Bicriteria robotic operation allocation in a flexible manufacturing cell

Consider a manufacturing cell of two identical CNC machines and a material handling robot. Identical parts requesting the completion of a number of operations are to be produced in a cyclic scheduling environment through a flow shop type setting. The existing studies in the literature overlook the flexibility of the CNC machines by assuming that both the allocation of the operations to the machines as well as their respective processing times are fixed. Consequently, the provided results may be either suboptimal or valid under unnecessarily limiting assumptions for a flexible manufacturing cell. The allocations of the operations to the two machines and the processing time of an operation on a machine can be changed by altering the machining conditions of that machine such as the speed and the feed rate in a CNC turning machine. Such flexibilities constitute the point of origin of the current study. The allocation of the operations to the machines and the machining conditions of the machines affect the processing times which, in turn, affect the cycle time. On the other hand, the machining conditions also affect the manufacturing cost. This study is the first to consider a bicriteria model which determines the allocation of the operations to the machines, the processing times of the operations on the machines, and the robot move sequence that jointly minimize the cycle time and the total manufacturing cost. We provide algorithms for the two 1-unit cycles and test their efficiency in terms of the solution quality and the computation time by a wide range of experiments on varying design parameters.     

Throughput optimization in two-machine flowshops with flexible operations

In this study, a two-machine flowshop producing identical parts is considered. Each of the identical parts is assumed to require a number of manufacturing operations, and the machines are assumed to be flexible enough to perform different operations. Due to economical or technological constraints, some specific operations are preassigned to one of the machines. The remaining operations, called flexible operations, can be performed on either one of the machines, so that the same flexible operation can be performed on different machines for different parts. The problem is to determine the assignment of the flexible operations to the machines for each part, with the objective of maximizing the throughput rate. We consider various cases regarding the number of parts to be produced and the capacity of the buffer between the machines. We present solution methods for each variant of the problem.     

A gantry-based tri-modality system for bioluminescence tomography

A gantry-based tri-modality system that combines bioluminescence (BLT), diffuse optical (DOT), and x-ray computed tomography (XCT) into the same setting is presented here. The purpose of this system is to perform bioluminescence tomography using a multi-modality imaging approach. As parts of this hybrid system, XCT and DOT provide anatomical information and background optical property maps. This structural and functional a priori information is used to guide and restrain bioluminescence reconstruction algorithm and ultimately improve the BLT results. The performance of the combined system is evaluated using multi-modality phantoms. In particular, a cylindrical heterogeneous multi-modality phantom that contains regions with higher optical absorption and x-ray attenuation is constructed. We showed that a 1.5 mm diameter bioluminescence inclusion can be localized accurately with the functional a priori information while its source strength can be recovered more accurately using both structural and the functional a priori information.     

Effect of TiO<Subscript>2</Subscript> addition on crystallization and machinability of potassium mica and fluorapatite glass ceramics

In this study, the effect of TiO₂ addition as a nucleating agent on the crystallization and machinability of potassium mica and fluorapatite base glass ceramics were investigated. Glass compositions were prepared and casted at predetermined temperatures. Differential thermal analysis and XRD methods were applied to characterize phase precipitation sequence and identification of phases. Disc and cylindrical shaped samples were prepared to determine microstructural and mechanical properties in terms of microhardness and machinability. FEG-SEM was used to characterize variation of microstructural constituents depending on the amount of nucleating agent. The results indicate that optimum microstructure and machinability can be obtained in machinable glass-ceramic by the addition of 1 wt% TiO₂ for the composition having 3:7 weight ratio of fluorapatite to potassium mica.     

Microstructure and densification of ZrB2–SiC composites prepared by spark plasma sintering

ZrB₂–SiC composites were prepared by spark plasma sintering (SPS) at temperatures of 1800–2100 °C for 180–300 s under a pressure of 20 MPa and at higher temperatures of above 2100 °C without a holding time under 10 MPa. Densification, microstructure and mechanical properties of ZrB₂–SiC composites were investigated. Fully dense ZrB₂–SiC composites containing 20–60 mass% SiC with a relative density of more than 99% were obtained at 2000 and 2100 °C for 180 s. Below 2120 °C, microstructures consisted of equiaxed ZrB₂ grains with a size of 2–5 μm and α-SiC grains with a size of 2–4 μm. Morphological change from equiaxed to elongated α-SiC grains was observed at higher temperatures. Vickers hardness of ZrB₂–SiC composites increased with increasing sintering temperature and SiC content up to 60 mass%, and ZrB₂–SiC composite containing 60 mass% SiC sintered at 2100 °C for 180 s had the highest value of 26.8 GPa. The highest fracture toughness was observed for ZrB₂–SiC composites containing 50 mass% SiC independent of sintering temperatures.     

