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.     

Income, Time Effects and Direct Preferences in a Multimodal Choice Context: Application of Mixed RP/SP Models with Non-Linear Utilities

Transport problems typically involve at least two types of constraints, on income and on time. Therefore, the indirect utility function depends either on the income available after having subtracted the cost of the discrete alternative and on the free time left after having worked and travelled by each competing option. In the typical linear-in-the-attributes and in-the-parameters specification, that represents the first grade approximation of the indirect utility function, the effect of income and time constraints cancel out and only the cost and time of the alternatives matter in the comparison between them. From a microeconomic point of view this is equivalent to assume that income and time effects could be disregarded; which is not always the case. To account for these effects the utility function should include second order attributes; however, in non-linear utility functions it may not be easy to distinguish among several effects that could be relevant: direct preferences for good and leisure, and simple interactions between attributes other than income and time effects. This paper analyses these effects from a theoretical point of view focusing on the possible confounding problem in detecting income and time effects. We use a dataset collected for a modal choice context and containing both revealed and stated preference data, and estimate several NL models examining the effect of the different second-order terms on detecting income and time effects. We compared specifications including square cost and time attributes, interactions between time and cost, cost divided by the income available to be spent on free time, and time multiplied by free time. Our results confirm the strong effect of direct preferences for goods and leisure time on choice, and the potential confounding effect between quadratic attributes and other non-linear omitted terms. Finally, we also found that care should be taken in highlighting income and time effects using mixed data sources, since confounding effects can occur when non-linearities are accounted for in both data sets.     

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.