| 1. |
- Paul, Satyam, et al.
(författare)
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A Vibration Based Automatic Fault Detection Scheme for Drilling Process Using Type-2 Fuzzy Logic
- 2022
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Ingår i: Algorithms. - : MDPI. - 1999-4893. ; 15:8
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Tidskriftsartikel (refereegranskat)abstract
- The fault detection system using automated concepts is a crucial aspect of the industrial process. The automated system can contribute efficiently in minimizing equipment downtime therefore improving the production process cost. This paper highlights a novel model based fault detection (FD) approach combined with an interval type-2 (IT2) Takagi–Sugeno (T–S) fuzzy system for fault detection in the drilling process. The system uncertainty is considered prevailing during the process, and type-2 fuzzy methodology is utilized to deal with these uncertainties in an effective way. Two theorems are developed; Theorem 1, which proves the stability of the fuzzy modeling, and Theorem 2, which establishes the fault detector algorithm stability. A Lyapunov stabilty analysis is implemented for validating the stability criterion for Theorem 1 and Theorem 2. In order to validate the effective implementation of the complex theoretical approach, a numerical analysis is carried out at the end. The proposed methodology can be implemented in real time to detect faults in the drilling tool maintaining the stability of the proposed fault detection estimator. This is critical for increasing the productivity and quality of the machining process, and it also helps improve the surface finish of the work piece satisfying the customer needs and expectations.
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| 2. |
- Paul, Satyam, 1981-, et al.
(författare)
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Discrete Time Sliding Mode Control of Milling Chatter
- 2020
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Ingår i: ICCSAMA 2019. - Cham : Springer-Verlag New York. - 9783030383633 - 9783030383640 ; , s. 381-390
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Bokkapitel (refereegranskat)abstract
- The technique of mitigating chatter phenomenon in an effective manner is an important issue from the viewpoint of superior quality machining process with quality production. In this paper, an innovative solution to control chatter vibration actively in the milling process is presented. The mathematical modelling associated with the milling technique is presented in the primary phase of the paper. In this paper, an innovative technique of discrete time sliding mode control(DSMC) is blended with Type 2 fuzzy logic system. Superior mitigation of chatter is the outcome of developed active controller. The Lyapunov scheme is implemented to validate the stability criteria of the proposed controller. The embedded nonlinearity in the cutting forces and damper friction are compensated in an effective manner by the utilization of Type-2 fuzzy technique. The vibration attenuation ability of DSMC-Type-2 fuzzy (DSMC-T2) is compared with the Discrete time PID (D-PID) and DSMC-Type-1 fuzzy (DSMC-T1) for validating the effectiveness of the controller. Finally, the numerical analysis is carried out to validate that DSMC-T2 is superior to D-PID and DSMC-T1 in the minimization of the milling chatter.
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| 3. |
- Reed, Sean, 1982-, et al.
(författare)
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Discrete Event Simulation Using Distributional Random Forests to Model Event Outcomes
- 2022
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Konferensbidrag (refereegranskat)abstract
- In discrete event simulation (DES), the events are random (aleatory) and typically represented by a probability distribution that fits the real phenomena that is studied. The true distributions of event outcomes, which may be multivariate, are often dependent on the values of covariates and this relationship may be complex. Due to difficulties in representing the influence of covariates within DES models, often only the averaged distribution or expected value of the conditional distribution is used. However, this can reduce modelling accuracy and prevent the model from being used to study the influence of covariates. Distributional random forests (DRF) are a machine learning technique for predicting the multivariate conditional distribution of an outcome from the values of covariates using an ensemble of decision trees. In this paper, the benefits of utilizing DRF in DES are explored through comparison with alternative approaches in a model of a powder coating industrial process.
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| 4. |
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| 5. |
- Reed, Sean, 1982-, et al.
(författare)
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Modelling cycle for simulation digital twins
- 2021
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Ingår i: Manufacturing Letters. - : Elsevier. - 2213-8463. ; 28, s. 54-58
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Tidskriftsartikel (refereegranskat)abstract
- Digital twins (DT) form part of the Industry 4.0 revolution within manufacturing and related industries. A DT is a digital model (DM) of a real system that features continuous and automated synchronisation and feedback of optimisations between the real and digital domains. A core technology for predictive capabilities from DT is discrete event simulation (DES). The modelling cycle for developing and analysing DES models is significantly different compared to DM. A DT specific DES modelling cycle is introduced that is evolved from that of DM. The availability of specialised software tools for DT tailored to these differences would benefit industry.
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| 6. |
- Reed, Sean, 1982-, et al.
(författare)
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Modelling stochastic behaviour in simulation digital twins through neural nets
- 2022
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Ingår i: Journal of Simulation. - : Taylor & Francis. - 1747-7778 .- 1747-7786. ; 16:5, s. 512-525
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Tidskriftsartikel (refereegranskat)abstract
- In discrete event simulation (DES) models, stochastic behaviour is modelled by sampling random variates from probability distributions to determine event outcomes. However, the distribution of outcomes for an event from a real system is often dynamic and dependent on the current system state. This paper proposes the use of artificial neural networks (ANN) in DES models to determine the current distribution of each event outcome, conditional on the current model state or input data, from which random variates can then be sampled. This enables more realistic and accurate modelling of stochastic behaviour. An application is in digital twin models that aim to closely mimic a real system by learning from its past behaviour and utilising current data to predict its future. The benefits of the approach introduced in this paper are demonstrated through a realistic DES model of load-haul-dump vehicle operations in a production area of a sublevel caving mine.
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