The effects of solid contamination in hydraulic fluids on axial piston pumps

The fluids used in hydraulic systems inevitably contain large numbers of small, solid particles, a phenomenon known as 'fluid contamination'. Particles enter a hydraulic system from the environment, and are generated within it by processes of wear. At the same time, particles are removed from the system fluid by sedimentation and in hydraulic filters. This thesis considers the problems caused by fluid contamination, as they affect a manufacturer of axial piston pumps. The specific project aim was to investigate methods of predicting or determining the effects of fluid contamination on this type of pump. The thesis starts with a theoretical analysis of the contaminated lubrication of a slipper-pad bearing. Statistical methods are used to develop a model of the blocking, by particles, of the control capillaries used in such bearings. The results obtained are compared to published, experimental data. Poor correlation between theory and practice suggests that more research is required in this area before such theoretical analysis can be used in industry. Accelerated wear tests have been developed in the U.S.A. in an attempt to predict pump life when operating on contaminated fluids. An analysis of such tests shows that reliability data can only be obtained from extensive test programmes. The value of contamination testing is suggested to be in determining failure modes, and in identifying those pump components which are susceptible to the effects of contamination. A suitable test is described, and the results of a series of tests on axial piston pumps are presented and discussed. The thesis concludes that pump reliability data can only be obtained from field experience. The level of confidence which can be placed in results from normal laboratory testing is shown to be too low for the data to be of real value. Recommendations are therefore given for the ways in which service data should be collected and analysed.

Priority evaluation in transportation policies and programmes

This work is concerned with the development of techniques for the evaluation of large-scale highway schemes with particular reference to the assessment of their costs and benefits in the context of the current transport planning (T.P.P.) process. It has been carried out in close cooperation with West Midlands County Council, although its application and results are applicable elsewhere. The background to highway evaluation and its development in recent years has been described and the emergence of a number of deficiencies in current planning practise noted. One deficiency in particular stood out, that stemming from inadequate methods of scheme generation and the research has concentrated upon improving this stage of appraisal, to ensure that subsequent stages of design, assessment and implementation are based upon a consistent and responsive foundation. Deficiencies of scheme evaluation were found to stem from inadequate development of appraisal methodologies suffering from difficulties of valuation, measurement and aggregation of the disparate variables that characterise highway evaluation. A failure to respond to local policy priorities was also noted. A 'problem' rather than 'goals' based approach to scheme generation was taken, as it represented the current and foreseeable resource allocation context more realistically. A review of techniques with potential for highway problem based scheme generation, which would work within a series of practical and theoretical constraints were assessed and that of multivariate analysis, and classical factor analysis in particular, was selected, because it offerred considerable application to the difficulties of valuation, measurement and aggregation that existed. Computer programs were written to adapt classical factor analysis to the requirements of T.P.P. highway evaluation, using it to derive a limited number of factors which described the extensive quantity of highway problem data. From this, a series of composite problem scores for 1979 were derived for a case study area of south Birmingham, based upon the factorial solutions, and used to assess highway sites in terms of local policy issues. The methodology was assessed in the light of its ability to describe highway problems in both aggregate and disaggregate terms, to guide scheme design, coordinate with current scheme evaluation methods, and in general to improve upon current appraisal. Analysis of the results was both in subjective, 'common-sense' terms and using statistical methods to assess the changes in problem definition, distribution and priorities that emerged. Overall, the technique was found to improve upon current scheme generation methods in all respects and in particular in overcoming the problems of valuation, measurement and aggregation without recourse to unsubstantiated and questionable assumptions. A number of deficiencies which remained have been outlined and a series of research priorities described which need to be reviewed in the light of current and future evaluation needs.

Comparing methods to separate treatment from self-selection effects in an online banking setting

The literature discusses several methods to control for self-selection effects but provides little guidance on which method to use in a setting with a limited number of variables. The authors theoretically compare and empirically assess the performance of different matching methods and instrumental variable and control function methods in this type of setting by investigating the effect of online banking on product usage. Hybrid matching in combination with the Gaussian kernel algorithm outperforms the other methods with respect to predictive validity. The empirical finding of large self-selection effects indicates the importance of controlling for these effects when assessing the effectiveness of marketing activities.

