Improving Workplace Expertise to Meet Increasing Customer Requirements: The Impact of Training

This article focuses upon the training of engineers at a factory producing integrated circuits. Inadequate use of statistical process techniques by the engineers meant that the production process was not being optimised in the context of increasing customer requirements. A training needs analysis was undertaken and a training programme was developed, implemented and evaluated. The results of this programme are presented and conclusions drawn

Quiescent thermal emission from neutron stars in LMXBs

We monitored the quiescent thermal emission from neutron stars in low-mass X-ray binaries after active periods of intense activity in x-rays (outbursts). The theoretical modeling of the thermal relaxation of the neutron star crust may be used to establish constraints on the crust composition and transport properties, depending on the astrophysical scenarios assumed. We numerically simulated the thermal evolution of the neutron star crust and compared them with inferred surface temperatures for five sources: MXB 1659-29, KS 1731-260, EXO 0748-676, XTE J1701-462 and IGR J17480-2446. We find that the evolution of MXB 1659-29, KS 1731-260 and EXO 0748-676 can be well described within a deep crustal cooling scenario. Conversely, we find that the other two sources can only be explained with models beyond crustal cooling. For the peculiar emission of XTE J1701-462 we propose alternative scenarios such as residual accretion during quiescence, additional heat sources in the outer crust, and/or thermal isolation of the inner crust due to a buried magnetic field. We also explain the very recent reported temperature of IGR J17480-2446 with an additional heat deposition in the outer crust from shallow sources.Comment: 19 pages, 32 figures, 2 Append., revised version accepted for publication in Astronomy & Astrophysic

Rational characteristic functions and markov chains

Abstract 1 We investigate in this paper how to estimate the density function of a random variable using a parametric ARMA model for its characteristic function. The choice of this model is motivated by the fact that this type of density characterizes the duration of staying at an N-states Markov chain, but the approach is general enough to be applied to many practical problems. Both ML and moment-based linear estimates are derived, the former being based on the optimization of a highly non-linear function. 1.Peer ReviewedPostprint (published version