Cloud-Based Automated Design and Additive Manufacturing: A Usage Data-Enabled Paradigm Shift

Area of Science:

• Manufacturing Engineering
• Product Design
• Data Science

Background:

• Sensor integration provides valuable product usage data for optimization.
• Current limitations include lack of large-scale sensor data and high optimization costs.
• Emerging technologies like cloud services and additive manufacturing address these barriers.

Purpose of the Study:

• To explore the state of the art in product data gathering, additive manufacturing, and sensor integration.
• To develop a manufacturing concept for continuous, economically viable product optimization.
• To assess the concept's viability through diverse application scenarios.

Main Methods:

• Review of current technologies in data acquisition, additive manufacturing, and cloud-based services.
• Extrapolation of development trends across these domains.
• Analysis of three distinct application scenarios to validate the proposed concept.

Main Results:

• Identification of foundational elements for a new manufacturing paradigm.
• Demonstration of potential for optimization at general, user group, or individual levels.
• Validation of the holistic concept through practical application examples.

Conclusions:

• The convergence of sensor technology, additive manufacturing, and cloud services enables continuous product optimization.
• Significant research needs and critical issues were identified from stakeholder perspectives.
• The proposed concept offers a pathway to more user-friendly and efficient products.