Decomposition-based design optimization method using genetic co-evolution

The paper examines new strategies for the implementation of genetic algorithms in a decomposition-based approach for design. In this approach, the design problem is decomposed into smaller-sized sub-problems, the solutions for which are obtained through co-evolution. The emphasis resides in evaluating methods for exchanging design information relevant to coordinating solutions of temporarily decoupled sub-problems. Methods based on modification of genetic makeup through experiential inheritance (exposure to another species), and through inter-species migration are investigated in this work. Different forms of design problem coupling are investigated, ranging from coupling through constraints only, to coupled objective and constraint functions. The proposed strategies are validated through implementation in representative algebraic and structural design problems.     

Molecular mobility in a homologous series of amorphous solid glucose oligomers

The molecular mobility of amorphous solid biomaterials influences the stability of dried foods and pharmaceuticals, the viability of seeds and spores, and the desiccation-tolerance of organisms during anhydrobiosis. Current understanding of how structure correlates with molecular mobility in the glassy state is inadequate. We used phosphorescence from vanillin dispersed in amorphous films to study the effect of temperature on molecular mobility in the homologous series of oligosaccharides glucose, maltose, maltotriose, maltotetraose, maltopentaose, maltohexaose, and maltoheptaose. Phosphorescence emission spectra and intensity decays were collected from −10 to as high as 130 °C. Emission peak energy, a measure of the extent of dipolar relaxation around the excited state prior to emission, decreased monotonically with temperature, decreasing more significantly in the glassy state in larger sugars (higher degree of polymerisation). The intensity decays were well fitted with sums of either four (glucose, maltose, maltotriose) or three exponentials (maltotetraose, maltopentaose, maltohexaose, maltoheptaose); fit lifetimes at each temperature varied over nearly two orders of magnitude, suggesting a comparable range in matrix dynamic heterogeneity. The lifetimes decreased monotonically with temperature, while the lifetime amplitudes favoured the long lifetime components at lower and short lifetime components at higher temperatures near T_g. Arrhenius analysis indicated that the rate of non-radiative decay, which reflects coupling of probe vibrations with matrix motions and thus provides an estimate of the matrix molecular mobility, increased with molecular size in the glassy state. Both apparent activation energy and activation entropy increased systematically with temperature in all sugars. These data provide additional evidence that the rate and extent of molecular mobility in glassy state carbohydrates is higher in sugars of greater molecular size (mass) and thus higher glass transition temperature and provides additional insight into the molecular dynamics of the glassy state in carbohydrates.     

Electrospinning pure protein solutions in core–shell fibers

Electrospinning of protein‐loaded fibers faces many challenges, e.g. burst release owing to segregation of the protein on the fiber surface, loss of activity due to electrospinning conditions, limitation of loading capacity etc. Core–shell electrospinning provides an effective way to electrospin fibers wherein the core can be loaded with bioactive molecules in friendly conditions of a compatible polymer solution, thereby protecting the molecules from the electrostatic field and organic solvent of shell solutions. The shell polymer, after the electrospinning, acts as a barrier to control the release of the loaded molecules. However, the limitation of loading capacity still remains due the prerequisite of using an additional polymer as additive to achieve the minimum viscosity of the core solution required for viscous drag by the shell solution being drawn by the electrostatic force. The work reported here aims to alleviate the need of a polymer additive by using aqueous protein solutions of very high concentration. High concentrations of protein solutions were successfully electrospun as the core of the protein–poly(lactide‐co‐glycolic acid) core–shell fibers. A partitioning effect was seen in the controlled release of hydrophilic proteins as they were retained in the aqueous core for longer times. Using lysozyme as a model protein, it was shown that the activity is significantly retained after electrospinning, compared with electrospinning in monolithic fibers. Moreover, the lysozyme activity was also comparable with the lysozyme released from core–shell fibers spun using poly(vinyl acetate) as additive in the core. Copyright © 2012 Society of Chemical Industry     

Crowdsourcing as a service – from pilot projects to sustainable innovation routines

While crowdsourcing may strengthen a company's innovation performance, it is only rarely embedded in organizations as an innovation practice. Our action research shows that organizations often struggle with crowdsourcing projects as they represent a different form of innovation projects and require additional capabilities and skills e.g., to frame a crowd challenge, deal with IP rights, manage the crowd, or integrate the vast input into innovation projects. To overcome these problems, organizations have to invest in project-led learning to establish easy-to-use templates and routines e.g., to handle offered incentives or the applied winner selection processes. They further need to enable business-led learning as the established innovation structures, processes, and management practices do not cope with crowdsourcing projects and present some rigidities causing high coordination efforts. Organizations that are willing to run a number of consecutive crowdsourcing projects may rapidly improve their capabilities and even come up with scalable crowdsourcing services. Our findings further suggest that crowdsourcing, digital platforms, artificial intelligence, and as-a-service approaches may also add to general project capability building.     

Impulse Pressure Assisted Diffusion Bonding of Low Carbon Steel Using Silver Interlayer

In the present study, impulse pressure assisted diffusion bonding of low carbon steel was carried out using silver interlayer. To study the influence of input process parameters namely bonding temperature (T), maximum pulse pressure (P), and number of pulses (N), experiments of diffusion bonding were conducted according to the Taguchi L9 orthogonal array. To reveal the typical bond interface characteristics, selected samples were examined by scanning electron microscopy (FESEM) equipped with energy dispersive spectroscopy (EDS). The EDS analysis revealed a diffusion affected zone at the interface due to the diffusion of silver and iron across the interface. Lap joints were developed to measure the shear strength of the diffusion bonds. The optimum level of bonding temperature, maximum pulse pressure and number of pulses (875 °C, 10 MPa and 10 pulses) were identified. The ANOVA results indicated that bonding temperature had the highest statistical effect of 66.37% on shear strength followed by number of pulses and maximum pulse pressure. The fracture surface of the lap joints was also examined by FESEM and X-ray diffraction analysis.     

An efficient hybrid evolutionary heuristic using genetic algorithm and simulated annealing algorithm to solve machine loading problem in FMS

In this paper, a machine loading problem in a flexible manufacturing system (FMS) is discussed, with bi-criterion objectives of minimising system imbalance and maximising system throughput in the occurrence of technological constraints such as available machining time and tool slots. A mathematical model is used to select machines, assign operations and the required tools in order to minimise the system's imbalance while maximising the throughput. An efficient evolutionary algorithm by hybridising the genetic algorithm (GA) and simulated annealing (SA) algorithm called GASA is proposed in this paper. The performance of the GASA is tested by using 10 sample dataset and the results are compared with the heuristics reported in the literature. The influence of genetic operators on the evolutionary search in GASA is studied and reported. Two machine selection heuristics are proposed and their influence on the quality of the solution is also studied. Extensive computational experiments have been carried out to evaluate the performance of the proposed evolutionary heuristics and the results are presented in tables and figures. The results clearly support the better performance of GASA over the algorithms reported in the literature.