Reducing cycle times in manufacturing and supply chains by input and service rate smoothing

A key performance parameter of a manufacturing network or supply chain is its cycle time; the time that a typical item spends in the network. A previous simulation study on a semiconductor assembly and test facility showed that cycle times could be reduced by having smooth input and service rates. This suggested that there is a “cycle time principle” that, for a system with a specified throughput or input rate, the shortest cycle times are obtained when the input and service rates do not vary over time. We prove that this principle is true for the M/G/1 and M/M/s queueing systems and Jackson networks. The analysis involves establishing several results on the concavity of waiting time probabilities and the convexity of expected waiting times and queue lengths, as functions of input and service rates. These results also have natural uses in other optimization problems.     

Parallel transport: a new transport layer paradigm for enabling Internet quality of service

The transport layer in the network protocol stack serves as a liaison between the application and the underlying network. Any quality of service provided by the network thus has to be effectively translated by the transport layer protocol in order to be enjoyed by the applications. In this article, we argue for a fundamental rethinking of the transport layer design to facilitate such QoS delivery. We identify the key requirement for a QoS enabling transport layer protocol as the ability to effectively handle multiplicity in terms of user differentiation levels, network resources, and service models. However, TCP, the transport layer protocol predominantly used in the Internet, is unable to support such multiplicity due to its single-state design. We extend TCP to a parallel transport layer protocol called parallel TCP (pTCP) that can tackle the different dimensions of multiplicity, and hence enable varying classes of QoS to applications. We discuss the applicability of pTCP in three specific domains with different levels of network support for QoS, and present simulation results substantiating our arguments.     

Control of power factor correcting boost converter withoutinstantaneous measurement of input current

This paper proposes a new control method for the constant-frequency control of power factor correcting boost power converter using a sinewave template modulated PWM signal which eliminates the need for instantaneous measurement of the line current for the switching control of the boost converter. The control strategy is based on the notion that the line current can be forced to trace a deterministic waveform such as a sinusoid by considering the implicit model of the sinewave in the boost converter controller structure. The modulating sinewave template is generated using the line voltage, the boost converter output voltage and the load current. The paper provides the analysis and the design of the controller and presents simulation and implementation results to demonstrate its effectiveness     

A study on development of cognitive support features in recent ontology visualization tools

Ontologies are currently emerging as representation techniques for overlapping compatibility context domains. The continuing need for more effective information retrieval has lead to the creation of the notions of the semantic web and personalized information management. Subsequently, the need for effective ontology visualization for design, management and browsing has arisen. Several ontology visualization tools have come out to strengthen the users’ cognitive support. The primary goal of this paper is to present a survey on recently implemented ontology visualization tools and their contributions in the enrichment of users’ cognitive support. This work also presents the preliminary results of an evaluation of three visualization tools to determine the suitability of each method for end user applications where ontologies are used as browsing aids.     

A robust kinematic hardening rule for cyclic plasticity with ratchetting effects

Summary A robust kinematic hardening rule is proposed which appropriately blends the deviatoric stress rate rule and the Tseng-Lee rule in order to satisfy both the experimental observations made by Phillips et al. [1]–[5] and the nesting of the yield surface to the limit surface. The work presented in Part I is confined to the theoretical formulation of kinematic hardening rule with limited correlation to experimental results. A more general expression for the plastic modulus is proposed. The expressions proposed by McDowell and by Dafalias can be obtained as a special case of the proposed expression. An additional parameter is introduced that reflects the dependence of the plastic modulus on the angle between the deviatoric stress rate tensor and the direction of the limit backstress relative to the yield backstress.     

On the electrochemical nature of hot-corrosion attack in Ni-Cr alloys

Hot-corrosion attack on gas-turbine components has been a problem of practical importance for over two decades. The nature and the extent of corrosion are influenced by the type of contaminants, the alloy constituents, and temperature. The hot-corrosion process is quite complex. There is controversy regarding the role of alloying elements, and whether the process is chemical or electrochemical in nature. In this investigation, an attempt has been made to investigate the role of Al and Ti in influencing the hot-corrosion attack of Ni-20 wt. % Cr alloys in molten Na₂SO₄-NaCl mixtures. It was found that Ni-Cr-Al alloys undergo a localized, heavy-blister attack under certain experimental conditions which is electrochemical in nature. An electrochemical model has been proposed which can satisfatorily explain the nature and kinetics of the localized blister corrosion.     

