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A scope in quality control, which has recently received a great deal of attention is profile that characterizes the quality of a product or process by a relationship between two or more variables. In this paper, we propose an EWMA chart for…

Applications · Statistics 2019-11-12 Seyed Nasser Moosavi , Mohammad Saleh Owlia , Ashkan Khalifeh

The classic N p chart gives a signal if the number of successes in a sequence of inde- pendent binary variables exceeds a control limit. Motivated by engineering applications in industrial image processing and, to some extent, financial…

Methodology · Statistics 2010-01-13 Ansgar Steland , Ewaryst Rafalowicz

New trends towards multiple core processors imply using standard programming models to develop efficient, reliable and portable programs for distributed memory multiprocessors and workstation PC clusters. Message passing using MPI is widely…

Programming Languages · Computer Science 2013-11-05 Alaa I. Elnashar

Tool condition monitoring (TCM) systems can improve productivity and ensure workpiece quality, yet, there is a lack of reliable TCM solutions for small-batch or one-off manufacturing of industrial parts. TCM methods which include the…

Classical Physics · Physics 2013-09-17 Mathieu Ritou , Sébastien Garnier , Benoît Furet , Jean-Yves Hascoët

Control systems are sets of interconnected hardware and software components which regulate the behaviour of processes. The software of modern control systems rises for some years by requirements regarding the flexibility and functionality.…

Software Engineering · Computer Science 2009-04-24 Rolf Andreas Rasenack , Karsten Wolke , Kostyantyn Yermashov , Karl Hayo Siemsen

Setting up effective and efficient mechanisms for controlling software and system development projects is still challenging in industrial practice. On the one hand, necessary prerequisites such as established development processes,…

Software Engineering · Computer Science 2014-01-08 Jens Heidrich , Jürgen Münch

This paper describes a hierarchical control scheme for interconnected systems. The higher layer of the control structure is designed with robust Model Predictive Control (MPC) based on a reduced order dynamic model of the overall system and…

Systems and Control · Computer Science 2017-03-09 Marcello Farina , Xinglong Zhang , Riccardo Scattolini

In preliminary analysis of control charts, one may encounter multiple shifts and/or outliers especially with a large number of observations. The following paper addresses this problem. A statistical model for detecting and estimating…

Applications · Statistics 2014-03-05 Issac Shams , Saeede Ajorlou , Kai Yang

Most statistical process control programmes in healthcare focus on surveillance of outcomes at the final stage of a procedure, such as mortality or failure rates. Such an approach ignores the multi-stage nature of these procedures, in which…

Methodology · Statistics 2020-06-29 Doaa Ayad , Nokuthaba Sibanda

To use control charts in practice, the in-control state usually has to be estimated. This estimation has a detrimental effect on the performance of control charts, which is often measured for example by the false alarm probability or the…

Methodology · Statistics 2013-07-30 Axel Gandy , Jan Terje Kvaløy

Sequential Convex Programming (SCP) has recently gained significant popularity as an effective method for solving optimal control problems and has been successfully applied in several different domains. However, the theoretical analysis of…

Optimization and Control · Mathematics 2022-09-07 Riccardo Bonalli , Thomas Lew , Marco Pavone

Modern statistical process monitoring (SPM) applications focus on profile monitoring, i.e., the monitoring of process quality characteristics that can be modeled as profiles, also known as functional data. Despite the large interest in the…

A comprehensive approach addressing identification and control for learningbased Model Predictive Control (MPC) for linear systems is presented. The design technique yields a data-driven MPC law, based on a dataset collected from the…

Systems and Control · Computer Science 2018-10-31 Enrico Terzi , Lorenzo Fagiano , Marcello Farina , Riccardo Scattolini

Stochastic model predictive control (SMPC) has been a promising solution to complex control problems under uncertain disturbances. However, traditional SMPC approaches either require exact knowledge of probabilistic distributions, or rely…

Optimization and Control · Mathematics 2020-01-03 Chao Shang , Fengqi You

This paper proposes a real-time model predictive control (MPC) scheme to execute multiple tasks using robots over a finite-time horizon. In industrial robotic applications, we must carefully consider multiple constraints for avoiding joint…

Robotics · Computer Science 2022-09-27 Jaemin Lee , Mingyo Seo , Andrew Bylard , Robert Sun , Luis Sentis

Software debugging has been shown to utilize upwards of half of developers' time. Yet, machine programming (MP), the field concerned with the automation of software (and hardware) development, has recently made strides in both research and…

Software Engineering · Computer Science 2021-05-18 Niranjan Hasabnis , Justin Gottschlich

We describe a particular control method for a system controlled by several actuators with the same control constants. We show under certain assumptions that the control constants for the whole system can be obtained immediately from the…

Optimization and Control · Mathematics 2022-05-26 Stephen Montgomery-Smith

Shewhart Control Charts (SCC)s are constructed under the assumption of normality and are widely recognized in statistical quality control by numerous researchers. Problems arise when the distribution of process data does not conform to a…

Applications · Statistics 2025-03-27 Seyedeh Azadeh Fallah Mortezanejad , Ruochen Wang

During the recent years there was an increased interest in studying the performance of different types of control charts, under various distributional models for continuous proportions, such as percentages and rates. In this work we…

Methodology · Statistics 2025-02-05 Athanasios C. Rakitzis

To estimate the causal effect of an intervention, researchers need to identify a control group that represents what might have happened to the treatment group in the absence of that intervention. This is challenging without a randomized…

Methodology · Statistics 2026-03-20 Robert Pickett , Jennifer Hill , Sarah Cowan
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