriculum planning. This paper presents self-associated concept mapping (SACM) which extends the use of concept mapping by proposing the idea of self-construction and automatic problem solving to traditional concept maps. The SACM can be automatically constructed and dynamic updated. A Constrained Fuzzy Spreading Activation (CFSA) model is proposed to SACM for supporting rapid and automatic decisions. With the successful development of the SACM, the capability of Knowledge-based systems (KBS) can be enhanced. The concept and operational feasibility of the SACM is realized through a case study in a consultancy business. The theoretical results are found to agree well with the experimental results.
Knowledge-Based Systems.
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ABSTRACT: Optical microstructures have a small scale topography classified as micro-grooves, microlens arrays, pyramids, lenticulations, etc. They are widely applied in optical components such as light guide panels for electronic displays. Most previous research work focuses on either the characterization of individual scale topography, or the optical performance of optical microstructures. There is a lack of surface characterization methods which are capable of characterizing the surface generation in terms of the form errors and the lattice relationships in the small scale topography of optical microstructures with sub-micrometer accuracy.This paper presents a pattern and feature parametric analysis method (PFPAM) for the characterization of the surface generation of optical microstructures. The method includes data acquisition, data processing and pattern analysis, exploration of and analysis of feature parameters, etc. Digital image processing technology has been employed and a series of lattice dislocation parameters have been developed to characterize the features of the distribution and the dislocation of optical microstructures. To verify the PFPAM, a prototype surface characterization system has been built. A series of cutting and measurement experiments have been conducted on microlens arrays and titled flats using a two-axis ultra-precision machining system equipped with Fast Tool Servo (FTS) and examined by a non-contact micro-surface profiler system. The results demonstrate that the PFPAM provides an adequate basis for good form characterization of optical microstructures, with form accuracy down to below sub-micrometer range. The proposed lattice dislocation parameters are shown to be useful for the characterization of the distribution and dislocation features in the small scale topography of the optical microstructures. This is not possible using traditional methods. Potential applications of the PFPAM for quality control and evaluation of optical microstructures are discussed.
Precision Engineering.
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ABSTRACT: Taxonomy construction is a resource-demanding, top–down, and time consuming effort. It does not always cater for the prevailing context of the captured information. This paper proposes a novel approach to automatically convert tags into a hierarchical taxonomy. Folksonomy describes the process by which many users add metadata in the form of keywords or tags to shared content. Using folksonomy as a knowledge source for nominating tags, the proposed method first converts the tags into a hierarchy. This serves to harness a core set of taxonomy terms; the generated hierarchical structure facilitates users’ information navigation behavior and permits personalizations. Newly acquired tags are then progressively integrated into a taxonomy in a largely automated way to complete the taxonomy creation process. Common taxonomy construction techniques are based on 3 main approaches: clustering, lexico-syntactic pattern matching, and automatic acquisition from machine-readable dictionaries. In contrast to these prevailing approaches, this paper proposes a taxonomy construction analysis based on heuristic rules and deep syntactic analysis. The proposed method requires only a relatively small corpus to create a preliminary taxonomy. The approach has been evaluated using an expert-defined taxonomy in the environmental protection domain and encouraging results were yielded.
Information Processing & Management.
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ABSTRACT: Ultra-precision freeform surfaces are complex surfaces that possess non-rotational symmetry. Currently, there is a lack of definitive international standards and techniques for the characterization of form accuracy and surface quality of ultra-precision freeform surfaces. This paper presents an integrated form characterization method (IFCM) to measure the form accuracy of ultra-precision freeform surfaces. The IFCM is developed based on the five-point pre-fixture, dual cubic B-spline and an iterative precision adjustment algorithm with coordinate transfer. To verify the capability of the proposed method, a series of computer simulation and measurement experiments were undertaken. The results indicate that the IFCM can realize the precise alignment of measured and normal surfaces with accuracy in nanometer range which provides adequate base for good form characterization of ultra-precision freeform surfaces with form accuracy down to below sub-micrometer range.
International Journal of Machine Tools and Manufacture.
