Discussion: Widening engineering horizons: Addressing the complexity of sustainable development

The following discussion is from an Institution of Civil Engineers (ICE) prestige lecture based on the original paper and delivered by the authors at the ICE in London on 24 September 2008.1 The event was chaired by Engineering Sustainability editorial panel chair, Professor Chris Rogers from Birmingham University. It was attended by an audience of 130 people as well as being watched by a similar number over a live web-cast. The web-cast can be accessed from the ICE archive for online viewing at http://scenta. interwise.com/etechb/ OnDemand/TH6509.

Impacts of concurrency, iteration, design review, and problem complexity on design project lead time and error generation

A case study of an aircraft engine manufacturer is used to analyze the effects of management levers on the lead time and design errors generated in an iteration-intensive concurrent engineering process. The levers considered are amount of design-space exploration iteration, degree of process concurrency, and timing of design reviews. Simulation is used to show how the ideal combination of these levers can vary with changes in design problem complexity, which can increase, for instance, when novel technology is incorporated in a design. Results confirm that it is important to consider multiple iteration-influencing factors and their interdependencies to understand concurrent processes, because the factors can interact with confounding effects. The article also demonstrates a new approach to derive a system dynamics model from a process task network. The new approach could be applied to analyze other concurrent engineering scenarios. © The Author(s) 2012.

Disentangling the Complexity of Early-Stage Technology Acquisitions

While tools have been developed to assist firms' decision making for bringing known products and components into the supply chain, fewer tools are available to guide the acquisition of earlier-stage technologies, which is a riskier proposition due to higher technological and market uncertainties. Through synthesis of literature in technology sourcing, open innovation, alliances, mergers and acquisitions, outsourcing, and technology and knowledge transfer and consultation with industry, this paper identifies critical issues that decision makers should consider before making an early-stage technology acquisition. Sixteen questions emerge to guide decision making, comprising internal, technology, and partner assessments. These questions allow a firm to disentangle the complexity of early-stage technology acquisitions and select the most appropriate targets.

Random function priors for exchangeable arrays with applications to graphs and relational data

A fundamental problem in the analysis of structured relational data like graphs, networks, databases, and matrices is to extract a summary of the common structure underlying relations between individual entities. Relational data are typically encoded in the form of arrays; invariance to the ordering of rows and columns corresponds to exchangeable arrays. Results in probability theory due to Aldous, Hoover and Kallenberg show that exchangeable arrays can be represented in terms of a random measurable function which constitutes the natural model parameter in a Bayesian model. We obtain a flexible yet simple Bayesian nonparametric model by placing a Gaussian process prior on the parameter function. Efficient inference utilises elliptical slice sampling combined with a random sparse approximation to the Gaussian process. We demonstrate applications of the model to network data and clarify its relation to models in the literature, several of which emerge as special cases.

A method for analysing operational complexity in supply chains

This paper proposes a method for analysing the operational complexity in supply chains by using an entropic measure based on information theory. The proposed approach estimates the operational complexity at each stage of the supply chain and analyses the changes between stages. In this paper a stage is identified by the exchange of data and/or material. Through analysis the method identifies the stages where the operational complexity is both generated and propagated (exported, imported, generated or absorbed). Central to the method is the identification of a reference point within the supply chain. This is where the operational complexity is at a local minimum along the data transfer stages. Such a point can be thought of as a 'sink' for turbulence generated in the supply chain. Where it exists, it has the merit of stabilising the supply chain by attenuating uncertainty. However, the location of the reference point is also a matter of choice. If the preferred location is other than the current one, this is a trigger for management action. The analysis can help decide appropriate remedial action. More generally, the approach can assist logistics management by highlighting problem areas. An industrial application is presented to demonstrate the applicability of the method. © 2013 Operational Research Society Ltd. All rights reserved.