The classification of HLA supertypes by GRID/CPCA and hierarchical clustering methods

Biological experiments often produce enormous amount of data, which are usually analyzed by data clustering. Cluster analysis refers to statistical methods that are used to assign data with similar properties into several smaller, more meaningful groups. Two commonly used clustering techniques are introduced in the following section: principal component analysis (PCA) and hierarchical clustering. PCA calculates the variance between variables and groups them into a few uncorrelated groups or principal components (PCs) that are orthogonal to each other. Hierarchical clustering is carried out by separating data into many clusters and merging similar clusters together. Here, we use an example of human leukocyte antigen (HLA) supertype classification to demonstrate the usage of the two methods. Two programs, Generating Optimal Linear Partial Least Square Estimations (GOLPE) and Sybyl, are used for PCA and hierarchical clustering, respectively. However, the reader should bear in mind that the methods have been incorporated into other software as well, such as SIMCA, statistiXL, and R.

Enhanced process verification through re-engineering the manufacturing procedure

In today’s modern manufacturing industry there is an increasing need to improve internal processes to meet diverse client needs. Process re-engineering is an important activity that is well understood by industry but its rate of application within small to medium size enterprises (SME) is less developed. Business pressures shift the focus of SMEs toward winning new projects and contracts rather than developing long-term, sustainable manufacturing processes. Variations in manufacturing processes are inevitable, but the amount of non-conformity often exceeds the acceptable levels. This paper is focused on the re-engineering of the manufacturing and verification procedure for discrete parts production with the aim of enhancing process control and product verification. The ideologies of the ‘Push’ and ‘Pull’ approaches to manufacturing are useful in the context of process re-engineering for data improvement. Currently information is pulled from the market and prominent customers, and manufacturing companies always try to make the right product, by following customer procedures that attempt to verify against specifications. This approach can result in significant quality control challenges. The aim of this paper is to highlight the importance of process re-engineering in product verification in SMEs. Leadership, culture, ownership and process management are among the main attributes required for the successful deployment of process re-engineering. This paper presents the findings from a case study showcasing the application of a modified re-engingeering method for the manufacturing and verification process. The findings from the case study indicate there are several advantages to implementing the re-engineering method outlined in this paper.

The effects of material variations in high value manufacturing industries

It has never been easy for manufacturing companies to understand their confidence level in terms of how accurate and to what degree of flexibility parts can be made. This brings uncertainty in finding the most suitable manufacturing method as well as in controlling their product and process verification systems. The aim of this research is to develop a system for capturing the company’s knowledge and expertise and then reflect it into an MRP (Manufacturing Resource Planning) system. A key activity here is measuring manufacturing and machining capabilities to a reasonable confidence level. For this purpose an in-line control measurement system is introduced to the company. Using SPC (Statistical Process Control) not only helps to predict the trend in manufacturing of parts but also minimises the human error in measurement. Gauge R&R (Repeatability and Reproducibility) study identifies problems in measurement systems. Measurement is like any other process in terms of variability. Reducing this variation via an automated machine probing system helps to avoid defects in future products.Developments in aerospace, nuclear, oil and gas industries demand materials with high performance and high temperature resistance under corrosive and oxidising environments. Superalloys were developed in the latter half of the 20th century as high strength materials for such purposes. For the same characteristics superalloys are considered as difficult-to-cut alloys when it comes to formation and machining. Furthermore due to the sensitivity of superalloy applications, in many cases they should be manufactured with tight tolerances. In addition superalloys, specifically Nickel based, have unique features such as low thermal conductivity due to having a high amount of Nickel in their material composition. This causes a high surface temperature on the work-piece at the machining stage which leads to deformation in the final product.Like every process, the material variations have a significant impact on machining quality. The main cause of variations can originate from chemical composition and mechanical hardness. The non-uniform distribution of metal elements is a major source of variation in metallurgical structures. Different heat treatment standards are designed for processing the material to the desired hardness levels based on application. In order to take corrective actions, a study on the material aspects of superalloys has been conducted. In this study samples from different batches of material have been analysed. This involved material preparation for microscopy analysis, and the effect of chemical compositions on hardness (before and after heat treatment). Some of the results are discussed and presented in this paper.