Strategies for product recovery decisions

Product recovery is beset by uncertainty regarding the quality of end-of-life (EOL) products, and in order to ascertain the reusability of these products, they have to undergo expensive tests. This undermines the profitability of the recovery process. The key to improve the effectiveness of product recovery is to improve the quality of information available before testing. Emerging data capture technologies can significantly improve the availability of information. However, in order to maximise the potential of these technologies, appropriate decision-making algorithms that exploit such information must be developed. We model the recovery process using a decision-theoretic approach, and derive strategies to ascertain the reusability of EOL products, and also to decide when tests are beneficial. We show that improving the quality of information leads to increase in effectiveness of the recovery process by reducing the need for tests. Copyright © 2009 Inderscience Enterprises Ltd.

The role for low carbon electrification technologies in poverty reduction and climate change strategies: A focus on renewable energy mini-grids with case studies in Nepal, Peru and Kenya

As a potential poverty reduction and climate change strategy, this paper considers the advantages and disadvantages of using renewable energy technologies for rural electrification in developing countries. Although each case must be considered independently, given a reliable fuel source, renewable energy mini-grids powered by biomass gasifiers or micro-hydro plants appear to be the favoured option due to their lower levelised costs, provision of AC power, potential to provide a 24. h service and ability to host larger capacity systems that can power a wide range of electricity uses. Sustainability indicators are applied to three case studies in order to explore the extent to which sustainable welfare benefits can be created by renewable energy mini-grids. Policy work should focus on raising awareness about renewable energy mini-grids, improving institutional, technical and regulatory frameworks and developing innovative financing mechanisms to encourage private sector investments. Establishing joint technology and community engagement training centres should also be encouraged. © 2011 Elsevier Ltd.

Sensor graphs for guaranteed cooperative localization performance

A group of mobile robots can localize cooperatively, using relative position and absolute orientation measurements, fused through an extended Kalman filter (ekf). The topology of the graph of relative measurements is known to affect the steady-state value of the position error covariance matrix. Classes of sensor graphs are identified, for which tight bounds for the trace of the covariance matrix can be obtained based on the algebraic properties of the underlying relative measurement graph. The string and the star graph topologies are considered, and the explicit form of the eigenvalues of error covariance matrix is given. More general sensor graph topologies are considered as combinations of the string and star topologies, when additional edges are added. It is demonstrated how the addition of edges increases the trace of the steady-state value of the position error covariance matrix, and the theoretical predictions are verified through simulation analysis.

Linear quadratic game and non-cooperative predictive methods for potential application to modelling driver-AFS interactive steering control

This paper is concerned with the modelling of strategic interactions between the human driver and the vehicle active front steering (AFS) controller in a path-following task where the two controllers hold different target paths. The work is aimed at extending the use of mathematical models in representing driver steering behaviour in complicated driving situations. Two game theoretic approaches, namely linear quadratic game and non-cooperative model predictive control (non-cooperative MPC), are used for developing the driver-AFS interactive steering control model. For each approach, the open-loop Nash steering control solution is derived; the influences of the path-following weights, preview and control horizons, driver time delay and arm neuromuscular system (NMS) dynamics are investigated, and the CPU time consumed is recorded. It is found that the two approaches give identical time histories as well as control gains, while the non-cooperative MPC method uses much less CPU time. Specifically, it is observed that the introduction of weight on the integral of vehicle lateral displacement error helps to eliminate the steady-state path-following error; the increase in preview horizon and NMS natural frequency and the decline in time delay and NMS damping ratio improve the path-following accuracy. © 2013 Copyright Taylor and Francis Group, LLC.

Strategies for modeling turbulent flows in electronics

Hybrid methods based on the Reynolds Averaged Navier Stokes (RANS) equations and the Large Eddy Simulation (LES) formulation are investigated to try and improve the accuracy of heat transfer and surface temperature predictions for electronics systems and components. Two relatively low Reynolds number flows are studied using hybrid RANS-LES, RANS-Implicit-LES (RANS-ILES) and non-linear LES models. Predictions using these methods are in good agreement with each other, even using different grid resolutions. © 2008 IEEE.

Value creation from the innovation environment: Partnership strategies in university spin-outs

University spin-out (USO) companies play an increasingly important role in generating value from radical, generic technologies, but this translation requires significant resources from other players to reach the market. Seven case studies illuminate how relationships with each type of partner can be leveraged to help the firm create value. We find that most firms in the sample are aware of the importance of corporate partners and actively seek to cultivate these relationships, but may not be taking full advantage of the resources available through nonparent academic institutions and other USOs with similar or complementary technologies. © 2013 The Authors. R&D Management © 2013 Blackwell Publishing Ltd.

Neural mechanisms of belief inference during cooperative games.

Humans have the arguably unique ability to understand the mental representations of others. For success in both competitive and cooperative interactions, however, this ability must be extended to include representations of others' belief about our intentions, their model about our belief about their intentions, and so on. We developed a "stag hunt" game in which human subjects interacted with a computerized agent using different degrees of sophistication (recursive inferences) and applied an ecologically valid computational model of dynamic belief inference. We show that rostral medial prefrontal (paracingulate) cortex, a brain region consistently identified in psychological tasks requiring mentalizing, has a specific role in encoding the uncertainty of inference about the other's strategy. In contrast, dorsolateral prefrontal cortex encodes the depth of recursion of the strategy being used, an index of executive sophistication. These findings reveal putative computational representations within prefrontal cortex regions, supporting the maintenance of cooperation in complex social decision making.

Strategies to reduce the carbon footprint of consumer goods by influencing stakeholders

Consumer goods contribute to anthropogenic climate change across their product life cycles through carbon emissions arising from raw materials extraction, processing, logistics, retail and storage, through to consumer use and disposal. How can consumer goods manufacturers make stepwise reductions in their product life cycle carbon emissions by engaging with, and influencing their main stakeholders? A semi-structured interview approach was used: to identify strategies and actions, stakeholders in the consumer goods industry (suppliers, manufacturers, retailers and NGOs) were interviewed about carbon emissions reduction projects. Based on this, a summarising presentation was made, which was shared during a second round of interviews to validate and refine the results. The results demonstrate several opportunities that have not yet been exploited by companies. These include editing product choice in stores to remove products with higher carbon footprints, using marketing competences for environmental benefits, and bundling competences to create winewinewin business models. Governments and NGOs have important enabling roles to accelerate industry change. Although this work was initially developed to explore how companies can reduce life cycle carbon emissions of their products, these strategies and actions also give insights on how companies can influence and anticipate stakeholder actions in general. © 2012 Elsevier Ltd. All rights reserved.