Cormican_2023_Scaling.pdf

As technological advancements in artificial intelligence (AI) accelerate, the effect it has on the adoption of Industry 4.0 is significant. The adoption of AI-based Industry 4.0 projects creates a significant opportunity to generate new revenue streams and high-value customer-centric products. However, medical device manufacturing organisations are strictly scrutinised by regulatory authorities due to the critical nature of these devices and their impact on humans. This presents a challenging environment for medical device manufacturers to experiment with and implement new technologies. However, the significance and impact of AI?based projects are acknowledged by regulatory authorities such as the FDA and EMA and PMDA, allowing the incorporation of AI-based devices. This change in regulations, although limited, opens up immense opportunities for medical device manufacturers. Although extensive studies on the barriers, challenges, and failure factors of AI projects are available, very few studies explore these from a medical device manufacturing perspective. This is essential due to the significant limitations posed by the regulations governing medical device development. This study analyses the challenges and factors affecting the scaling of AI-based Industry 4.0 projects in medical device manufacturing organisations. The study found three major factors influencing the scaling of AI-based Insutry 4.0 projects. They comprise infrastructural costs, security risks and a change management migration plan. However, investing in these factors with a view to scaling may create additional revenue sources and also help in reaching a faster return on investment. Such investments can also improve the overall productivity of the industry, allowing the creation of high-value customer-centric products. The perceived security risks in the industry were found to be higher than the risks analysed in previous literature, suggesting a need to create an informed workforce. The study also found that for effective implementation of scalable AI-based industry 4.0 projects a skilled workforce with a shared long-term vision is required.