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ABSTRACT: Many multi-national companies have operations in geographically different locations. They need to communicate and work concurrently on large amount of complex product data with their factories, sub-contractors as well as suppliers across the border. The use of e-mail and fax are far from satisfactory as they are time consuming and ineffective. In this paper, a web-based collaborative product design platform is proposed which enables authorized users in geographically different locations to have access to the company’s product data such as product drawing files stored at designated servers and carry out product design work simultaneously and collaboratively on any operating systems. There is no need for the users to install any utility software at their ends since the access is based on a remote screen sharing technique built upon a Browser/Server and thin client technology. This results in substantial saving in the cost and the product development time in a network environment.
Journal of Materials Processing Technology.
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ABSTRACT: Virtual manufacturing (VM) which primarily aimed at reducing the lead times and costs associated with new product development offers a test-bed for the time-consuming and expensive physical experimentation. In this paper, a comprehensive architecture of test-bed for machining and errors prediction—Virtual Machining and Measuring Cell (VMMC) is built which can simulate the machining process, measuring process, predict the machining errors and so on. In VMMC, errors existed inevitably in machining are modeled and incorporated in the workpiece model (hence virtual workpiece) during Machining Process Simulation (MPS); then the topography of the machined surfaces of the virtual workpiece is constructed and measuring process is simulated to predict machining errors and surface roughness in virtual measuring. The output of VMMC provides a theoretical basis for optimization of machining conditions and error compensation. As a result, higher machining accuracy and development agility of a product can be achieved. The associated techniques related to develop VMMC are highlighted and practical examples of VMMC are also presented.
Computers in Industry.
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ABSTRACT: Materials induced vibration has its origin in the variation of micro-cutting forces caused by the changing crystallographic orientation of the material being cut. It is a kind of self-excited vibration which is inherent in a cutting system for crystalline materials. The captioned vibration results in a local variation of surface roughness of a diamond turned surface. In this paper, a dynamic surface topography model is proposed to predict the materials induced vibration and its effect on the surface generation in ultra-precision machining. The model takes into account the effect of machining parameters, the tool geometry, the relative tool–work motion as well as the crystallographic orientation of the materials being cut. A series of cutting experiments was performed to verify the performance of the model and good correlation has been found between the experimental and simulation results.
International Journal of Mechanical Sciences.
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ABSTRACT: This paper describes a framework of a virtual machining and inspection system (VMIS) for the diamond turning of precision optics. The development of the VMIS aims at creating a virtual manufacturing (VM) environment for the design, manufacture and inspection of precision optics through various model-based simulation modules. Basically, the VMIS consists of six building blocks which include the information module (IM), optics design and optimisation module (ODOM), virtual machining module (VMM), virtual inspection module (VIM), analysis and decision-making module (ADMM), and performance evaluation and monitoring module (PEMM). In this paper, the concept, the theoretical basis and the underlying assumptions in the development and implementation of each module are outlined. Preliminary experimental and simulation work together with the future development of the system are also discussed.
Journal of Materials Processing Technology.
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ABSTRACT: Acquisition of knowledge must be interwoven with the process of applying it. However, traditional training methods which provide abstract knowledge have shown ineffective for gaining experience of the work. In order to solve this problem, more and more researchers have included narrative in simulation, which is known as narrative simulation. By providing the narratives, participants recognize the choices, decisions, and experience that lead to the consequences of those decisions. It has been proven that narrative simulation is very useful in facilitating in-depth learning and reflective learning. However, conventional methods of data collection and narrative construction for narrative simulation are labor intensive and time consuming. They make use of previous narratives manually and directly. They are inadequate to cope with the fast moving world where knowledge is changing rapidly. In order to provide a way for facilitating the construction of narrative simulation, a novel computational narrative construction method is proposed. By incorporating technologies of knowledge-based system (KBS), computational linguistics, and artificial intelligence (AI), the proposed method provides an efficient and effective way for collecting narratives and automating the construction of narratives. The method converts the unstructured narratives into a structural representation for abstraction and facilitating computing processing. Moreover, it constructs the narratives that combine multiple narratives into a single narrative by applying a forecasting algorithm. The proposed method was successfully implemented in early intervention in mental health care of a social service company in Hong Kong since the case records in that process have structural similarities to narrative. The accuracies of data conversion and predictive function were measured based on recall and precision and encouraging results were obtained. High recall and precision are achieved in the data conversion function, and high recall for the predictive function when new concepts are excluded. The results show that it is possible for converting multiple narratives into a single narrative automatically. Based on the approach, it helps to stimulate knowledge workers to explore new problem solving methods so as to increase the quality of their solutions.
