Industry case studies in the use of immersive virtual assembly

In this paper, we report on two engineering case studies that have been conducted as part of a Virtual Assembly Technology Consortium. The objectives of the case studies were to determine if immersive virtual assembly capabilities allow industry assembly situations to be modelled and studied realistically, and to demonstrate the downstream value of the virtual assembly capabilities in areas such as ergonomics, assembly installation, process planning, installation, and serviceability. What is of special significance is that instead of modelling simplified problems or perceived representative situations, the case studies were constructed from actual assembly floor projects and situations encountered at industry member sites and with considerable participation from industry engineers and manufacturing shop floor personnel. Based on the success of the case studies, the consortium members inferred that virtual assembly methods are poised to move out of the realm of special projects and test scenarios to deployment in the actual design and manufacturing cycle. However, in order to be truly accepted in industry, there are still issues to be addressed in terms of ease of use, portability of the applications, and preparation of the models for the evaluations. Thus, the case studies added a new dimension to the exploration and understanding of how this new technology could be of practical value in industry.     

Improving process models by discovering decision points

Workflow management systems (WfMS) are widely used by business enterprises as tools for administrating, automating and scheduling the business process activities with the available resources. Since the control flow specifications of workflows are manually designed, they entail assumptions and errors, leading to inaccurate workflow models. Decision points, the XOR nodes in a workflow graph model, determine the path chosen toward completion of any process invocation. In this work, we show that positioning the decision points at their earliest points can improve process efficiency by decreasing their uncertainties and identifying redundant activities. We present novel techniques to discover the earliest positions by analyzing workflow logs and to transform the model graph. The experimental results show that the transformed model is more efficient with respect to its average execution time and uncertainty, when compared to the original model.     

Strength prediction of multi-layer plain weave textile composites using the direct micromechanics method

Previously developed micromechanical methods for stiffness and strength prediction are adapted for analysis of multi-layer plain weave textile composites. Utilizing the direct micromechanics method (DMM) via finite element modeling, three methods are presented: (a) direct simulation of a multi-layer plain weave textile composite; (b) micromechanical analysis of a single layer of interest from the force and moment resultants acting on that layer; and (c) application of the previously developed quadratic stress-gradient failure theory to the layer of interest. In comparison to direct modeling, the other two techniques show only 5% difference over a number of random test cases. Several practical design examples of strength prediction are included to illustrate the importance and accuracy of method implementation.     

Screening of Soil Amendments for Efficient Water-Holding Capacity Based on a Rainfall-Infiltration Model in a Vertisol

A simulation study was conducted with five soil amendments, viz., goat manure, coir pith, phosphogypsum, polyacrylamide, and a control at two rainfall intensities of 60 and 120?mm?h?1 under dry and wet soil conditions in a clay loam vertisol with the objective of identifying a superior soil amendment for maximum infiltration and suitable soil aggregate stability. The F-test based on analysis of variance of infiltration data indicated that soil amendments, rainfall intensities, and soil conditions were significantly different from each other. Based on least significant difference test, polyacrylamide was found to be superior with a significantly higher infiltration, compared to all other amendments. An exponential model of infiltration over a time interval was calibrated for each soil amendment under dry and wet soil conditions. Based on the model, polyacrylamide and phosphogypsum were found to have a better soil aggregate stability compared to other soil amendments. The exponential model gave a significant predictability of instantaneous infiltration ranging from 0.75 to 0.99 under different situations. A grouping of treatments based on mean and coefficient of variation of infiltration in comparison with soil aggregate stability values indicated that polyacrylamide was superior under different situations in the study. Phosphogypsum was found to be the second best soil amendment with a relatively lower infiltration compared to polyacrylamide, but with a better soil aggregate stability compared to other soil amendments. Coir pith, goat manure, and control gave a significantly lower infiltration with a relatively higher variation compared to polyacrylamide and phosphogypsum, and also had a relatively lower soil aggregate stability under different situations examined in the study.     

