Real-time tool control and job dispatching in flexible manufacturing systems

A method of loading a set of tools to the different machining centres of a shop is presented, where each part visits only one of the machining centres for its entire processing. Any tools which are required but unavailable for the processing of a part are borrowed from other machining centres. As a real-time control, the tool-returning policies for those borrowed tools and the job-dispatching rules at the machining centres are evaluated to maximize the throughput performance of the shop. Some experimental results are provided.     

Generating interpretable fuzzy rules for adaptive job dispatching

Adaptive scheduling is an approach that selects and applies the most suitable strategy considering the current state of the system. The performance of an adaptive scheduling system relies on the effectiveness of the mapping knowledge between system states and the best rules in the states. This study proposes a new fuzzy adaptive scheduling method and an automated knowledge acquisition method to acquire and continuously update the required knowledge. In this method, the criteria for scheduling priority are selected to correspond to the performance measures of interest. The decisions are made by rules that reflect those criteria with appropriate weights that are determined according to the system states. A situated rule base for this mapping is built by an automated knowledge acquisition method based on system simulation. Distributed fuzzy sets are used for evaluating the criteria and recognizing the system states. The combined method is distinctive in its similarity to the way human schedulers accumulate and adjust their expertise: qualitatively establishing meaningful criteria and quantitatively optimizing the use of them. As a result, the developed rules may readily be interpreted, adopted and, when necessary, modified by human experts. An application of the proposed method to a job-dispatching problem in a hypothetical flexible manufacturing system (FMS) shows that the method can develop effective and robust rules.     

Hydrogen production from low temperature WGS reaction on co-precipitated Cu–CeO2 catalysts: An optimization of Cu loading

Low temperature water–gas shift (WGS) reaction has been carried out at the gas hourly space velocity of 72,152 h⁻¹ over Cu–CeO₂ catalyst prepared by a co-precipitation method. Cu loading was optimized to obtain highly active co-precipitated Cu–CeO₂ catalysts for low temperature WGS. 80 wt% Cu–CeO₂ exhibited the highest CO conversion as well as the most stable activity (X_CO > 46% at 240 °C for 100 h). The excellent catalytic performance is mainly due to a strong metal to support interaction, resulting in the prevention of Cu sintering.     

New method for low temperature fabrication of Ni–Al alloy powder for molten carbonate fuel cell applications

Lump-free Ni-5 wt% Al alloy powder was successfully prepared using an AlCl₃ activator at 400 °C under vacuum. The AlCl₃ activator served as the catalyst, lowering the fabrication temperature by 1000 °C compared with the temperature required for the conventional process. The Ni–Al alloy was formed by the following steps: the formation of NiAl by the reaction of the Ni surface with AlCl₂ or AlCl produced by the reaction between Al and AlCl₃, the formation of Ni₃Al by Al diffusion and reaction, and the formation of a Ni–Al solid solution by Al diffusion into the Ni matrix until the solubility limitation was reached. Although lowering the alloying temperature lengthens the reaction time, the time could be reduced by controlling the amount of AlCl₃. A single cell test and a creep test were also conducted using a green sheet of as-prepared Ni–Al alloy powder as an anode of a molten carbonate fuel cell (MCFC).     

On the effect of shear coefficients in free vibration analysis of curved beams

We did a comparative study of shear coefficients in free vibration analysis of curved beams having circular and rectangular crosssections. Until recently, the shear coefficient k in Timoshenko beam theory has been studied by many researchers to include transverse shear deformation effect. To obtain more reliable numerical results, a higher-order hybrid-mixed curved beam element is formulated and programmed in MATLAB. The present numerical experiments show that k = 6(1 + v)² / (7 + 12v + 4v ²) is the best expression both for circular and rectangular cross-sections in the flexural vibration of curved beams.     

