Survey on the status of Computational Design research and practice

This report presents the results from a survey of current practice in the use of design optimization conducted amongst UK companies. The survey was completed by the Design Optimization Group in the Department of Engineering at Cambridge University. The general aims of this research were to understand the current status of design optimization research and practice and to identify ways in which the use of design optimization methods and tools could be improved.

Improving design quality and value in the built environment through knowledge of intangibles

Raising design quality and value in the built environment requires continuous improvement, drawing on feedback from clients or occupiers and other industry players. The challenging task for architectural and engineering designers has always been to use their intellectual knowledge to deliver both forms of benefits, tangibles and intangibles, in the built environment. Increasingly as clients demand best value for money, there is a greater need to understand the potential from intangibles, to see projects not as ends in themselves but as means to improved quality of life and wealth creation. As we begin to understand more about how - through the design of the built environment - to deliver these improvements in outcomes, clients will be better placed to expect their successful delivery from designers, and designers themselves will be better placed to provide them. This paper discusses cross-disciplinary issues about intangibles and is aimed at designers, clients, investors and entrepreneurs within the built environment. It presents some findings from a minuscule study that investigated intangible benefits in a new primary school. © 2004 IEEE.

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.