Experimental determination of effective moisture diffusivities of whole- and cut-rosehips in convective drying

Average effective moisture diffusivities for both the whole- and cut-rosehips were obtained during convective drying. The effects of process variables such as air temperature, air velocity and air absolute humidity on effective moisture diffusivity were studied. The average effective moisture diffusivity in rosehip ranged between 1.45 × 10^?10 and 10.3 × 10^?10 m²/s for whole-rosehip and between 1.44 × 10^?9 and 5.13 × 10^?9 m²/s for cut-rosehip at the temperatures studied. Activation energies for convective drying were found to be 62 kJ/mol for whole-rosehips and 58 kJ/mol for cut-rosehips.     

Wear and friction behavior of metal impregnated microporous carbon composites

Metal-matrix composites have been prepared by pressure-infiltration casting of copper-base alloy melts into microporous carbon preforms. The carbon preforms contained varying proportions of amorphous carbon and graphite. Load dependence of the wear and friction behavior of the composite pins has been examined under ambient conditions against cast-iron plates, using a pin-on-plate reciprocating wear tester. The wear resistance of the composite is significantly improved, as compared with the base alloy. Contrary to the normally expected behavior, the addition of graphite to the amorphous carbon does not reduce the friction coefficient, especially at high loads. The wear and friction behavior of the composites is very sensitive to the size and distribution of the microstructural constituents.     

Design and implementation of a semantic query optimizer

The authors describe a scheme to utilize semantic knowledge in optimizing a user-specified query. The semantics is represented as function-free clauses in predicate logic. The scheme uses a graph-theoretic approach to identify redundant joins and restrictions present in a given query while adding additional profitable specifications to it. Dynamic and heuristic interaction of three entities-schema, semantics, and query-forms the basis of the algorithm. The implementation architecture of the algorithm and test results on a representative set of data are presented. Issues associated with updating of semantic constraints are addressed, and an algorithm for semantic maintenance is introduced     

Implication and referential constraints: a new formal reasoning

The authors address the issue of reasoning with two classes of commonly used semantic integrity constraints in database and knowledge-base systems: implication constraints and referential constraints. They first consider a central problem in this respect, the IRC-refuting problem, which is to decide whether a conjunctive query always produces an empty relation on (finite) database instances satisfying a given set of implication and referential constraints. Since the general problem is undecidable, they only consider acyclic referential constraints. Under this assumption, they prove that the IRC-refuting problem is decidable, and give a novel necessary and sufficient condition for it. Under the same assumption, they also study several other problems encountered in semantic query optimization, such as the semantics-based query containment problem, redundant join problem, and redundant selection-condition problem, and show that they are polynomially equivalent or reducible to the IRC-refuting problem. Moreover, they give results on reducing the complexity for some special cases of the IRC-refuting problem     

Neural Models for the Resonant Frequency of Electrically Thin and Thick Circular Microstrip Antennas and the Characteristic Parameters of Asymmetric Coplanar Waveguides Backed with a Conductor

Neural models for computing the resonant frequency of electrically thin and thick circular microstrip antennas, based on the multilayered perceptrons and the radial basis function networks, are presented. Five learning algorithms, delta-bar-delta, extended delta-bar-delta, quick-propagation, directed random search and genetic algorithms, are used to train the multilayered perceptrons. The radial basis function network is trained according to its learning strategy. The resonant frequency results of neural models are in very good agreement with the experimental results available in the literature. In this paper, the characteristic impedance and the effective permittivity of the asymmetric coplanar waveguide backed with a conductor are also computed by using only one neural model trained by the backpropagation with momentum and the extended delta-bar-delta algorithms. When the performances of neural models are compared with each other, the best results for test are obtained from the multilayered perceptrons trained by the extended delta-bar-delta algorithm.