The difficulties of the assessment of tool life in CNC milling

In the manufacturing process, tool life is an important parameter in milling operations. The main objective of this paper is to explain how difficult is it to assess how much work a tool has undertaken before it must be changed. A number of ways of expressing tool life are currently used, including the conventional method based upon one of several configurations of the Taylor Tool Life Equation. These usually express tool life in terms of known material properties together with primary machining variables like speed, feed and depth of cut. Other approaches are based upon the extrapolation of a tool wear curve and considerations of the volume of metal removed. This initial investigation adopts an approach that is based upon a series of experiments, which produce data indicating the changes in machined feature form and dimension. For this study, a new test piece was designed in order to allow the indirect assessment of the tool flank wear by utilising a Coordinate Measuring Machine to accurately measure the workpieces. This work is intended to indicate how difficult it is to actually apply the existing methods to manage tool wear. The aim is to engineer a better way and to establish a methodology of measuring what the tool is actually doing in real time using the machine controller

The development of a process charge expert system for a Basic Oxygen Steelmaking plant.

In an integrated steelworks the Basic Oxygen Steelmaking (BOS) process is required for the refining of molten iron from a blast furnace to produce steel. The development of an expert diagnostic system is considered in the context of the initial phase of BOS operation, the loading and operation of the BOS vessel. In this part of the steelmaking process the BOS vessel is charged with the molten iron, scrap metal and fluxes which are there to facilitate the capture of impurities by forming slag. The nature of the elements added requires knowledge of the steelmaking process, the actual state of the contents of the vessel and the available process management options. The expert system produced to oversee this process exhibits the capability of dealing with both continuous and batch data, combining the two together to aid effective decision making and management. Fuzzy inference is used in the main diagnostic system due to the large rule base required to diagnose faults and infer a process state. The operation of the system and its use by the process operators and the application of this approach into other areas of the steelworks is considered in this paper

Development and application of a process diagnostic system for the desulphurisation process

In an increasingly competitive steel industry, with ever-stricter grade requirements for sulphur, the requirement for improved control and efficiency is increasingly important to reduce process costs. This paper describes an online system that has been developed and implemented at Tata Steel Port Talbot Works, to monitor and report on the desulphurisation process. The aim of the system is to generate an objective report on the process, to highlight all process deviations and issues, and facilitate diagnosis. This diagnosis will improve process control and process efficiency. The desulphurisation process typically uses lime and magnesium to facilitate the removal of sulphur from the hot metal and into the slag where this is removed by a rabble. The process, with a start Hot Metal Sulphur of 0.045 (wt.%) and Aim Sulphur of 0.008 (wt.%) typically uses approximately 100kg magnesium and 300kg lime for a 300T ladle. The main focus of this system has been the development of linguistic outputs. The outputs have been optimised to provide concise and interoperable information to assist the operators to quickly understand the current state of the process. The system has been designed to monitor three areas regarding the desulphurisation process; model setup, process deviation and sample availability. A report is generated every morning, for use by shift and plant managers, highlighting every deviation in the process over the past 24 hours and diagnosis of the exact cause where possible. The report is compiled on an exception basis, only highlighting treatments providing there has been an issue or deviation from expected material usage

Damage detection of a PTFE liner matrix composite through the use of acoustic emission

Self-lubricating bearings are widely used within the aerospace industry and are commonly found in the pitch control assembly of rotorcraft and, as such, are critical parts due to their importance within the system. The dry lubricant present within these bearings acts as a consumable material which occupies the troughs of the inner race therefore forming a smooth sliding surface between inner and outer race via the deposition of third body particles. For this research the liner material is in the form of a woven composite, consisting of Polytetrafluoroethylene (PTFE) as the dry-lubricant and glass fibres as the reinforcing material, cured in a resin matrix. A cylinder-on-flat oscillating wear test bench developed within Cardiff University allowed for the gathering of physical data including temperature and Acoustic Emission (AE) signals during an accelerated wear test of the liner material. A radial load of 2.5 kN and oscillation frequency of 5Hz were applied to replicate typical operating conditions within a pitch control system. Frequency analysis techniques were carried out on the AE data, successfully identifying the transition from healthy contact into the failure region

Tidal Steam Turbine blade fault diagnosis using time-frequency analyses

Tidal Stream Turbines are developing renewable energy devices, for which proof of concept commercial devices are been deployed. The optimisation of such devices is supported by research activities. Operation within selected marine environments will lead to extreme dynamic loading and other problems. Further, such environments emphasise the need for condition monitoring and prognostics to support difficult maintenance activities. This paper considers flow and structural simulation research and condition monitoring evaluations. In particular, reduced turbine blade functionality will result in reduced energy production, long down times and potential damage to other critical turbine sub-assemblies. Local sea conditions and cyclic tidal variations along with shorter timescale dynamic fluctuations lead to the consideration of time-frequency methods. This paper initially reports on simulation and scale-model experimental testing of blade-structure interactions observed in the total axial thrust signal. The assessment is then extended to monitoring turbine blade and rotor condition, via drive shaft torque measurements. Parametric models are utilised and reported and a motor-drive train-generator test rig is described. The parametric models allow the generation of realistic time series used to drive this test rig and hence to evaluate the applicability of various time-frequency algorithms to the diagnosis of blade faults

Performance and condition monitoring of tidal stream turbines

Research within the Cardiff Marine Energy Research Group (CMERG) has considered the integrated mathematical modelling of Tidal Stream Turbines (TST). The modelling studies are briefly reviewed. This paper concentrates on the experimental validation testing of small TST models in a water flume facility. The dataset of results, and in particular the measured axial thrust signals are analysed via timefrequency methods. For the 0.5 m diameter TST the recorded angular velocity typically varies by ± 2.5% during the 90 second test durations. Modelling results confirm the expectations for the thrust signal spectrums, for both optimum and deliberately offset blade results. A discussion of the need to consider operating conditions, condition monitoring sub-system refinements and the direction of prognostic methods development, is provided

Performance and condition monitoring of tidal stream turbines

Research within the Cardiff Marine Energy Research Group (CMERG) has considered the integrated mathematical modelling of Tidal Stream Turbines (TST). The modelling studies are briefly reviewed. This paper concentrates on the experimental validation testing of small TST models in a water flume facility. The dataset of results, and in particular the measured axial thrust signals are analysed via timefrequency methods. For the 0.5 m diameter TST the recorded angular velocity typically varies by ± 2.5% during the 90 second test durations. Modelling results confirm the expectations for the thrust signal spectrums, for both optimum and deliberately offset blade results. A discussion of the need to consider operating conditions, condition monitoring sub-system refinements and the direction of prognostic methods development, is provided

A discussion of the prognostics and health management aspects of embedded condition monitoring systems

This paper presents a review of embedded condition monitoring research carried out at Cardiff University. A variety of application areas are described, along with a discussion of the evolution of the hardware platforms used. The current operating philosophies of the Intelligent Process Monitoring and Management (IPMM) research group and the deployed hierarchical and distributed architectures are described. The paper sets out to discuss the on-going trend towards such monitoring systems needing to provide more than fault detection and diagnostic capabilities. System requirements such as tracking operational settings, performance and efficiency measures and providing limp-home facilities are seen to be consistent with prognostics and health management ideals. The paper concludes with a discussion of new and future developments and application