Performance measurement and benchmarking of a major innovation programme

Purpose: The purpose of this paper is to describe the problems encountered and the solutions developed when using benchmarking and key performance indicators (KPIs) to monitor a major UK social house building innovation (change) programme. The innovation programme sought improvements to both the quality of the house product and the procurement process. Design/methodology/approach: Benchmarking and KPIs were used to quantify performance and in-depth case studies to identify underlying cause and effect relationships within the innovation programme. Findings: The inherent competition between consortium members; the complexity of the relationship between the consortium and its strategic partner; the lack of an authoritative management control structure; and the rapidly changing nature of the UK social housing market all proved problematic to the development of a reliable and robust monitoring system. These problems were overcome by the development of multi-dimensional benchmarking model that balanced the needs and aspirations of the individual organisations with the broader objectives of the consortium. Research limitations/implications: Whilst the research methodology provides insight into the factors that affected the performance of a major innovation programme its findings may not be representative of all projects. Practical implications: The lessons learnt should assist those developing benchmarking models for multi-client consortia. Originality/value: The work reported in this paper describes an inclusive approach to benchmarking in which a multiple client group and their strategic partner sought to work together for shared gain. Very few papers have addressed this issue.

Investigation into the performance of turbulence models for fluid flow and heat transfer phenomena in electronic applications

Computational Fluid Dynamics (CFD) is gradually becoming a powerful and almost essential tool for the design, development and optimization of engineering applications. However the mathematical modelling of the erratic turbulent motion remains the key issue when tackling such flow phenomena. The reliability of CFD analysis depends heavily on the turbulence model employed together with the wall functions implemented. In order to resolve the abrupt changes in the turbulent energy and other parameters situated at near wall regions a particularly fine mesh is necessary which inevitably increases the computer storage and run-time requirements. Turbulence modelling can be considered to be one of the three key elements in CFD. Precise mathematical theories have evolved for the other two key elements, grid generation and algorithm development. The principal objective of turbulence modelling is to enhance computational procedures of efficient accuracy to reproduce the main structures of three dimensional fluid flows. The flow within an electronic system can be characterized as being in a transitional state due to the low velocities and relatively small dimensions encountered. This paper presents simulated CFD results for an investigation into the predictive capability of turbulence models when considering both fluid flow and heat transfer phenomena. Also a new two-layer hybrid kε / kl turbulence model for electronic application areas will be presented which holds the advantages of being cheap in terms of the computational mesh required and is also economical with regards to run-time.

Application of simulation technologies in the analysis of granular material behaviour during transport and storage

Problems in the preservation of the quality of granular material products are complex and arise from a series of sources during transport and storage. In either designing a new plant or, more likely, analysing problems that give rise to product quality degradation in existing operations, practical measurement and simulation tools and technologies are required to support the process engineer. These technologies are required to help in both identifying the source of such problems and then designing them out. As part of a major research programme on quality in particulate manufacturing computational models have been developed for segregation in silos, degradation in pneumatic conveyors, and the development of caking during storage, which use where possible, micro-mechanical relationships to characterize the behaviour of granular materials. The objective of the work presented here is to demonstrate the use of these computational models of unit processes involved in the analysis of large-scale processes involving the handling of granular materials. This paper presents a set of simulations of a complete large-scale granular materials handling operation, involving the discharge of the materials from a silo, its transport through a dilute-phase pneumatic conveyor, and the material storage in a big bag under varying environmental temperature and humidity conditions. Conclusions are drawn on the capability of the computational models to represent key granular processes, including particle size segregation, degradation, and moisture migration caking.

Modelling technologies and applications

Numerical modelling technology and software is now being used to underwrite the design of many microelectronic and microsystems components. The demands for greater capability of these analysis tools are increasing dramatically, as the user community is faced with the challenge of producing reliable products in ever shorter lead times. This leads to the requirement for analysis tools to represent the interactions amongst the distinct phenomena and physics at multiple length and timescales. Multi-physics and Multi-scale technology is now becoming a reality with many code vendors. This chapter discusses the current status of modelling tools that assess the impact of nano-technology on the fabrication/packaging and testing of microsystems. The chapter is broken down into three sections: Modelling Technologies, Modelling Application to Fabrication, and Modelling Application to Assembly/Packing and Modelling Applied for Test and Metrology.

Numerical and experimental studies of a substructural identification strategy

For structural health monitoring it is impractical to identify a large structure with complete measurement due to limited number of sensors and difficulty in field instrumentation. Furthermore, it is not desirable to identify a large number of unknown parameters in a full system because of numerical difficulty in convergence. A novel substructural strategy was presented for identification of stiffness matrices and damage assessment with incomplete measurement. The substructural approach was employed to identify large systems in a divide-and-conquer manner. In addition, the concept of model condensation was invoked to avoid the need for complete measurement, and the recovery process to obtain the full set of parameters was formulated. The efficiency of the proposed method is demonstrated numerically through multi-storey shear buildings subjected to random force. A fairly large structural system with 50 DOFs was identified with good results, taking into consideration the effects of noisy signals and the limited number of sensors. Two variations of the method were applied, depending on whether the sensor could be repositioned. The proposed strategy was further substantiated experimentally using an eight-storey steel plane frame model subjected to shaker and impulse hammer excitations. Both numerical and experimental results have shown that the proposed substructural strategy gave reasonably accurate identification in terms of locating and quantifying structural damage.

The missing link between information and action: hastenings and delays as universal reactions to performance feedback

This chapter focuses on what the key decision makers in organizations decide after having received information on the current state of the organizational performance. Because of strong attributions to success and failure, it is impossible to predict in advance which concrete actions will occur. We can however find out what kinds of actions are decided upon by means of an organizational learning model that focuses on the hastenings and delays after performance feedback. As an illustration, the responses to performance signals by trainers and club owners in Dutch soccer clubs are analyzed.

Modelling the effect of temperature on product reliability

Reliability of electronic parts is a major concern for many manufacturers, since early failures in the field can cost an enormous amount to repair - in many cases far more than the original cost of the product. A great deal of effort is expended by manufacturers to determine the failure rates for a process or the fraction of parts that will fail in a period of time. It is widely recognized that the traditional approach to reliability predictions for electronic systems are not suitable for today's products. This approach, based on statistical methods only, does not address the physics governing the failure mechanisms in electronic systems. This paper discusses virtual prototyping technologies which can predict the physics taking place and relate this to appropriate failure mechanisms. Simulation results illustrate the effect of temperature on the assembly process of an electronic package and the lifetime of a flip-chip package.