The effect of cure cycle heating rate on the fibre/matrix interface

Development of civil aerospace composites is key to future “greener” aircraft. Aircraft manufacturers must improve efficiency of their product and manufacturing processes to remain viable. The aerospace industry is undergoing a materials revolution in the design and manufacture of composite airframes. The Airbus A350 and Boeing 787 (both due to enter service in the latter part of this decade) will push utilisation levels of  composite materials beyond 50% of the total airframe by weight. This  change requires massive investment in materials technology, manufacturing capability and skills development. The Quickstep process provides the ability to rapidly cure aerospace standard composite materials whilst providing enhanced mechanical properties. Utilising fluid to transfer heat to the   composite component during the curing process allows far higher heat rates than with conventional cure techniques. The rapid heat-up rates reduce the viscosity of the resin system greatly to provide a longer processing window introducing greater flexibility and removing the need for high pressure during cure. Interlaminar fracture toughness (Mode I) and Interfacial Shear Strength of aerospace standard materials cured using Quickstep have been    compared to autoclave cured laminates. Results suggest an improvement in fibre-matrix adhesion.

Empirical examination of the stakeholder strategy matrix

Purpose – This paper seeks to examine whether the stakeholder strategy matrix provides useful guidance for managers in dealing with stakeholders. The matrix suggests that strategies for dealing with stakeholders can be determined based on stakeholder ability to cooperate and threaten organisational outcomes.

Design/methodology/approach – The study uses a hypothetical scenario looking at the development of a new environmentally friendly product, where eight stakeholder groups and their influencing abilities are manipulated. Marketers reviewed one version of the scenario and were then asked the applicability of 13 strategies for each stakeholder group described. Mixed design analysis is then undertaken to examine the direct effects and interactions between the four combinations of influencing abilities, the stakeholder group examined or how the strategy suggested impacted on managers' views.

Findings – The research found that there was an interaction effect suggesting that some strategies were more applicable to stakeholders with certain sets of influencing abilities, as the stakeholder strategy matrix suggested. The specific stakeholder group examined also appeared to impact on managers' views, which is inconsistent with the theory.

Research limitations/implications – The limitations are that the research focused on managers' perceptions of the applicability of strategies, rather than the actual success of strategies examined. Research into the effectiveness of actual behaviours would possibly require more in-depth examination of case studies.

Practical implications – The research suggests that the stakeholder strategy matrix may provide some guidance as to how managers deal with stakeholders. However, it also suggests that managers may be implicitly applying influencing abilities to groups irrespective of their “true” influencing ability. In this case managers are in fact ignoring valuable information when deciding how to interact with stakeholders and therefore possibly using less effective strategies to interact with stakeholders.

Originality/value – The research is unique as it looks at determining whether different types of strategies for dealing with stakeholders are perceived to be more or less effective. This therefore seeks to make stakeholder theory more strategic and applicable in a broader set of contexts. As such the paper would be of interest to managers seeking to understand better how to deal with stakeholders and to theorists seeking to understand better how stakeholder theory impacts on organisational outcomes.

The TOC-ABC choice debate for product mix decisions : introducing asset specificity as an alternate explanation

Though constructed with different purposes, the theory of constraints and activity based costing systems pose a choice problem in respect of product mix decisions. We believe that the existing explanation of short versus long run criterion to explain firms' choice between these two systems is incomplete and offer an alternate explanation based on asset specificity. We argue that the extent to which specialized resources are deployed to make products in a mix determines the choice. We present a 2*2 matrix stating that when asset specificity is high, a firm is likely to choose ABC instead of TOC since ABC makes a large portion of costs visible to enable control. However, the choice is likely to be a TOC-ABC combination when the manufacture of asset specific products is also constrained by bottlenecks.

MoO3 nanoparticles dispersed uniformly in carbon matrix : a high capacity composite anode for Li-ion batteries

A MoO₃-carbon nanocomposite was synthesized from a mixture of MoO₃ and graphite by a controlled ball milling procedure. The as-prepared product consists of nanosized MoO₃ particles (2-180 nm) homogeneously distributed in carbon matrix. The nanocomposite acts as a high capacity anode material for lithium-ion batteries and exhibits good cyclic behavior. Its initial capacity exceeds the theoretical capacity of 745 mA h g^-1 in a mixture of MoO₃ and graphite (1:1 by weight), and the stable capacity of 700 mA h g^-1 (94% of the theoretical capacity) is still retained after 120 cycles. The electrode performance is linked with the unique nanoarchitecture of the composite and is compared with the performance of MoO₃-based anode materials reported in the literature previously (nanoparticles, ball milled powders, and carbon-coated nanobelts). The high value of capacity and good cyclic stability of MoO₃-carbon nanocomposite are attractive in respect to those of the reported MoO₃ electrodes.

Cumulative restricted Boltzmann machines for ordinal matrix data analysis

Ordinal data is omnipresent in almost all multiuser-generated feedback - questionnaires, preferences etc. This paper investigates modelling of ordinal data with Gaussian restricted Boltzmann machines (RBMs). In particular, we present the model architecture, learning and inference procedures for both vector-variate and matrix-variate ordinal data. We show that our model is able to capture latent opinion profile of citizens around the world, and is competitive against state-of-art collaborative filtering techniques on large-scale public datasets. The model thus has the potential to extend application of RBMs to diverse domains such as recommendation systems, product reviews and expert assessments.