Plasmon-enhanced quasi-solid-state dye-sensitized solar cells with metal@Dendron nanoparticles

We have investigated the effects of localized surface plasmons (LSPs) on the performance of quasi-solid-state dye-sensitized solar cells (DSSCs). Ag and Au nanoparticles (NPs) were prepared by photoreduction in the presence of generation 5 polyester hydroxyl acetylene bis(hydroxymethyl)propanoic acid dendrons (Dendron) as a stabilizer. The plasmon-enhanced DSSCs were achieved by incorporating metal@Dendron NPs into TiO₂ photoanodes. The presence of dendrons prevents the photoelectrons from recombining on the surface of TiO₂ semiconductor and improves the stability of metal NPs. With the addition of Ag@Dendron NPs, the photocurrent and the power conversion efficiency of quasi-solid-state DSSCs increased due to the LSP effect of metal NPs and the barrier effect of dendron, which were confirmed by the increased incident photon-to-photocurrent efficiency and by electrochemical impedance spectroscopy analysis.     

Mixing and Simplex Search for Optimal Illumination in Machine Vision

Mixed-color illumination affects the quality of images in industrial vision system and it is important to optimize color and intensity for image acquisition. This study used simplex search to find the optimal illumination in a short amount of time. A typical color mixer synthesized various color of lights by changing the inputs of RGB power LEDs and passing the lights through an optical system. The image quality under mixed-color illumination was calculated according to the sharpness. For the purpose of optimal illumination using simplex search, a probe network was organized with N + 1probing points for N inputs. The shape of the probe network, simplex, was varied through procedures of extension, contraction, and shrinkage. The inputs of the color mixer were changed until the size of the simplex became smaller than a threshold. The simplex search was tested for commercial semiconductor patterns, and was useful for finding the optimal illumination.     

Gaseous Nanocarving‐Mediated Carbon Framework with Spontaneous Metal Assembly for Structure‐Tunable Metal/Carbon Nanofibers

Vapor phase carbon (C)‐reduction‐based syntheses of C nanotubes and graphene, which are highly functional solid C nanomaterials, have received extensive attention in the field of materials science. This study suggests a revolutionary method for precisely controlling the C structures by oxidizing solid C nanomaterials into gaseous products in the opposite manner of the conventional approach. This gaseous nanocarving enables the modulation of inherent metal assembly in metal/C hybrid nanomaterials because of the promoted C oxidation at the metal/C interface, which produces inner pores inside C nanomaterials. This phenomenon is revealed by investigating the aspects of structure formation with selective C oxidation in the metal/C nanofibers, and density functional theory calculation. Interestingly, the tendency of C oxidation and calculated oxygen binding energy at the metal surface plane is coincident with the order Co > Ni > Cu > Pt. The customizable control of the structural factors of metal/C nanomaterials through thermodynamic‐calculation‐derived processing parameters is reported for the first time in this work. This approach can open a new class of gas–solid reaction‐based synthetic routes that dramatically broaden the structure‐design range of metal/C hybrid nanomaterials. It represents an advancement toward overcoming the limitations of intrinsic activities in various applications.     

Analytical and numerical assessments of local overpressure from hydrogen gas explosions in petrochemical plants

Accurate prediction of pressure rise is important for safety assessments of a petrochemical plant in the event of an explosion accident. The sudden pressures arising from gas explosions at various hydrogen concentrations in air have been predicted analytically and numerically. These solutions were compared against experimental data. The analytical solution, based on the self‐similar solution for pointwise strong explosions in an open space, which assumed no energy loss and premixed fuel‐air mixture, reasonably predicted the explosive‐ignition detonation case while the numerical solutions were more suitable to model spark‐ignition deflagration cases that accounted for the effect of turbulence arising from three‐dimensionality and presence of obstacles in the computational domain. Comparison of both analytical and numerical results against experimental data indicates that their differences are within a 30% margin. The analytical model presented herein can be useful for field engineers who want conservative estimates of the overpressure resulting from explosive‐ignition detonation. Copyright © 2016 John Wiley & Sons, Ltd.