Robust Control Charts for Time Series Data

Croux, Christophe; Gelper, Sarah; Mahieu, Koen

doi:10.2139/ssrn.1588646

Cited by 1 publication

(2 citation statements)

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“…To quantitatively identify abnormal behaviour in the fluctuation of a time-series, a standard procedure is the following: (1) model the time series to be monitored; (2) monitor model residuals, through an appropriate control chart (Croux, Gelper & Mahieu, 2011;Montgomery, 2005). We developed a custom-made statistical tool based upon Holt-Winters filtering and a robust control chart (Lutz, Roustant & Boucher, 2011).…”

Section: 222mentioning

confidence: 99%

“…Ideally, the final outcome of our work would be the design of an IT capacity knowledge-based Decision Support System (DSS), inspired by Arinze et al (1992) First of all, despite the fact that the control chart used is robust to outliers, this is not the case for the underlying Holt-Winters smoothing. That is why the development and testing of a robust Holt-Winters algorithm (Croux et al, 2011), less sensitive to exceptional events, is under way. Secondly, the statistical controls are performed independently from one another.…”

Section: Future Research and Conclusionmentioning

confidence: 99%

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Methods and applications for IT capacity decisions: Bringing management frameworks into practice

Lutz

Boucher

Roustant

2013

Journal of Decision Systems

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International audienceThis paper discusses some aspects of the decisional challenges implied by the management of modern information technology (IT) systems. These rapidly evolving complex systems are crucial to the overall performance of industrial companies. Two challenges are delineated: (1) the complexity of modern systems requires a system-thinking approach; (2) the critical role of IT in business performance implies taking into account these technological aspects within any business plan. Some IT management frameworks are designed to face these challenges but seem not to provide enough comprehensible decisional support to IT managers in real time. That is why this paper proposes innovative decision-aid methods, designed for some of the activities related to capacity management. Attention is paid to modelling and monitoring activities, through methods that combine qualitative and quantitative analyses. These approaches can provide operational support to IT managers. The added value of the methods developed is demonstrated by practical examples implemented in a semiconductor manufacturing firm. These results are an encouraging first step towards more comprehensive and more effective solutions

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Section: 222mentioning

confidence: 99%

Section: Future Research and Conclusionmentioning

confidence: 99%