Exploring innovative engineering solutions in New Zealand.
Results
Data Collection & Key Findings
This secondary research project used a PMBOK/Agile methodology, integrating global and NZ evidence via formal analysis tools
The research recommends trialling an integrated AI-assisted CAD and 3D printing toolchain to lift speed, quality, and capability in NZ engineering firms
Data Collection Summary
Evidence was assembled primarily through secondary research, drawing upon global and NZ-specific sources including academic literature, industry reports, and case studies
Analysis was conducted by applying business case + PMBOK/Agile methodology, utilizing tools such as SWOT, feasibility matrices, implementation readiness models, stakeholder analysis, and the CRIME/MEDIC model
Identified Technologies & Selection
The identified technologies of Artificial Intelligence (AI), Digital Twins
(DT), Robotics/Automation (R/A), 3D Printing
(3DP), Augmented/Virtual Reality (AR/VR) & Internet of Things (IoT) were analysed
The options analysis rigorously screened various options based on strategic objectives and critical success factors
Key screening criteria included feasibility against measurable KPI
Top Recommendation (MVP Choice)
The preferred Minimum Viable Product (MVP) is an AI-assisted CAD and 3D Printing workflow
AI-assisted CAD and 3D printing are relatively low-cost to pilot compared with the alternatives summarised here, delivering faster iteration and improved first-pass yield
It directly resolves the core problem of fragmented workflows that cause slow, variable results in NZ manufacturing sector. The chosen option offers the best overall value considering indicative benefits, costs, and risks
