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During miniaturisation, size of the part comes close to grain size of the material. There is an overall decrease in the total number grains undergoing deformation and most of these are surface grains. Therefore, microscale deformation is marked by abnormal stress-strain response which limits the manufacturing capabilities of microforming. Two distinct phenomena responsible for this are: (i) dominance of single crystal deformation behaviour, and (ii) increased strain localisation due to incompatibly between surface and core grains during deformation. The present work attempts to neutralise these effects by increasing the number of grains in the deformation zone. This has been achieved by engineering refined microstructure in the materials. To develop the refined microstructure, cryorolling followed by controlled annealing treatment has been employed. Microscale deformation behaviour and microforming capabilities of the refined material have been compared with its coarse-grained counterpart by analysing their tensile curves and by post-mortem study of micro deep drawn components over a wide range of sample thicknesses. Material with fully recrystallised, equiaxed, strain-free refined microstructure is found to have the best strain hardening response both in micro and macro deformation domains. This property is also reflected in the micro deep drawing capabilities of the same material.

The dynamic effect of machine tool errors leaves its signature on machined surfaces. This paper proposes an application of data dependent systems (DDS) methodology to recover this signature from the surfaces in a comprehensive manner and provides a realistic basis for machine-tool acceptance. The approach is illustrated by experimental results from three different lathes. It is shown that relative contributions due to the feed wavelength reveal the dynamic performance of the machine tools. The deviation from the nominal and the spread of the estimated feed wavelength quantify the accuracy and rigidity, the feed wavelength being precisely maintained with minimal spread in a machine tool with high accuracy and high rigidity. Presence of other wavelengths and their relative contribution to the RMS surface roughness serve as quantitative indicators of other machine tool errors.

Both feature recognition and reasoning are needed for automating manufacturing planning activities for 3D sheet metal components. The feature reasoning system proposed here generates manufacturing information (e.g. flat pattern, locations of various features, internal cuts and blank profiles, type of tools required, operation sequence, bending sequence, etc.) for the features recognized in Part I of this paper. The issues related to flat pattern developments as experienced while using commercial software have been addressed in this work. A tool selection approach that uses standard tools for single and multiple blow features in punch presses is suggested. A zigzag method for operation sequencing and a virtual bend sequencing system are included. The system has been tested with various components and the results are compatible with industrial practices. [ABSTRACT FROM AUTHOR]

Byline: M. Kanthababu, M.S. Shunmugam, M. Singaperumal Sensing Acoustic Emission (AE) signals from a machining process is one of the most promising methods suitable for tool condition monitoring because of its sensitivity combined with quick and high frequency response. In this work, AE signals are monitored during rough, finish and plateau honing of cylinder liner using fresh and completely worn out honing tools. AE parameters such as Root Mean Square (RMS), peak to peak, skewness and kurtosis and dominant frequency in the power spectrum are analysed. The results show that the dominant frequency in the power spectrum is very sensitive to honing tool conditions and a good correlation exists with honed surface quality. Therefore, AE signals can be used for ascertaining the honing tool performance and establishing the end of tool life.

Boring Trepanning Association (BTA) drills are capable of machining holes having large length to diameter ratio in a single pass. The study of the accuracy and surface finish of holes produced would reveal quite useful information regarding the process. This paper deals with the experimental results obtained during BTA drilling on EN-9 steel for different machining conditions. The data presented here are mainly on size variation, straightness of axis, out of roundness and surface finish. A different approach has been followed to study the error on the straightness of axis. [ABSTRACT FROM AUTHOR]