The future of lean construction: a brave new world

Lean construction is considered from a human resource management (HRM) perspective. It is contended that the UK construction sector is characterised by an institutionalised regressive approach to HRM. In the face of rapidly declining recruitment rates for built environment courses, the dominant HRM philosophy of utilitarian instrumentalism does little to attract the intelligent and creative young people that the industry so badly needs. Given this broader context, there is a danger that an uncritical acceptance of lean construction will exacerbate the industry's reputation for unrewarding jobs. Construction academics have strangely ignored the extensive literature that equates lean production to a HRM regime of control, exploitation and surveillance. The emphasis of lean thinking on eliminating waste and improving efficiency makes it easy to absorb into the best practice agenda because it conforms to the existing dominant way of thinking. 'Best practice' is seemingly judged by the extent to which it serves the interests of the industry's technocratic elite. Hence it acts as a conservative force in favour of maintaining the status quo. In this respect, lean construction is the latest manifestation of a long established trend. In common with countless other improvement initiatives, the rhetoric is heavy in the machine metaphor whilst exhorting others to be more efficient. If current trends in lean construction are extrapolated into the future the ultimate destination may be uncomfortably close to Aldous Huxley's apocalyptic vision of a Brave New World. In the face of these trends, the lean construction research community pleads neutrality whilst confining its attention to the rational high ground. The future of lean construction is not yet predetermined. Many choices remain to be made. The challenge for the research community is to improve practice whilst avoiding the dehumanising tendencies of high utilitarianism.

State estimation using model order reduction for unstable systems

The problem of state estimation occurs in many applications of fluid flow. For example, to produce a reliable weather forecast it is essential to find the best possible estimate of the true state of the atmosphere. To find this best estimate a nonlinear least squares problem has to be solved subject to dynamical system constraints. Usually this is solved iteratively by an approximate Gauss–Newton method where the underlying discrete linear system is in general unstable. In this paper we propose a new method for deriving low order approximations to the problem based on a recently developed model reduction method for unstable systems. To illustrate the theoretical results, numerical experiments are performed using a two-dimensional Eady model – a simple model of baroclinic instability, which is the dominant mechanism for the growth of storms at mid-latitudes. It is a suitable test model to show the benefit that may be obtained by using model reduction techniques to approximate unstable systems within the state estimation problem.