EGEP: An Event Tracker Enhanced Gene Expression Programming for Data Driven System Engineering Problems

Huang, Zheng; Li, Maozhen; Mousavi, Alireza; Danishva, Morad; Wang, Zidong

doi:10.1109/tetci.2018.2864724

Cited by 11 publications

(5 citation statements)

References 23 publications

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“…The gene sequencing (DNA of the process) can be a powerful tool for interpreting and demonstrating the knowledge graphs in CDT. Another potential area to explore is the role of GIP in simplifying and relaxing rule-based models (e.g., [45] and [46]).…”

Section: Discussionmentioning

confidence: 99%

The Genomics of Industrial Process Through the Qualia of Markovian Behavior

Danishvar

Mousavi

Daneshvar

2022

IEEE Trans. Syst. Man Cybern, Syst.

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A technique for registering and relating events that cause an observable and definable system state is proposed. Discrete events of system-state transfer are expressed by event tracking and clustering in the form of contiguous quanta of data. This approach is capable of describing typical processes in industrial systems in a chain of codes that contain system input/output parameters. The constituent nodes of the Markovian Processes chain form a series akin to genes in the deoxyribonucleic acid, repeatable and predictable. The process genes are the quanta of information that aligns to represent a chain of activities (process). They describe the causal links between occurring events forming a pattern (pathway) that leads to a well-specified output (e.g., a product with a defect or otherwise). The creation of process genomics requires the knowledge of system observed or latent parameters (state) as well as the state change at specified time intervals (discretization). The process genomics theory is tested in an industrial case study for quality assessment and control of glue dispensing in micro-semiconductor manufacturing. The resulting definitions of the system state and interrelationship of control parameters contribute to the development of the process genes. The outcome of the gene alignment is the geometric interpretation of the glue droplet formation. A predicted or observed droplet within the production tolerance leads to a nondefective product. The principle of creating production genomics is to find and rectify the defect-causing genes or to disrupt the sequences that lead to producing defective products, leading to a zero-defect manufacturing process.

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Section: Discussionmentioning

confidence: 99%

The Genomics of Industrial Process Through the Qualia of Markovian Behavior

Danishvar

Mousavi

Daneshvar

2022

IEEE Trans. Syst. Man Cybern, Syst.

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“…Another potential area to explore is the role of GIP in simplifying and relaxing rulebased models (e.g. [48], [49]).…”

Section: VImentioning

confidence: 99%

The Genomics of Industrial Process through the Qualia of Markovian Behaviour

Danishvar¹,

Daneshvar²,

Mousavi³

2022

Preprint

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A technique for registering and relating events that cause an observable and definable system state is proposed. Discrete events of system state transfer are expressed by event tracking and clustering in the form of contiguous quanta of data. This approach is capable of describing typical processes in industrial systems in a chain of codes that contain system input/output parameters. The constituent nodes of the Markovian Processes chain form a series akin to genes in the DNA, repeatable and predictable.<br>

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“…The Event Tracker is a computationally efficient technique that focuses on the state changes of the involved system components. It merely takes a snapshot of the system states, which helps engineers observe system performance [6]. Further details on the description and four Event-Tracker functional parameters (Search Slot, Analysis Span, Event Threshold and Trigger Threshold) can found in [35].…”

Section: Eventtracker Algorithmmentioning

confidence: 99%

“…The technique is capable of grouping together high correlation system parameters, forming an input-output relationship that is not limited to internal parameters only. As such, the homogenized correlation system will indicate the possible root cause of harmonic failures, while eliminating non-important parameters in real-time [6]. This paper presents a real-time simulation of CSU machines, which shows the changes in the output parameters of the input activity.…”

Section: Introductionmentioning

confidence: 99%

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Event Modeller Data Analytic for Harmonic Failures

Zamsyah¹,

Mousavi²,

Danishvar³

2021

Adv. sci. technol. eng. syst. j.

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The optimum performance of power plants has major technical and economic benefits. A case study in one of the Malaysian power plants reveals an escalating harmonic failure trend in their Continuous Ship Unloader (CSU) machines. This has led to a harmonic filter failure causing performance loss leading to costly interventions and safety concerns. Analysis of the harmonic parameter using Power Quality Assessment indicates that the power quality is stable as per IEEE standards; however, repetitive harmonic failures are still occurring in practice. This motivates the authors to explore whether other unforeseen events could cause harmonic failure. Usually, post-failure plant engineers try to backtrack and diagnose the cause of power disturbance, which in turn causes delay and disruption to power generation. This is a costly and time-consuming practice. A novel event-based predictive modelling technique, namely, Event Modeller Data Analytic (EMDA), designed to inclusive the harmonic data in line with other technical data such as environment and machine operation in the cheap computational effort is proposed. The real-time Event Tracker and Event Clustering extended by the proposed EMDA widens the sensitivity analysis spectrum by adding new information from harmonic machines' performance. The added information includes machine availability, utilization, technical data, machine state, and ambient data. The combined signals provide a wider spectrum for revealing the status of the machine in real-time. To address this, a software-In-the-Loop application was developed using the National Instrument LabVIEW. The application was tested using two different data; simulation data and industrial data. The simulation study results reveal that the proposed EMDA technique is robust and could withstand the rapid changing of real-time data when events are detected and linked to the harmonic inducing faults. A hardware-inthe-Loop test was implemented at the plant to test and validate the sensitivity analysis results. The results reveal that in a single second, a total of 2,304 input-output relationships were captured. Through the sensitivity analysis, the fault causing parameters were reduced to 10 input-output relationships (dimensionality reduction). Two new failure causing event/parameter were detected, humidity and feeder current. As two predictable and controllable parameters, humidity and feeder velocity can be regulated to reduce the probability of harmonic fluctuation.

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EGEP: An Event Tracker Enhanced Gene Expression Programming for Data Driven System Engineering Problems

Cited by 11 publications

References 23 publications

The Genomics of Industrial Process Through the Qualia of Markovian Behavior

The Genomics of Industrial Process Through the Qualia of Markovian Behavior

The Genomics of Industrial Process through the Qualia of Markovian Behaviour

Event Modeller Data Analytic for Harmonic Failures

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