Supply network integration in multi-organisational network systems

This paper explores supply network integration in complex product service systems involving close collaboration between primes. Four case study networks are studied (aerospace, naval, power and telecoms), each involving equipment manufacture and service provision. Factors that support network integration, identified from the literature and refined in the in-depth pilot case, were used to explore which processes support integration of the extended enterprise. Results suggests that a select set of processes support integration of the extended enterprise and that the absence of a shared view on these critical enabling processes results from contextual complexity of the network rather than from competing commercial interests. Copyright © 2011 Inderscience Enterprises Ltd.

Extraction of fibre network architecture by X-ray tomography and prediction of elastic properties using an affine analytical model

This paper proposes a method for extracting reliable architectural characteristics from complex porous structures using micro-computed tomography (μCT) images. The work focuses on a highly porous material composed of a network of fibres bonded together. The segmentation process, allowing separation of the fibres from the remainder of the image, is the most critical step in constructing an accurate representation of the network architecture. Segmentation methods, based on local and global thresholding, were investigated and evaluated by a quantitative comparison of the architectural parameters they yielded, such as the fibre orientation and segment length (sections between joints) distributions and the number of inter-fibre crossings. To improve segmentation accuracy, a deconvolution algorithm was proposed to restore the original images. The efficacy of the proposed method was verified by comparing μCT network architectural characteristics with those obtained using high resolution CT scans (nanoCT). The results indicate that this approach resolves the architecture of these complex networks and produces results approaching the quality of nanoCT scans. The extracted architectural parameters were used in conjunction with an affine analytical model to predict the axial and transverse stiffnesses of the fibre network. Transverse stiffness predictions were compared with experimentally measured values obtained by vibration testing. © 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Evaluating the impacts of iteration on PD processes by transforming task network models into System Dynamics models

Iteration is unavoidable in the design process and should be incorporated when planning and managing projects in order to minimize surprises and reduce schedule distortions. However, planning and managing iteration is challenging because the relationships between its causes and effects are complex. Most approaches which use mathematical models to analyze the impact of iteration on the design process focus on a relatively small number of its causes and effects. Therefore, insights derived from these analytical models may not be robust under a broader consideration of potential influencing factors. In this article, we synthesize an explanatory framework which describes the network of causes and effects of iteration identified from the literature, and introduce an analytic approach which combines a task network modeling approach with System Dynamics simulation. Our approach models the network of causes and effects of iteration alongside the process architecture which is required to analyze the impact of iteration on design process performance. We show how this allows managers to assess the impact of changes to process architecture and to management levers which influence iterative behavior, accounting for the fact that these changes can occur simultaneously and can accumulate in non-linear ways. We also discuss how the insights resulting from this analysis can be visualized for easier consumption by project participants not familiar with simulation methods. Copyright © 2010 by ASME.

Managing global network operations along the engineering value chain

Purpose: This paper aims to improve understanding of how to manage global network operations from an engineering perspective. Design/methodology/approach: This research adopted a theory building approach based on case studies. Grounded in the existing literature, the theoretical framework was refined and enriched through nine in-depth case studies in the industry sectors of aerospace, automotives, defence and electrics and electronics. Findings: This paper demonstrates the main value creation mechanisms of global network operations along the engineering value chain. Typical organisational features to support the value creation mechanisms are captured, and the key issues in engineering network design and operations are presented with an overall framework. Practical implications: Evidenced by a series of pilot applications, outputs of this research can help companies to improve the performance of their current engineering networks and design new engineering networks to better support their global businesses and customers in a systematic way. Originality/value: Issues about the design and operations of global engineering networks (GEN) are poorly understood in the existing literature in contrast to their apparent importance in value creation and realisation. To address this knowledge gap, this paper introduces the concept of engineering value chain to highlight the potential of a value chain approach to the exploration of engineering activities in a complex business context. At the same time, it develops an overall framework for managing GEN along the engineering value chain. This improves our understanding of engineering in industrial value chains and extends the theoretical understanding of GEN through integrating the engineering network theories and the value chain concepts. © Emerald Group Publishing Limited.

An Infinite Latent Attribute Model for Network Data

Latent variable models for network data extract a summary of the relational structure underlying an observed network. The simplest possible models subdivide nodes of the network into clusters; the probability of a link between any two nodes then depends only on their cluster assignment. Currently available models can be classified by whether clusters are disjoint or are allowed to overlap. These models can explain a "flat" clustering structure. Hierarchical Bayesian models provide a natural approach to capture more complex dependencies. We propose a model in which objects are characterised by a latent feature vector. Each feature is itself partitioned into disjoint groups (subclusters), corresponding to a second layer of hierarchy. In experimental comparisons, the model achieves significantly improved predictive performance on social and biological link prediction tasks. The results indicate that models with a single layer hierarchy over-simplify real networks.

Defining product-service network configurations and location roles: A current and future state analysis framework for international engineering operations

Many manufacturing firms have developed a service dimension to their product portfolio. In response to this growing trend of servitisation, organisations, often involved in complex, long-lifecycle product-service system (PSS) provision, need to reconfigure their global engineering networks to support integrated PSS offerings. Drawing on parallel concepts in 'production' networks, the idea of 'location role' now becomes increasingly complex, in terms of service delivery. As new markets develop, locations in a specific region may need to grow/adapt engineering service 'competencies' along the value chain, from design and build to support and service, in order to serve future location-specific requirements and, potentially, those requirements of the overall network. The purpose of this paper is to advance understanding of how best to design complex multi-organisational engineering service networks, through extension of the 'production' network location role concept to a PSS context, capturing both traditional engineering 'design and build' and engineering 'service' requirements. Copyright © 2012 Inderscience Enterprises Ltd.

Single sublattice endotaxial phase separation driven by charge frustration in a complex oxide.

Complex transition-metal oxides are important functional materials in areas such as energy and information storage. The cubic ABO3 perovskite is an archetypal example of this class, formed by the occupation of small octahedral B-sites within an AO3 network defined by larger A cations. We show that introduction of chemically mismatched octahedral cations into a cubic perovskite oxide parent phase modifies structure and composition beyond the unit cell length scale on the B sublattice alone. This affords an endotaxial nanocomposite of two cubic perovskite phases with distinct properties. These locally B-site cation-ordered and -disordered phases share a single AO3 network and have enhanced stability against the formation of a competing hexagonal structure over the single-phase parent. Synergic integration of the distinct properties of these phases by the coherent interfaces of the composite produces solid oxide fuel cell cathode performance superior to that expected from the component phases in isolation.