Prediction of urban stormwater quality using artificial neural networks

There are a vast number of complex, interrelated processes influencing urban stormwater quality. However, the lack of measured fundamental variables prevents the construction of process-based models. Furthermore, hybrid models such as the buildup-washoff models are generally crude simplifications of reality. This has created the need for statistical models, capable of making use of the readily accessible data. In this paper, artificial neural networks (ANN) were used to predict stormwater quality at urbanized catchments located throughout the United States. Five constituents were analysed: chemical oxygen demand (COD), lead (Pb), suspended solids (SS), total Kjeldhal nitrogen (TKN) and total phosphorus (TP). Multiple linear regression equations were initially constructed upon logarithmically transformed data. Input variables were primarily selected using a stepwise regression approach, combined with process knowledge. Variables found significant in the regression models were then used to construct ANN models. Other important network parameters such as learning rate, momentum and the number of hidden nodes were optimized using a trial and error approach. The final ANN models were then compared with the multiple linear regression models. In summary, ANN models were generally less accurate than the regression models and more time consuming to construct. This infers that ANN models are not more applicable than regression models when predicting urban stormwater quality.     

Mixed Nb<Subscript>2</Subscript>O<Subscript>5</Subscript>:MoO<Subscript>3</Subscript> (95:5 and 85:15) thin films and their properties for electrochromic device applications

Nb₂O₅:MoO₃ (95:5 and 85:15) thin films were deposited onto glass and fluorine doped tin oxide coated glass substrates at 100 and 300 °C by RF magnetron sputtering technique. The physical and electrochromic properties of the films were studied. XRD result reveals that deposited films were amorphous. The XPS study confirms the compositional purity and the presence of Nb⁵⁺ and Mo⁶⁺ in the deposited film. Surface morphological study shows platelet like features of deposited film. The average transmittance of the film is varied between 91 and 85 %. Photoluminescence study exhibits three characteristic emission peaks and confirms the better optical quality of deposited film. Raman spectra show the LO–TO splitting of Nb–O stretching of the deposited film. Electrochromic behavior of the deposited films characterized by cyclic voltammetry using 0.5 M LiClO₄·PC and 0.5 M H₂SO₄ electrolyte solutions show all the films are having better reversibility and reproducibility in their electrochemical analysis.     

Simultaneous optimal selection of design and manufacturing tolerances with alternative manufacturing process selection

Tolerance specification is an important part of mechanical design. Design tolerances strongly influence the functional performance and manufacturing cost of a mechanical product. Tighter tolerances normally produce superior components, better performing mechanical systems and good assemblability with assured exchangeability at the assembly line. However, unnecessarily tight tolerances lead to excessive manufacturing costs for a given application. The balancing of performance and manufacturing cost through identification of optimal design tolerances is a major concern in modern design. Traditionally, design tolerances are specified based on the designer’s experience. Computer-aided (or software-based) tolerance synthesis and alternative manufacturing process selection programs allow a designer to verify the relations between all design tolerances to produce a consistent and feasible design. In this paper, a general new methodology using intelligent algorithms viz., Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi Objective Particle Swarm Optimization (MOPSO) for simultaneous optimal selection of design and manufacturing tolerances with alternative manufacturing process selection is presented. The problem has a multi-criterion character in which 3 objective functions, 3 constraints and 5 variables are considered. The average fitness factor method and normalized weighted objective functions method are separately used to select the best optimal solution from Pareto optimal fronts. Two multi-objective performance measures namely solution spread measure and ratio of non-dominated individuals are used to evaluate the strength of Pareto optimal fronts. Two more multi-objective performance measures namely optimiser overhead and algorithm effort are used to find the computational effort of NSGA-II and MOPSO algorithms. The Pareto optimal fronts and results obtained from various techniques are compared and analysed.