In situ synthesised TiO2 ‐chitosan‐chondroitin 4–sulphate nanocomposites for bone implant applications

The artificial materials for bone implant applications are gaining more importance in the recent years. The series titania‐chitosan‐chondroitin 4–sulphate nanocomposites of three different concentrations (2:1:x, where x ‐ 0.125, 0.25, 0.5) have been synthesised by in situ sol–gel method and characterised by various techniques. The particle size of the nanocomposites ranges from 30–50 nm. The bioactivity, swelling nature, and the antimicrobial nature of the nanocomposites were investigated. The swelling ability and bioactivity of the composites is significantly greater and they possess high zone of inhibition against the microorganisms such as Staphylococcus aureus and Escherichia coli. The cell viability of the nanocomposites were evaluated by using MG‐63 and observed the composites possess high cell viability at low concentration. The excellent bioactivity and biocompatibility makes these nanocomposites a promising biomaterial for bone implant applications.Inspec keywords: titanium compounds, filled polymers, nanocomposites, bone, orthopaedics, biomedical materials, sol‐gel processing, nanofabrication, particle size, swelling, microorganisms, cellular biophysics, nanomedicine, prostheticsOther keywords: in situ synthesised TiO₂ ‐chitosan‐chondroitin 4‐sulphate nanocomposites, bone implant applications, artificial materials, in situ sol‐gel method, particle size, swelling nature, antimicrobial nature, microorganisms, Staphylococcus aureus, Escherichia coli, cell viability, MG‐63, biomaterial, size 30 nm to 50 nm, TiO₂      

Optimization of bead geometry of submerged arc weld using fuzzy based desirability function approach

The present study highlights application of Taguchi’s robust design coupled with fuzzy based desirability function approach for optimizing multiple bead geometry parameters of submerged arc weldment. Fuzzy inference system has been adapted to avoid uncertainly, imprecision and vagueness in experimentation as well as in data analysis by traditional Taguchi based optimization approach. Detailed methodology and unique features of the proposed method has been highlighted through a case study. The said approach can efficiently be used in off-line quality control of any production process as well as automation of the process.     

Price sensitive demand with random sales price – a newsboy problem

Up to now, many newsboy problems have been considered in the stochastic inventory literature. Some assume that stochastic demand is independent of selling price (p) and others consider the demand as a function of stochastic shock factor and deterministic sales price. This article introduces a price-dependent demand with stochastic selling price into the classical Newsboy problem. The proposed model analyses the expected average profit for a general distribution function of p and obtains an optimal order size. Finally, the model is discussed for various appropriate distribution functions of p and illustrated with numerical examples.     

A multi-sensor climatological view of double ITCZs over the Indian Ocean

We characterize the climatological features of the double inter-tropical convergence zones (DITCZs) over the western Indian Ocean during November–December by a synergistic analysis of the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite (HOAPS III) data (1988–2005) and the National Aeronautics and Space Administration's (NASA's) A-Train data (2002–2009). We investigate rainfall, freshwater flux and cloud liquid water, cloud fraction and relative humidity over the DITCZs. In addition, the daily rainfall data from the Global Precipitation Climatology Project (GPCP) are used to document the DITCZs during the El Niño southern oscillation (ENSO) events. An analysis of the GPCP data shows that the DITCZs are clearly discernible during strong ENSO events (1997, 2002 and 2006), in sharp contrast to the DITCZs in the eastern Pacific Ocean, where they are absent during ENSOs. Further, these convergence zones on either side of the equator are of short duration, approximately 3–6 pentads during November and December. All satellite sensor data sets consistently capture the major features of DITCZs. As an accurate simulation of DITCZs in coupled global climate models remains a challenge, the results from the present study would provide a platform for evaluating these models.     

A fuzzy-controlled Hooke-Jeeves optimization algorithm

This article presents an approach to enhance the Hooke-Jeeves optimization algorithm through the use of fuzzy logic. The Hooke-Jeeves algorithm, similar to many other optimization algorithms, uses predetermined fixed parameters. These parameters do not depend on the objective function values in the current search region. In the proposed algorithm, several fuzzy logic controllers are integrated at the various stages of the algorithm to create a new optimization algorithm: Fuzzy-Controlled Hooke-Jeeves algorithm. The results of this work show that incorporating fuzzy logic in the Hooke-Jeeves algorithm can improve the ability of the algorithm to reach an extremum in different typical optimization test cases and design problems. Sensitivity analysis of the variables of the algorithm is also considered.     

An analytical approach to dynamic crosstalk in coupled interconnects

This paper deals with waveform analysis, crosstalk peak and delay estimation of CMOS gate driven capacitively and inductively coupled interconnects. Simultaneously switching inputs for the coupled interconnects are considered. A transmission line-based coupled model of interconnect is used for analysis. Alpha-power Law model of MOS transistor is used to represent the transistors in CMOS driver. Peaks and delays at far-end of victim line are estimated for conditions when the inputs to the two coupled interconnects are switching in-phase and out-of-phase. The comparison of analytically obtained results with SPICE simulations show that the proposed model captures noise peak and their timing; 90% propagation delay; transition time delay and waveform shape with good accuracy, such as not more than 5% error in crosstalk peak estimation.