Developing a Novel Data Driven based Process Monitoring and Reporting System for a Pharmaceutical Company

Project Member(s): Saberi, M.

Funding or Partner Organisation: Department of Industry, Innovation and Science (Innovation Connections)
Department of Industry, Innovation and Science (Innovation Connections)
EZYMED PTY LTD
EZYMED PTY LTD

Start year: 2021

Summary: EzyMed automates the administration and packing of Dose Administration Aids (DAA's), ensuring greater medication compliance & adherence and greater accuracy in DAA assembling by standing between pharmaceutical wholesalers and pharmacies. EzyMed has built systems and integrated available technologies that successfully satisfy current demand. Certain of the businesses machinery and equipment are operating at less than 25% capacity, but scaling to full capacity, the business needs to implement more sophisticated technologies -namely to automate a number of steps in its processing and packing to ensure accuracy in DAAs at higher volumes. This requires sophisticated expertise in Industry 4.0, specifically in process automation, AI, and data-driven based business process management. In the age of big data, AI is a powerful differentiator for the business. Understanding the ability and interconnectivity of our machines, people, and the potential of sensors and more to support advanced automation and enhance system communications is a highly specialized area; and is beyond the knowledge of our current team and the industry's core skillset. Moreover, EzyMed relies on heterogeneous and sophisticated technologies for DAAs packing which are underpinned by various business processes. The monitoring of different EzyMed’s processes producing a huge and complex amount of data requires an advanced AI-based monitoring system beyond the current team’s skillset. We have instigated initial discussions about accessing the specialized expertise of Dr. Morteza Saberi, Lecturer and Assistant Professor at the School of Information, Systems and Modelling, UTS, Sydney. Our overarching goal is to develop an AI-based monitoring platform that assists us in monitoring and analysing the various EzyMed’s processes, thereby ensuring that the process is executed effectively. This is an essential and critical step for EzyMed to scale its production to full capacity.

FOR Codes: Communication Networks and Services not elsewhere classified, Decision Support and Group Support Systems, Communication technologies, systems and services

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.