Process Mining on a Robotic Mechanism

Nicoleta, Turcanu Cristina

doi:10.1109/icstw52544.2021.00043

Cited by 3 publications

(1 citation statement)

References 14 publications

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“…Cristina Nicoleta [23] discussed Industry 4.0 reliability and safety, suggesting a method for real-time robotic process verification with IIoT and Celonis. It enhances quality control and cuts errors, costs, and downtime.…”

Section: Related Workmentioning

confidence: 99%

PMiner: Process Mining using Deep Autoencoder for Anomaly Detection and Reconstruction of Business Processes

Chinnaiah,

Veerabhadram,

Aavula

et al. 2024

Int. j. electr. comput. eng. syst. (Online)

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We proposed a deep learning-based process mining framework known as PMiner for automatic detection of anomalies in business processes. Since there are thousands of business processes in real-time applications such as e-commerce, in the presence of concurrency, they are prone to exhibit anomalies. Such anomalies if not detected and rectified, cause severe damage to businesses in the long run. Our Artificial Intelligence (AI) enabled framework PMiner takes business process event longs as input and detects anomalies using a deep autoencoder. The framework exploits a deep autoencoder technique which is well-known for Its ability to discriminate anomalies. We proposed an algorithm known as Intelligent Business Process Anomaly Detector (IBPAD) to realize the framework. This algorithm learns from historical data and performs encoding and decoding procedures to detect business process anomalies automatically. Our empirical results using the BPI Challenge dataset, released by the IEEE Task Force on Process Mining, revealed that PMiner outperforms state-of-the-art methods in detecting business process anomalies. This framework helps businesses to identify process anomalies and rectify them in time to leverage business continuity prospects.

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Section: Related Workmentioning

confidence: 99%

PMiner: Process Mining using Deep Autoencoder for Anomaly Detection and Reconstruction of Business Processes

Chinnaiah,

Veerabhadram,

Aavula

et al. 2024

Int. j. electr. comput. eng. syst. (Online)

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A Methodology for the Analysis of Robotic Systems via Process Mining

Corradini,

Pettinari,

et al. 2023

Lecture Notes in Computer Science

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Modeling of the stress-deformed state of a capacitive apparatus with geometric deviations when mounting on a foundation

Рубцов

Arkhipova

Kulakov

et al. 2021

IOP Conf. Ser.: Mater. Sci. Eng.

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The reliable and trouble-free operation of the capacitive equipment of hazardous production facilities is significantly influenced by the quality of the installation performed before commissioning. So, during the installation of capacitive equipment, various geometric inconsistencies and deviations may occur, which are established by the current regulatory and technical documents for the installation of technological equipment. If unacceptable deviations and inconsistencies established by regulatory and technical documents are found, they must be fully eliminated. However, in certain cases, the regulatory and technical documentation allows operation with various insignificant geometric deviations and inconsistencies that do not go beyond the established limits. This may relate to deviations from the design horizontal position of the apparatus when installed on a foundation. It should be noted that during operation, under the influence of increased pressure, temperature and other loads, an apparatus with deviations of this type can undergo a completely different stress-deformed state compared to an apparatus without geometric deviations, which is not taken into account in expert diagnostics, strength analysis and assessment of residual resource. The solution to this issue can be approached using software systems that allow building 3D models of the objects under consideration with the introduction of all the necessary parameters into these models and getting a real picture of the distribution of zones of increased stress. In this work, the stress-deformed state of the process vessel is simulated due to the impact of working loads and different directions of deviation from the horizontal design position of the body when the apparatus is mounted on the foundation.

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Process Mining on a Robotic Mechanism

Cited by 3 publications

References 14 publications

PMiner: Process Mining using Deep Autoencoder for Anomaly Detection and Reconstruction of Business Processes

PMiner: Process Mining using Deep Autoencoder for Anomaly Detection and Reconstruction of Business Processes

A Methodology for the Analysis of Robotic Systems via Process Mining

Modeling of the stress-deformed state of a capacitive apparatus with geometric deviations when mounting on a foundation

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