The primary focus of this thesis report was to develop an HMI application specifically tailored for the Life Sciences industry, with the overarching goal of enhancing user-centricity. To achieve this objective, the project investigated the crucial factors of HMI adaptability, usability, compatibility, and data integrity. The study explored various methods and approaches for implementing and improving these four key determinants, using Rockwell Automation's FT Optix software and Getinge Manufacturing as the case study.

To achieve this, the study incorporated functionalities such as recipe management, audit trails, authentication of changes, and in-built report generation to attain CFR Part 11 compliance in line with the Life Sciences requirements for electronic data handling. Additionally, the study also explored the use of Machine Learning models to improve HMI adaptability. 

Overall, the research successfully showcased the development of an HMI application that effectively incorporated and prioritised the above-mentioned features. Furthermore, the study identified the limitations of the project and highlighted areas that require further improvements. These findings provide valuable insights for advancing the field of man-machine collaboration, which holds significant importance in the realm of robotics and automation. The research contributes to the growing knowledge in this domain, providing a deeper understanding of optimising human-machine interaction and paving the way for future research.