On-line fault diagnosis system support for reactive scheduling in multipurpose batch chemical plants

Ruiz, Diego; Cantón, Jordi; Nougués, José María; Espuña, Antonio; Puigjaner, Luís

doi:10.1016/s0098-1354(01)00657-3

Cited by 54 publications

(25 citation statements)

References 10 publications

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“…To alleviate this issue, [28] considers machine outages and rush order arrivals, and develops an approach in which an appropriate penalty term is introduced in the objective function that minimizes the deviation of the revised schedule from the original one. The scheme presented in [29] includes a knowledge-based expert system with the aim of minimizing the impact on the schedule from uncertainty on processing time or unit availability. For this same type of uncertainty, [30] develops a least-impact heuristic algorithm.…”

Section: Literaturementioning

confidence: 99%

Robust Optimization of Schedules Affected by Uncertain Events

Vujanic

Goulart

Morari

2016

J Optim Theory Appl

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In this paper, we present a new method for finding robust solutions to mixed-integer linear programs subject to uncertain events. We present a new modeling framework for such events that result in uncertainty sets that depend parametrically on the decision taken. We also develop results that can be used to compute corresponding robust solutions. The usefulness of our proposed approach is illustrated by applying it in the context of a scheduling problem. For instance, we address uncertainty on the start times chosen for the tasks or on which unit they are to be executed. Delays and unit outages are possible causes for such events and can be very common in practice. Through our approach, we can accommodate them without altering the remainder of the schedule. We also allow for the inclusion of recourse on the continuous part of the problem, that is, we allow for the revision of some of the decisions once uncertainty is observed. This allows one to increase the performance of the robust solutions. The proposed scheme is also computationally favorable since the robust optimization problem to be solved remains a mixed-integer linear program, and the number of integer variables is not increased with respect to the nominal formulation. We finally apply the method to a concrete batch scheduling problem and discuss the effects of robustification in this case.Communicated by Christodoulos Floudas.

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Section: Literaturementioning

confidence: 99%

Robust Optimization of Schedules Affected by Uncertain Events

Vujanic

Goulart

Morari

2016

J Optim Theory Appl

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“…Due to several factors such as complexity of dynamics, incomplete uncertain knowledge and diverse sources of knowledge, many diagnostic methods and techniques are adopted in fault diagnosis research and development work. These methods and techniques can briefly be classified into the following: rule-based (Cho, Ahn, & Chung, 2003;El Gamal & Abdulghafour, 2003;Jämsä, Jounela, Vermasvuori, Endén, & Haavisto, 2003), knowledge-based (Cho et al, 2003;Ruiz et al, 2001), modelbased (Ding, Fennel, & Ding, 2004;Liu & Coghill, 2005), case-based (Cunningham, Smyth, & Bonzano, 1998), neural network (Mohamed, Abdelaziz, & Mostafa, 2005;Yang, Han, & An, 2004), rough set theory (Tay & Shen, 2003;Wang & Li, 2004), fuzzy logic (Dash, Rengaswamy, & Venkatasubramanian, 2003;Tarifa & Scenna, 2004) and statistical method (Yang, Lim, & Tan, 2005).…”

Section: Literature Reviewmentioning

confidence: 99%

HYDES: A Web-based hydro turbine fault diagnosis system

Song

Chu

et al. 2008

Expert Systems with Applications

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“…They are mainly divided into modelbased [3,4] and data-based approaches [5][6][7]. Model-based method uses deviations between the measured value and the reference value as an indicator to raise alarm about faults and take action on timely fault diagnosis and correction.…”

Section: Introductionmentioning

confidence: 99%

An Integrated FDD Approach for an Intensified HEX/Reactor

Zhang

Cabassud

et al. 2018

Journal of Control Science and Engineering

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In this paper, a fault detection and diagnosis (FDD) scheme is developed for a class of intensified HEX/reactor, in which faults caused by sensor, actuator, and process are taken into account in the unified framework. By considering overall heat transfer coefficient as a function of fouling and fluid flow rate, a dynamic model which is capable of identifying these two faults simultaneously is derived. Sensor measurements, together with estimation by adaptive high gain observers, are processed, aimed at identifying sensor faults and providing adequate estimation to substitute faulty measurements. Then reliable measurements are fed to several banks of interval filters to generate several banks of residuals; each bank of residuals is sensitive to a particular process parameter/actuator. By evaluating these residuals, process/actuator fault isolation and identification are achieved. The proposed strategy is applied to actual data retrieved from a new intensified heat exchanger reactor. Simulation results confirm the applicability and robustness of the proposed methodology.

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On-line fault diagnosis system support for reactive scheduling in multipurpose batch chemical plants

Cited by 54 publications

References 10 publications

Robust Optimization of Schedules Affected by Uncertain Events

Robust Optimization of Schedules Affected by Uncertain Events

HYDES: A Web-based hydro turbine fault diagnosis system

An Integrated FDD Approach for an Intensified HEX/Reactor

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