A systematic approach for product families formation in Reconfigurable Manufacturing Systems

The aim of this work is to establish a methodology for an effective working of Reconfigurable Manufacturing Systems (RMSs). These systems are the next step in manufacturing, allowing the production of any quantity of highly customised and complex products together with the benefits of mass production. In RMSs, products are grouped into families, each of which requires a system configuration. The system is configured to produce the first family of products. Once it is finished, the system is reconfigured in order to produce the second family, and so forth. Therefore, the effectiveness of a RMS depends on the formation of the best set of product families. Therefore, a methodology for grouping products into families, which takes into account the requirements of products in RMSs, is an issue of core importance. These requirements are modularity, commonality, compatibility, reusability, and product demand. The methodology starts by calculating, for each product requirement, a matrix that summarises the similarity between pairs of products. Then, through the use of the AHP methodology, a unique matrix that comprises the similarity values between products is obtained. The Average Linkage Clustering algorithm is applied to this matrix in order to obtain a dendogram that shows the diverse sets of product families that may be formed.     

Gigabit pulse position bistability in semiconductor lasers

The paper briefly reviews the major forms of optical bistability in active optical devices compatible for use in gigabit optical communication systems, and reports an entirely new optical bistability for the first time. Unlike previous devices, the two bistable states of the optical device are each a series of picosecond optical pulses at 1 GHz or greater repetition rates, and are distinguished by a half period temporal shift between their temporal positions in relation to a clock pulse. The bistable device is based on a gain switched semiconductor laser. Theoretical studies suggest 100-ps switching speeds might be achieved, and experimental results are reported indicating optically triggered switching times of 500 ps.     

FACTORS AFFECTING THE HARDNESS OF FAT ON SIDES OF CHILLED BEEF

The influence of some factors on the hardness of subcutaneous fat on sides of chilled beef as measured by the average force resisting movement of a cutting pin (Ff) was investigated. Values of Ff determined at a fat temperature of 10°C on grass-fed animals denied water 24 h preslaughter were not significantly influenced by moisture content (5-11%) or fat depth (2-27 mm). There was a quadratic relationship (P<0.001) between the age of animals at slaughter (31-141 months) and Ff, and a linear one (P<0.001) between saturated fatty acid content (35-50%) and Ff. Values of Ffat a fat temperature of 5°C were not significantly related to moisture content (1-22%) but there was a linear relationship (P<0.01) with fat depth (5-13 mm). This had a common slope for the three feeding patterns: (1) grass-fed animals denied water 24 h preslaughter; (2) grass-fed animals given access to water 24 h preslaughter, and; (3) lot-fed animals given access to water 24 h preslaughter.     

Inverse controller design for fuzzy interval systems

This paper aims at designing and analyzing an inverse controller for stable inversible (minimum phase) fuzzy interval linear and/or multilinear systems. The controller is designed from the fuzzy interval ranges of the system parameters using an /spl alpha/-cut methodology. Indeed, for a given /spl alpha/-cut of the fuzzy system parameters representing an uncertainty level, the control objective can be viewed as maintaining the system output within a tolerance envelope, around the exact trajectory, specified by the degree of preference /spl alpha/ on the fuzzy trajectory. The stability is ensured in the way that the controller restricts the system output divergence within the tolerance envelope. The validity of the proposed method is illustrated by simulation examples.     

Modeling the tensile properties in β-processed α/β Ti alloys

The development of a set of computational tools that permit microstructurally based predictions for the tensile properties of commercially important titanium alloys, such as Ti-6Al-4V, is a valuable step toward the accelerated maturation of materials. This paper will discuss the development of neural network models based on a Bayesian framework to predict the yield and ultimate tensile strengths of Ti-6Al-4V at room temperature. The development of such rules-based model requires the population of extensive databases, which in the present case are microstructurally based. The steps involved in database development include producing controlled variations of the microstructure using novel approaches to heat treatments, the use of standardized stereology protocols to characterize and quantify microstructural features rapidly, and mechanical testing of the heat-treated specimens. These databases have been used to train and test neural network models for prediction of tensile properties. In addition, these models have been used to identify the influence of individual microstructural features on the tensile properties, consequently guiding the efforts toward development of more robust mechanistically based models. Based on the neural network model, it is possible to investigate the influence of individual microstructural features on the tensile properties, and in certain cases these dependencies can point toward unrecognized phenomena. For example, the apparently unexpected trend of increase in tensile strength with increasing prior β-grain size has led to the determination of the pronounced role of the basketweave microstructure in strengthening these alloys, especially in case of larger prior β grains. This article is based on a presentation made in the symposium “Computational Aspects of Mechanical Properties of Materials,” which occurred at the 2005 TMS Annual Meeting, February 13–17, 2005, in San Francisco, CA, under the auspices of the MPMD-Computational Materials Science & Engineering (Jt. ASM-MSCTS) Committee.     

Poly-functional Catalyst Development for Benzene Production from Alkyl-aromatic Mixture via Hydrodealkylation

Development of a poly-functional catalyst that has higher hydrodealkylation activity based on 15% Cr/γ- Al₂ O₃ was researched for benzene production from an alkyl-aromatic mixture via hydrodealkylation. For this goal, the effects of the promoters like Fe, Co, or Ni and their concentrations on the activity of a Cr/Al₂ O₃ catalyst were investigated. Toluene + n-heptane + tetrahydrotiophene (89:10:1 w%) model mixture, which has the same content as industrial aromatics, was used as feedstock. The activities of catalysis in reactions of hydrodealkylation, hydrocracking, and hydrogenolize with respect to conversions of toluene, heptane, and tetrahydrotiophene were tested, respectively. As to the obtained results, the catalyst including 5% Fe has a higher hydrodealkylation activity, compared to the catalyst including Co, and especially to the alumocrom catalyst not including a promoter, while it has a lower coke formation and reduced activity to the catalyst including Ni.     

Effect of sodium carbonate on the oxidation of sublimates during niobium electron-beam remelting

The effect of sodium carbonate additions on phase formation during the air oxidation of the sublimates of niobium electron-beam remelting is studied by derivatography, X-ray diffraction analysis, and electron-probe microanalysis. The composition of the oxidation products changes with the heating temperature. The formation of sodium niobates and aluminates is detected by X-ray diffraction analysis at temperatures higher than 600°C. The oxidation of the sublimates is completed by the formation of sodium metaniobate and aluminate. Sodium carbonate additions are shown to accelerate the oxidation of the sublimates.