Mangolika Bhattacharya
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Mangolika Bhattacharya has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Eoin O Connell
Department of Electronic and Computer Engineering, University of Limerick, Limerick, Ireland
1 shared publication - Mark Southern
School of Engineering and Enterprise Research Centre, University of Limerick, V94 T9PX Limerick, Ireland
1 shared publication - Martin J. Hayes
Department of Electronic and Computer Engineering, University of Limerick, V94 TP9X Limerick, Ireland
1 shared publication - Mihai Penica
Department of Electronic and Computer Engineering, University of Limerick, Limerick, Ireland
1 shared publication
Latest Publications
- Open Access
Human-in-Loop: A Review of Smart Manufacturing Deployments
The recent increase in computational capability has led to an unprecedented increase in the range of new applications where machine learning can be used in real time. Notwithstanding the range of use cases where automation is now feasible, humans are likely to retain a critical role in the operation and certification of manufacturing systems for the foreseeable future. This paper presents a use case review of how human operators affect the performance of cyber–physical systems within a ’smart’ or ’cognitive’ setting. Such applications are classified using Industry 4.0 (I4.0) or 5.0 (I5.0) terminology. The authors argue that, as there is often no general agreement as to when a specific use case moves from being an I4.0 to an I5.0 example, the use of a hybrid Industry X.0 notation at the intersection between I4.0 and I5.0 is warranted. Through a structured review of the literature, the focus is on how secure human-mediated autonomous production can be performed most effectively to augment and optimise machine operation.
Open AccessHuman-in-Loop: A Review of Smart Manufacturing Deployments
The recent increase in computational capability has led to an unprecedented increase in the range of new applications where machine learning can be used in real time. Notwithstanding the range of use cases where automation is now feasible, humans are likely to retain a critical role in the operation and certification of manufacturing systems for the foreseeable future. This paper presents a use case review of how human operators affect the performance of cyber–physical systems within a ’smart’ or ’cognitive’ setting. Such applications are classified using Industry 4.0 (I4.0) or 5.0 (I5.0) terminology. The authors argue that, as there is often no general agreement as to when a specific use case moves from being an I4.0 to an I5.0 example, the use of a hybrid Industry X.0 notation at the intersection between I4.0 and I5.0 is warranted. Through a structured review of the literature, the focus is on how secure human-mediated autonomous production can be performed most effectively to augment and optimise machine operation.