Crafting large prototypes

Contour crafting utilizes computer-aided ancient sculpting techniques for fabrication of large components. The article presents the essentials of the contour crafting process, the status of research and development of the process, experiments with thermoplastics and ceramics materials, engineering analysis of certain aspects of the technology, and its potential application areas     

On-line application of microprocessors in quality control

A system is described that collects data and computes and plots control charts and sampling plans automatically. An inspection device is connected with a microcomputer to measure a physical characteristics of a product, transmit data to the computer and process and store summary statistics. The software accepts preliminary measurements, computes control limits, accepts further measurements, plots them on a CRT or plotter and stops the process when an out-of-control measurement is detected. The software will also determine a single-sampling plan which meets specified producer's and consumer's risks, measures products to determine if acceptable and will report decisions on lot acceptance.     

A framework for artificial intelligence applications software development

Despite the promise and prominence of artificial intelligence, successful widely-based applications have been rare. Much of previous artificial intelligence work has concentrated on the demonstration of techniques rather than the development of tools that can be used in systems design, analysis and operation. A systematic program of knowledge compilation in artificial intelligence is proposed where extensible function libraries can be used by professionals in various fields and non-programming specialists in developing artificial intelligence applications.     

Automated inspection in robotic additive manufacturing using deep learning for layer deformation detection

Journal of Intelligent Manufacturing - In this paper, an automated layer defect detection system for construction 3D printing is proposed. Initially, a step-by-step procedure is implemented to...     

Automating identification of services and their variability for product lines using NSGA-II

Architecture-level business services are identified based on business processes; and likewise, in service-oriented product lines, identifying the domain architecture-level business services and their variability is preferred to be based on business processes and their variability. Identification of business services for a product line satisfying a set of given design metrics (such as cohesion and coupling) is extremely difficult for a domain architect, since there are many product configurations for which the services must be proper at the same time. This means that the identified services must have proper values for n metrics in m different configurations at the same time. The problem becomes more serious when there are high degrees of variability and complexity embedded in the business processes that are the basis for service identification.We contribute to solve the multi-objective optimization problem of identifying business services for a product line by partitioning the graph of a business process variability model utilizing Non-dominated Sorting Genetic Algorithm-II. The service specification is achieved based on the results of the partitioning. The variability of the services is then determined in terms of mandatory and optional services as well as variability relationships, which are all represented in a Service Variability Model. The method was empirically evaluated through experimentation, and showed proper levels of reusability and variability. Furthermore, the resulting models were fully consistent.     

Opportunistic Spectral Usage: Bounds and a Multi-Band CSMA/CA Protocol

In this paper, we study the gains from opportunistic spectrum usage when neither sender or receiver are aware of the current channel conditions in different frequency bands. Hence to select the best band for sending data, nodes first need to measure the channel in different bands which takes time away from sending actual data. We analyze the gains from opportunistic band selection by deriving an optimal skipping rule, which balances the throughput gain from finding a good quality band with the overhead of measuring multiple bands. We show that opportunistic band skipping is most beneficial in low signal to noise scenarios, which are typically the cases when the node throughput in single-band (no opportunism) system is the minimum. To study the impact of opportunism on network throughput, we devise a CSMA/CA protocol, multi-band opportunistic auto rate (MOAR), which implements the proposed skipping rule on a per node pair basis. The proposed protocol exploits both time and frequency diversity, and is shown to result in typical throughput gains of 20% or more over a protocol which only exploits time diversity, opportunistic auto rate (OAR).     

Investigation on the determination of flow direction using two parallel cylindrical hot film sensors

Measurement of instantaneous air flow velocity with high frequency can be carried out by using a hot wire anemometer (HWA). HWA works on the basis of heat transfer rate from hot wire to the fluid flow, therefore directional identification of the air flow using hot wire anemometer is a difficult task. By using two parallel cylindrical hot film sensors a probe was built. By considering the wake and heat effect of the upstream sensor on the downstream sensor, direction of the air flow can be identified. In this work, the wake and heat effect resulting from the upstream sensor to the velocity measurement, by the downstream sensor was studied. This measured velocity is dependent of the following factors namely; air velocity, upstream sensor overheat ratio, distance between the two sensors and turbulence intensity of the flow. As a result it was found that the manufactured probe with sensor distance of 1 mm apart is capable of measuring reverse flow measurements of up to 20 m/s for a moderate turbulent flow.     

A linearized polynomial mixed integer programming model for the integration of process planning and scheduling

This paper presents a linearized polynomial mixed-integer programming model (PMIPM) for the integration of process planning and scheduling problem. First, the integration problem is modeled as a PMIPM in which some of the terms are of products of up to three variables, of both binary and continuous in nature. Then, an equivalent linearized model is derived from the polynomial model by applying certain linearization techniques. Although the linearized models have more variables and constraints than their polynomial counterparts, they are potentially solvable to the optimum in comparison to their equivalent polynomial models. Experiments show that the linearized model possesses certain characteristics that are absent from other models in the literature, and provides a fundamental framework for further research in this area.     

Development of a Rapid Prototyping System using Response Surface Methodology

This case study presents an investigation of the relationships between eight process operating variables (factors) and five part performance measures (responses) in a rapid prototyping system. The use of fractional factorial, single‐factor foldover, and central composite designs is demonstrated. Polynomial regression models are constructed for each response, followed by a desirability function model. Canonical and ridge analyses are used to identify a group of factor settings that simultaneously produce improved performance for all responses. Copyright © 2006 John Wiley & Sons, Ltd.