Delamination and wear in drilling of carbon-fiber reinforced plastic composites using multilayer TiAlN/TiN PVD-coated tungsten carbide tools

This study aims to investigate drilling process in carbon-fiber reinforced plastic (CFRP) composites with multilayer TiAlN/TiN PVD-coated tungsten carbide drill. The effect of process parameters have been investigated in drilling of Hexcel M21-T700GC. Thrust force and torque were measured online throughout the drilling experiments. Delamination were observed using optical microscope and analyzed via a developed algorithm based on digital image processing technique. Surface roughness of each hole was measured using a surface profilometer. In addition, the progression of tool wear in various surfaces of drill was observed using tool microscope and measured using image software. Our results indicate that the thrust force and torque increased with the increasing cutting speed and feed rate. Delamination and average surface roughness that rose with the increase in feed rate, however, decreased with the increasing cutting speed. The average surface roughness tended to increase with the increase in feed rate and decrease with the increasing cutting speed in drilling of carbon-fiber reinforced plastic (CFRP). Feed rate was found as the predominant factor on the drilling outputs. Abrasive wear was observed on both flank and relief surfaces, which created edge wear on cutting edges. No sign of chipping or plastic deformation has been observed on the surfaces of drills. © 2012 The Author(s).

Performance management systems and Public Value Strategy: a case study

Purpose
This article aims to analyze the role of performance management systems (PMS) in supporting public value strategies.

Design/methodology/approach
This article draws on the public value dynamic model by Horner and Hutton (2010). It presents the results of a case study of implementation of a PMS model, the ‘Value Pyramid’ (VP).

Findings
The results stress the need for an improved conceptualization of PMS within public value strategy. Through experimentation using the VP, the case site was able to measure and visualize what it considered public value and reflect on the internal/external causes of both creation and destruction of public value.

Research limitations/implication
This article is limited to just one case study, although in-depth and longitudinal.

Originality/value
This article is one of the first attempting to understand the role of PMS within the public value strategy framework, answering the call of Benington and Moore (2010) to consider public value from an accounting perspective.

Semi batch learning with store management using enhanced conjugate gradient

This paper explores the performance of sliding-window based training, termed as semi batch, using multilayer perceptron (MLP) neural network in the presence of correlated data. The sliding window training is a form of higher order instantaneous learning strategy without the need of covariance matrix, usually employed for modeling and tracking purposes. Sliding-window framework is implemented to combine the robustness of offline learning algorithms with the ability to track online the underlying process of a function. This paper adopted sliding window training with recent advances in conjugate gradient direction with application of data store management e.g. simple distance measure, angle evaluation and the novel prediction error test. The simulation results show the best convergence performance is gained by using store management techniques. © 2012 Springer-Verlag.