Process improvement within a HR division at a UK police force

A structured approach to process improvement is described in the context of the human resources division of a UK police force. The approach combines a number of established techniques of process improvement such as the balanced scorecard and process mapping with a scoring system developed to prioritise processes for improvement. The methodology described presents one way of ensuring the correct processes are identified and redesigned at an operational level in such a way as to support the organisation's strategic aims. In addition, a performance measurement system is utilised to attempt to ensure that the changes implemented do actually achieve the desired effect over time. The case demonstrates the need to choose and in some cases develop in-house tools and techniques dependent on the context of the process improvement effort.

Force sensing for measuring human body movement

The research developed in this thesis explores the sensing and inference of human movement in a dynamic way, as opposed to conventional measurement systems, that are only concerned with discrete evaluations of stimuli in sequential time. Typically, conventional approaches are used to infer the dynamic movement of the body; such as vision and motion tracking devices, with either a human diagnosis or complex image processing algorithm to classify the movement. This research is therefore the first of its kind to attempt and provide a movement classifying algorithm through the use of minimal sensing points, with the application for this novel system, to classify human movement during a golf swing. There are two main categories of force sensing. Firstly, array-type systems consisting of many sensing elements, and are the most commonly researched and commercially available. Secondly, reduced force sensing element systems (RFSES) also known as distributive systems have only been recently exploited in the academic world. The fundamental difference between these systems is that array systems handle the data captured from each sensor as unique outputs and suffer the effects of resolution. The effect of resolution, is the error in the load position measurement between sensing elements, as the output is quantized in terms of position. This can be compared to a reduced sensor element system that maximises that data received through the coupling of data from a distribution of sensing points to describe the output in discrete time. Also this can be extended to a coupling of transients in the time domain to describe an activity or dynamic movement. It is the RFSES that is to be examined and exploited in the commercial sector due to its advantages over array-based approaches such as reduced design, computational complexity and cost.

Influence of macroscopic residual stress fields on fatigue crack growth measurement in SiC particulate reinforced 8090 aluminium alloy

The effect of residual stresses, induced by cold water quenching, on the morphology of fatigue crack fronts has been investigated in a powder metallurgy 8090 aluminium alloy, with and without reinforcement in the form of 20 wt-%SiC particles. Residual stress measurements reveal that the surface compressive stresses developed in these materials are significantly greater than in conventional metallurgy ingot 8090, because surface yielding occurs on quenching. The yield stresses of the powder route materials are greater than those of ingot produced 8090 and hence greater surface stresses can be maintained. In fatigue, severe crack front bowing is observed in the powder formed materials as a result of the reduction of the R ratio (minimum load/maximum load) by the compressive residual stresses at the sides of the specimen, causing premature crack closure and hence reducing the local driving force for fatigue crack growth ΔKeff. This distortion of the crack fronts introduces large errors into measurements of crack growth rate and threshold values of ΔK.

A hybrid measurement systems analysis and uncertainty of measurement approach for industrial measurement in the light controlled factory

The uncertainty of measurements must be quantified and considered in order to prove conformance with specifications and make other meaningful comparisons based on measurements. While there is a consistent methodology for the evaluation and expression of uncertainty within the metrology community industry frequently uses the alternative Measurement Systems Analysis methodology. This paper sets out to clarify the differences between uncertainty evaluation and MSA and presents a novel hybrid methodology for industrial measurement which enables a correct evaluation of measurement uncertainty while utilising the practical tools of MSA. In particular the use of Gage R&R ANOVA and Attribute Gage studies within a wider uncertainty evaluation framework is described. This enables in-line measurement data to be used to establish repeatability and reproducibility, without time consuming repeatability studies being carried out, while maintaining a complete consideration of all sources of uncertainty and therefore enabling conformance to be proven with a stated level of confidence. Such a rigorous approach to product verification will become increasingly important in the era of the Light Controlled Factory with metrology acting as the driving force to achieve the right first time and highly automated manufacture of high value large scale products such as aircraft, spacecraft and renewable power generation structures.