Proposing a holistic framework for the assessment and management of manufacturing complexity through data-centric and human-centric approaches

Positional Health Assessment of Collaborative Robots Based on Long Short-Term Memory Auto-Encoder (LSTMAE) Network
Hasan, N., Webb, L., Kaniappan Chinnathai, M., Hossain, M.A-A., Ozkat, E.C., Tokhi, M.O. and Alkan, B. 2024. Positional Health Assessment of Collaborative Robots Based on Long Short-Term Memory Auto-Encoder (LSTMAE) Network. in: El Youssef, E.S., Tokhi, M.O., Silva, M.F. and Rincon, L.M. (ed.) Synergetic Cooperation between Robots and Humans: Proceedings of the CLAWAR 2023 Conference - Volume 2 Springer. pp. 323-335

A digital life-cycle management framework for sustainable smart manufacturing in energy intensive industries
Kaniappan Chinnathai, M. and Alkan, B. 2023. A digital life-cycle management framework for sustainable smart manufacturing in energy intensive industries. Journal of Cleaner Production. 419 138259. https://doi.org/10.1016/j.jclepro.2023.138259

Image segmentation of micro-TIG battery welds
Ferri, C., Kaniappan Chinnathai, M., Titmarsh, R. and Abdelaziz, H. 2022. Image segmentation of micro-TIG battery welds. 27th International conference on Automation and Computing (ICAC). Bristol, UK 01 - 03 Sep 2022

Performance Comparison of Recent Population-Based Metaheuristic Optimisation Algorithms in Mechanical Design Problems of Machinery Components
Alkan, B. and Kaniappan Chinnathai, M. 2021. Performance Comparison of Recent Population-Based Metaheuristic Optimisation Algorithms in Mechanical Design Problems of Machinery Components . Machines. 9 (12) 341. https://doi.org/10.3390/machines9120341

A novel data-driven approach to support decision-making during production scale-up of assembly systems
Kaniappan Chinnathai, M., Alkan, B. and Harrison, R. 2021. A novel data-driven approach to support decision-making during production scale-up of assembly systems. Journal of Manufacturing Systems. 59, pp. 577-595. https://doi.org/10.1016/j.jmsy.2021.03.018

A framework to predict energy related key performance indicators of manufacturing systems at early design phase
Assad, F., Alkan, B., Kaniappan Chinnathai, M., Ahmad, M, Rushforth, E. and Harrison, R. 2019. A framework to predict energy related key performance indicators of manufacturing systems at early design phase . 52nd CIRP Conference on Manufacturing Systems. Ljubljana, Slovenia 12 - 14 Jun 2019 Elsevier. https://doi.org/10.1016/j.procir.2019.03.026

A Framework for Pilot Line Scale-up using Digital Manufacturing
Kaniappan Chinnathai, M., Al-mowafy, Z., Alkan, B., Vera, D. and Harrison, R. 2019. A Framework for Pilot Line Scale-up using Digital Manufacturing . 52nd CIRP Conference on Manufacturing Systems. Ljubljana, Slovenia 12 - 14 Jun 2019 Elsevier. https://doi.org/10.1016/j.procir.2019.03.235

Pilot to Full-Scale Production: A Battery Module Assembly Case Study
Kaniappan Chinnathai, M., Alkan, B., Vera, D. and Harrison, R. 2018. Pilot to Full-Scale Production: A Battery Module Assembly Case Study. 51st CIRP Conference on Manufacturing Systems. Stockholm, Sweden 16 - 18 May 2018 Elsevier. https://doi.org/10.1016/j.procir.2018.03.194

An Application of Physical Flexibility and Software Reconfigurability for the Automation of Battery Module Assembly
Kaniappan Chinnathai, M., Günther, T., Ahmad, M., Stocker, C., Richter, L., Schreiner, D., Vera, D., Reinhart, G. and Harrison, R. 2017. An Application of Physical Flexibility and Software Reconfigurability for the Automation of Battery Module Assembly. 50th CIRP Conference on Manufacturing Systems. Taichung City, Taiwan 03 - 05 May 2017 Elsevier. https://doi.org/10.1016/j.procir.2017.03.128

Convertibility Evaluation of Automated Assembly System Designs for High Variety Production
Kaniappan Chinnathai, M., Chinnathai, M.K., Alkan, B. and Harrison, R. 2017. Convertibility Evaluation of Automated Assembly System Designs for High Variety Production. 50th CIRP Conference on Manufacturing Systems. Taichung City, Taiwan 03 - 05 May 2017 Elsevier. https://doi.org/10.1016/j.procir.2017.01.005