Expert Systems with Applications.
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ABSTRACT: Microlens array (MLA) is a type of structured freeform surfaces which are widely used in advanced optical products. Fast tool servo (FTS) machining provides an indispensible solution for machining MLA with superior surface quality than traditional fabrication process for MLA. However, there are a lot of challenges in the characterization of the surface defects in FTS machining of MLA. This paper presents a pattern recognition and analysis method (PRAM) for the characterization of surface defects in FTS machining of MLA. The PRAM makes use of the Gabor filters to extract the features from the MLA. These features are used to train a Support Vector Machine (SVM) classifier for defects detection and analysis. To verify the method, a series of experiments have been conducted and the results show that the PRAM produces good accuracy of defects detection using different features and different classifiers. The successful development of PRAM throws some light on further study of surface characterization of other types of structure freeform surfaces.
Measurement.
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ABSTRACT: Natural Language Processing (NLP) techniques have been successfully used to automatically extract information from unstructured text through a detailed analysis of their content, often to satisfy particular information needs. In this paper, an automatic concept map construction technique, Fuzzy Association Concept Mapping (FACM), is proposed for the conversion of abstracted short texts into concept maps. The approach consists of a linguistic module and a recommendation module. The linguistic module is a text mining method that does not require the use to have any prior knowledge about using NLP techniques. It incorporates rule-based reasoning (RBR) and case based reasoning (CBR) for anaphoric resolution. It aims at extracting the propositions in text so as to construct a concept map automatically. The recommendation module is arrived at by adopting fuzzy set theories. It is an interactive process which provides suggestions of propositions for further human refinement of the automatically generated concept maps. The suggested propositions are relationships among the concepts which are not explicitly found in the paragraphs. This technique helps to stimulate individual reflection and generate new knowledge. Evaluation was carried out by using the Science Citation Index (SCI) abstract database and CNET News as test data, which are well known databases and the quality of the text is assured. Experimental results show that the automatically generated concept maps conform to the outputs generated manually by domain experts, since the degree of difference between them is proportionally small. The method provides users with the ability to convert scientific and short texts into a structured format which can be easily processed by computer. Moreover, it provides knowledge workers with extra time to re-think their written text and to view their knowledge from another angle.
Information Processing & Management.
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ABSTRACT: The e-business arena is a dynamic, complex and demanding environment. It is essential to make optimal reuse of knowledge of customer services across various functional units of the enterprise. On the other hand, it is also important to ensure that the customer service staff can access and be trained up with dynamically updated knowledge that meets the changing business environment of an enterprise in customer services. However, conventional way of customer service management (CSM) is inadequate to achieve the multi-perspective of an enterprise for achieving knowledge acquisition, knowledge diffusion, business automation and business performance measurement so as to drive the continuous improvement of the customer service quality. In this paper, a multi-perspective knowledge-based system (MPKBS) is proposed for CSM. The MPKBS incorporates various artificial intelligence technologies such as case-based reasoning (CBR) and adaptive time-series model which are used for decision analysis, performance measurement and monitoring. A prototype customer service portal has been built based on the MPKBS and implemented successfully in a consultancy business.
Expert Systems with Applications.
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ABSTRACT: This paper presents an investigation of the effect of materials swelling in ultra-precision machining of ductile materials. The combined influence of materials swelling and recovery was found to affect the surface roughness in single-point diamond turning. It is interesting to note that the effect of materials swelling for ductile materials would be overwhelmed by the impact of recovery when the depth of cut is extremely small and the front clearance is small. In addition, radically different surface roughness profiles were found for different materials even though they are machined under the same cutting conditions. The difference in the machining behaviour could not be accounted by the elastic recovery alone but by the plastic deformation induced in the machined layer. The findings in the present study provide an important means for improving the surface roughness in ultra-precision machining.
Journal of Materials Processing Technology.
