A matrix-calculation-based algorithm for numerical change propagation analysis

Engineering changes (ECs) are raised throughout the lifecycle of engineering products. A single change to one component produces knock-on effects on others necessitating additional changes. This change propagation significantly affects the development time and cost and determines the product's success. Predicting and managing such ECs is, thus, essential to companies. Some prediction tools model change propagation by algorithms, whereof a subgroup is numerical. Current numerical change propagation algorithms either do not account for the exclusion of cyclic propagation paths or are based on exhaustive searching methods. This paper presents a new matrix-calculation-based algorithm which can be applied directly to a numerical product model to analyze change propagation and support change prediction. The algorithm applies matrix multiplications on mutations of a given design structure matrix accounting for the exclusion of self-dependences and cyclic propagation paths and delivers the same results as the exhaustive search-based Trail Counting algorithm. Despite its factorial time complexity, the algorithm proves advantageous because of its straightforward matrix-based calculations which avoid exhaustive searching. Thereby, the algorithm can be implemented in established numerical programs such as Microsoft Excel which promise a wider application of the tools within and across companies along with better familiarity, usability, practicality, security, and robustness. © 1988-2012 IEEE.

Change propagation analysis in complex technical systems

Understanding how and why changes propagate during engineering design is critical because most products and systems emerge from predecessors and not through clean sheet design. This paper applies change propagation analysis methods and extends prior reasoning through examination of a large data set from industry including 41,500 change requests, spanning 8 years during the design of a complex sensor system. Different methods are used to analyze the data and the results are compared to each other and evaluated in the context of previous findings. In particular the networks of connected parent, child and sibling changes are resolved over time and mapped to 46 subsystem areas. A normalized change propagation index (CPI) is then developed, showing the relative strength of each area on the absorber-multiplier spectrum between -1 and +1. Multipliers send out more changes than they receive and are good candidates for more focused change management. Another interesting finding is the quantitative confirmation of the "ripple" change pattern. Unlike the earlier prediction, however, it was found that the peak of cyclical change activity occurred late in the program driven by systems integration and functional testing. Patterns emerged from the data and offer clear implications for technical change management approaches in system design. Copyright © 2007 by ASME.

No evidence for an item limit in change detection.

Change detection is a classic paradigm that has been used for decades to argue that working memory can hold no more than a fixed number of items ("item-limit models"). Recent findings force us to consider the alternative view that working memory is limited by the precision in stimulus encoding, with mean precision decreasing with increasing set size ("continuous-resource models"). Most previous studies that used the change detection paradigm have ignored effects of limited encoding precision by using highly discriminable stimuli and only large changes. We conducted two change detection experiments (orientation and color) in which change magnitudes were drawn from a wide range, including small changes. In a rigorous comparison of five models, we found no evidence of an item limit. Instead, human change detection performance was best explained by a continuous-resource model in which encoding precision is variable across items and trials even at a given set size. This model accounts for comparison errors in a principled, probabilistic manner. Our findings sharply challenge the theoretical basis for most neural studies of working memory capacity.

Bonding regimes of nitrogen in amorphous carbon

Nitrogen can have numerous effects on diamond-like carbon: it can dope, it can form the hypothetical superhard compound C3N4, or it can create fullerene-like bonding structures. We studied amorphous carbon nitrogen films deposited by a filtered cathodic vacuum arc as a function of nitrogen content, ion energy and deposition temperature. The incorporation of nitrogen from 10-2 to 10 at% was measured by secondary ion mass spectrometry and elastic recoil detection analysis and was found to vary slightly sublinearly with N2 partial pressure during deposition. In the doping regime from 0 to about 0.4% N, the conductivity changes while the sp3 content and optical gap remain constant. From 0.4 to approximately 10% N, existing sp2 sites condense into clusters and reduce the band gap. Nitrogen contents over 10% change the bonding from mainly sp3 to mainly sp2. Ion energies between 20 and 250 eV do not greatly modify this behaviour. Deposition at higher temperatures causes a sudden loss of sp3 bonding above about 150 °C. Raman spectroscopy and optical gap data show that existing sp2 sites begin to cluster below this temperature, and the clustering continues above this temperature. This transition is found to vary only weakly with nitrogen addition, for N contents below 10%.

Properties of amorphous carbon-silicon alloys deposited by a high plasma density source

The addition of silicon to hydrogenated amorphous carbon can have the advantageous effect of lowering the compressive stress, improving the thermal stability of its hydrogen, and maintaining a low friction coefficient up to high humidity. Most experiments to date have been on hydrogenated amorphous carbon-silicon alloys (a-C1-xSix:H) deposited by rf plasma enhanced chemical vapor deposition. This method gives alloys with sizeable hydrogen content and only moderate hardness. Here we use a high plasma density source known as the electron cyclotron wave resonance source to prepare films with higher sp3 content and lower hydrogen content. The composition and bonding in the alloys is determined by x-ray photoelectron spectroscopy, Rutherford backscattering, elastic recoil detection analysis, visible and ultraviolet (UV) Raman spectroscopy, infrared spectroscopy, and x-ray reflectivity. We find that it is possible to produce relatively hard, low stress, low friction, almost humidity insensitive a-C1-xSix:H alloys with a good optical transparency and a band gap well over 2.5 eV. The friction behavior and friction mechanism of these alloys are studied and compared with that of a-C:H, ta-C:H, and ta-C. We show how UV Raman spectroscopy allows the direct detection of Si-C, Si-Hx, and C-Hx vibrations, not seen in visible Raman spectra. © 2001 American Institute of Physics.

Hydrogen content estimation of hydrogenated amorphous carbon by visible Raman spectroscopy

In the present study, we report the hydrogen content estimation of the hydrogenated amorphous carbon (a-C:H) films using visible Raman spectroscopy in a fast and nondestructive way. Hydrogenated diamondlike carbon films were deposited by the plasma enhanced chemical vapor deposition, plasma beam source, and integrated distributed electron cyclotron resonance techniques. Methane and acetylene were used as source gases resulting in different hydrogen content and sp2/sp3 fraction. Ultraviolet-visible (UV-Vis) spectroscopic ellipsometry (1.5-5 eV) as well as UV-Vis spectroscopy were provided with the optical band gap (Tauc gap). The sp2/sp3 fraction and the hydrogen content were independently estimated by electron energy loss spectroscopy and elastic recoil detection analysis-Rutherford back scattering, respectively. The Raman spectra that were acquired in the visible region using the 488 nm line shows the superposition of Raman features on a photoluminescence (PL) background. The direct relationship of the sp2 content and the optical band gap has been confirmed. The difference in the PL background for samples of the same optical band gap (sp2 content) and different hydrogen content was demonstrated and an empirical relationship between the visible Raman spectra PL background slope and the corresponding hydrogen content was extracted. © 2004 American Institute of Physics.

Probabilistic computation in human perception under variability in encoding precision.

A key function of the brain is to interpret noisy sensory information. To do so optimally, observers must, in many tasks, take into account knowledge of the precision with which stimuli are encoded. In an orientation change detection task, we find that encoding precision does not only depend on an experimentally controlled reliability parameter (shape), but also exhibits additional variability. In spite of variability in precision, human subjects seem to take into account precision near-optimally on a trial-to-trial and item-to-item basis. Our results offer a new conceptualization of the encoding of sensory information and highlight the brain's remarkable ability to incorporate knowledge of uncertainty during complex perceptual decision-making.