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Enhancing Adoption of 3D Printing in Medical Technology Industry through Data Driven Decision Making

About This PhD Project

Project Description

The project investigates the adoption of disruptive technologies by focusing on the case of 3D Printing (3DP) in the Medical Technology (MedTech) industry. The expected outcome is a comprehensive decision making tool for companies in the MedTech industry who want to adopt 3DP as a production method. This is done by developing innovative optimisation tools to capture technological, market, and regulatory barriers for companies. The impact will be to unlock the potential of AM applications in the MedTech, which will benefit potential new entrants to the industry, incumbent firms, health care system, and patients in Australia. Our approach is based on data driven methodologies to carry state of art and research.

Research Question:
• How data driven decision making can result in more efficient adoption of 3D Printing among companies active in MedTech industry in Australia?
• How data driven decision making can result in encouraging entrepreneurial entry of new comers to the MedTech industry through adoption of 3D Printing as a production method?

Research Problem:
3D Printing offers a novel way of producing patient-specific medical devices (such as implants). However, there is no clear decision making tools for companies to decide, under various circumstances, whether 3D Printing is more cost-effect and more clinically-effective way of producing a medical devise in compare with traditional production methods or not. Examples of various circumstances that affect the decision making of the companies are the part of the body, risk category of the product, product material, and the specific technology of 3D Printing. Effective and efficient data driven decision-making models are needed to improve the efficiency of such decision making for companies, by systematically modelling various circumstances that affect the decision making of both established and new companies.

Proposed Outcome:
This project will generate innovative solutions to promote efficiency of the adaption of 3D Printing technologies in MedTech industry. The decision support tools are developed that can be calibrated to production system in MedTech industry and can be used by companies’ decision makers as well policy makers at different levels of government.

Proposed Postgraduate Research Programme

School: School of Management
Program name: PhD (Management)
Course code: DR204 Enabling Capability Platform (ECP)
Alignment : Global Business Innovation

Supervisory Team

Dr Sam Tavassoli Contact:
A/Professor Babak Abbasi Contact:

Academic Contact

HDR Coordinator, Dr Cameron Duff -

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