2018
DOI: 10.1016/j.measurement.2018.07.059
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A novel use of multivariate statistics to diagnose test-to-test variation in complex measurement systems

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Cited by 5 publications
(4 citation statements)
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“…performance curves). Thanks to engine and vehicle tests, the measured values such as economy, power, moment, emission are compared with performance curves [7][8][9]. The unbalanced distribution of fossil fuels, which make up the largest part of primary energy resources, has caused some disadvantageous countries to become dependent on advantageous countries.…”
Section: Introductionmentioning
confidence: 99%
“…performance curves). Thanks to engine and vehicle tests, the measured values such as economy, power, moment, emission are compared with performance curves [7][8][9]. The unbalanced distribution of fossil fuels, which make up the largest part of primary energy resources, has caused some disadvantageous countries to become dependent on advantageous countries.…”
Section: Introductionmentioning
confidence: 99%
“…We began to realize that our solution must be reliable, while not generating high costs for the measurement itself. The inspiration for achieving such a result was the study by [43], where, based on large datasets, the authors successfully analyzed them without reducing the volume unnecessarily. Thus, they achieved satisfactory results, similar to those obtained in [44], for the case of turbine shaft torque.…”
Section: Introductionmentioning
confidence: 99%
“…Changing the decision maker's assumptions can also significantly impact the nature of scenarios and decision outcomes hence methods employed by decision-makers should allow for sensitivity analysis to be incorporated. Moreover, CO 2 emission problems typically rely on non-linear models which involve highly correlated data, where detecting the specific variables which cause variations in results can be challenging to differentiate (Burke et al, 2018). One way to overcome the complexity of correlated data is to break down the problem into smaller sub-problems to sequentially solve (Qiao et al, 2017).…”
mentioning
confidence: 99%
“…Additionally, the other decision criteria considered in Section 3.4, included design configuration, fuel consumption and electricity consumption, product speed, voltage, external humidity and temperature during testing (Burke et al, 2018) plus the type of fuel used, fuel price and CO 2 reduction targets (Lee & Hashim, 2014). The possible explanation for the wide range of different criteria utilised in the literature, in comparison to the criteria adopted in the proposed decision support model, is likely due to the usage of the different terminology used across the industry to express the same criteria.…”
mentioning
confidence: 99%