A novel pose invariant 3D dental biometrics framework is proposed for human identification by matching dental plasters in this paper. Using 3D overcomes a number of key problems that plague 2D methods. As best as we can tell, our study is the first attempt at 3D dental biometrics. It includes a multi-scale feature extraction algorithm for extracting pose invariant feature points and a triplet-correspondence algorithm for pose estimation. Preliminary experimental result achieves 100% rank-1 accuracy by matching 7 postmortem (PM) samples against 100 ante-mortem (AM) samples. In addition, towards a fully automated 3D dental identification testing, the accuracy achieves 71.4% at rank-1 accuracy and 100% at rank-4 accuracy. Comparing with the existing algorithms, the feature point extraction algorithm and the triplet-correspondence algorithm are faster and more robust for pose estimation. In addition, the retrieval time for a single subject has been significantly reduced. Furthermore, we discover that the investigated dental features are discriminative and useful for identification. The high accuracy, fast retrieval speed and the facilitated identification process suggest that the developed 3D framework is more suitable for practical use in dental biometrics applications in the future. Finally, the limitations and future research directions are discussed.

This paper presents a model-based monitoring and failure detection approach in ball-nose end milling process. A mechanistic force model has been established for high speed milling on hardened stavax steel with 6 mm micro-grain tungsten carbide 2 flute ball-nose end mill. The threshold curve can be obtained off-line based on the process model as the cutting engagement conditions along the tool path are determined at the simulation stage. The measured cutting forces are monitored on-line to detect the faults by comparing them with the threshold curve at machining stage. If a fault is detected at certain position along the tool path, an intelligent predictive method is utilized to predict whether this fault will result in catastrophic failure. Experimental results are provided to demonstrate the feasibility of this approach.

This paper discusses the effect of geometric shape on the accuracy of direct metal laser sintering (DMLS) prototypes. The percentage shrinkages due to different shapes are investigated and their empirical relationship is determined. A new speed-compensation (SC) method is proposed to reduce uneven shrinkage affected by the two-dimensional geometric shape at each layer. From case studies conducted, the optimized SC method is found to be efficient in improving the accuracy of prototypes fabricated. Note to Practitioners-This paper aims to address the problem of dimensional errors of parts built by the direct metal laser sintering (DMLS) process. Existing compensation approaches are normally based on a general relationship between the nominal dimensions and the errors after sintering. However, the effect arising from different geometric shapes is not considered. A new approach is proposed using different scan speed settings to compensate for the effect of geometric shapes to improve the dimensional accuracy of the entire part. During processing, the laser sinters along the trajectory are guided by the hatch vectors or dexel. An appropriate experimental method is used to establish the relationship for different scan speeds with the dexel length to the final accuracy. When building the part, the laser scan speed is adjusted dynamically according to the dexel length which varies with the geometric shape of the part. The case study demonstrates that the proposed method can generate correct speed settings to effectively increase the dimensional accuracy of the final part. Although this method has been developed based on the DMLS process, it is also applicable to other laser sintering processes. In future research, other process parameters, such as laser power, will be considered independently, or together with the scan speed, for possible further improvement on the dimensional accuracy.

Large companies are looking for information and communication technology to manage their resources, and also expect partners, including suppliers, to quickly adopt appropriate technologies and business strategies. The mould industry is an important support industry during the product development process, and a link, between product designers and manufacturers. The paper presents a collaborative application portal (CAP) for mould industry to provide an application platform for collaborative product design, product data management, manufacturing information management and e-business services. A multi-tiers architecture and some pivotal technologies including of MVC development mode, information exchange, user management and security for portal, are used to construct this portal. Supporting collaborative activities between mould companies and its customers, suppliers and partners are illustrated. A portal of mould industry in Singapore, www.diemoldonline.net, is introduced as an application case.

In this paper, a new hybrid of genetic algorithm (GA) and simulated annealing (SA), referred to as GSA, is presented. In this algorithm, SA is incorporated into GA to escape from the local optima. Then, the idea of hierarchical parallel GA is borrowed to parallelize GSA for the optimization of multimodal functions. In addition, multi-niche crowding is used to maintain the diversity in the population of parallel GSA. The performance of the proposed algorithms is evaluated against a standard set of multimodal benchmark functions. Multi-niche crowding PGSA and normal PGSA show some remarkable improvement in comparison with the conventional parallel GA and the breeder genetic algorithm.

The factors that generally affect the slicing error in layered manufacturing (LM) processes are first analyzed, and issues pertaining to the current methods to deal with the slicing error are discussed in this paper. A method based on a recently developed and implemented orthogonal LM system to reduce the overall slicing error is presented. In this method, the flat region is separated from the stereolithography (STL) model and different processing methods are applied to the different areas in the part geometry. In addition, the mathematical model for calculating the slicing error is derived and an approach based on a genetic algorithm has been developed to optimize the build orientation in terms of minimizing the slicing error. Case studies are given to demonstrate the effectiveness and efficiency of the method. Note to Practitioner-The staircase effect has been the major concern for industry to widely adopt rapid prototyping technologies. It will not only worsen the surface quality but also create errors on the parts built. This paper introduces a novel approach to minimizing staircase errors based on a multidirectional deposition approach. A mathematical method combined with a generic algorithm is used to minimize the slicing errors. From the case study given, the approach has been proven to be effective in minimizing staircase errors and thus improving the rapid prototyping (RP) built part quality.

Global market today demands rapid introduction of products while maintaining high quality and minimal costs. To accomplish the goals in a timely and efficient manner, companies are considering the power of collaboration across the product lifecycle. This paper proposes a fuzzy decision guided method to optimize the component supplier selection in a dynamic collaborative environment. An objective function is advanced to formalize the component supplier selection problem. Fuzzy factors, fuzzy decision of the selection and their relations are analyzed. A fuzzy decisions based optimization algorithm is developed to select a set of suppliers that can provide the components at low prices and in time.

The paper presents the development of an enterprise application using distributed object technology that integrates material requirements planning (MRP) to a job shop (simulator). The application aims to realize an integrated system that responds rapidly to changing requirements and is able to integrate heterogeneous manufacturing facilities. The application accepts the customer's order and performs material requirements planning. The MRP system then sends daily planned orders to a job shop that carries out real-time scheduling and production. At the same time, orders are sent to suppliers to purchase raw materials. After completing the production task, the job shop returns the relevant information about the finished parts. Once the customer adds or modifies orders, the MRP system will update pertinent data automatically to respond to the changes in customer's requirements rapidly. The Unified Modeling Language (UML) is applied for the analysis and design of the total application. In this integrated application, the MRP system uses Enterprise Java Beans (EJB) that are deployed in a J2EE compliant application server to perform business-to-customer transactions and MRP logic. The job shop system uses Common Object Request Broker Architecture (CORBA) specification as communication platform.

This paper presents an off-line simulation approach that aims to provide a model-based online control of a proposed intelligent fixturing system. The intelligent fixturing system is to adaptively adjust the clamping forces to optimal values during the machining process. Using the off-line simulation, an analytical fixture-workpiece model and an optimization method have been developed for the control of a fixturing system. This simulation can also be applied to evaluate the performance of a fixturing system and determine optimal clamping forces for a given fixture configuration. Experiments have been conducted to verify the proposed model. The fixturing system can be applied in a high-precision machining environment where the workpiece deformation due to over-clamping and improper machining is a major concern.