Systems Integration for Additive Manufacturing

Summary

As manufacturers increasingly recognize AM as a viable production alternative, they find themselves facing many new informatics, systems, and systems integration challenges hindering full adoption. Issues related to platform interoperability (from and between design, manufacture, and post-process), establishing digital provenance (digital thread and verification), and establishing data resources (AM modeling and databases) are steadfastly emerging. A major area of opportunity is to complement existing efforts with advancements in end-to-end digital implementations of that process. Systematically-configured digital implementations have the potential to replace physical transformation processes with models and simulations, and would facilitate informational transformations through standard interfaces. This effort will develop 1) standards to support consistent data representation in modeling, simulation, and databases, and 2) validation and verification methods for data integration, curation, and exchange. This project will develop and test a federated, information systems architecture for additive manufacturing. The architecture will specify product requirements, the stages of the product realization process, and the interfaces needed to link those stages together. Common data structures and interfaces will allow developers and end users of additive manufacturing technologies to simplify and coordinate digital end-to-end implementations. By streamlining methods used during design-to-product transformations, additive manufacturing technologies will become more accessible to small and medium-sized businesses, thereby increasing industrial competiveness and promoting their widespread adoption.

Description

Objective:  Deliver an information systems architecture, including metrics, information models, and validation methods to shorten the design-to-product cycle time in additive manufacturing (AM).

Technical Idea:  AM adopters are increasingly facing many of the challenges faced by early computer-aided applications (CAx) adopters (and often still face) related to interoperability between platforms and across production stages. These challenges are exacerbated by the complexity of the manufacturing processes themselves and the comparative infancy of the technologies on which they are founded. A major area of opportunity in AM is to complement existing AM research efforts with advancements in end-to-end digital implementations of the product realization process. Systematically-configured digital implementations would replicate physical transformation processes with models and simulations, and would facilitate informational transformations through standard interfaces. This effort will develop: 1) standards to support consistent data representation in modeling, simulation, and databases, and 2) validation and verification methods for data integration, curation, and exchange. This project will develop and test a federated, information systems architecture for additive manufacturing. The architecture will specify
product requirements, the stages of the product realization process, and the interfaces needed to link those stages together. Common data structures and interfaces will allow developers and end users of additive manufacturing technologies to simplify and coordinate digital end-to-end implementations.

To deliver this architecture, advancements are needed in additive manufacturing metrics, models, methods, and protocols. This project will address 1) and 2) above by defining and structuring AM information within a holistic, federated systems architecture aimed to:

• Provide a mechanism for which real-time, process-control feedback can be integrated into the digital thread, reducing the risk of defects during the manufacturing process (see 1) above).
• Provide a platform for which analytical models can be developed, stored, and accessed in order to support composable predictive modeling of AM products (see 1) above).
• Define interactions between different stages of product realization to decrease throughput time of information while increasing traceability (see 2) above).
• Provide an information systems architecture on which end-to-end digital implementations of AM parts can be verified and validated (see 2) above).

Research Plan:  This project will establish the information systems requirements, including major gaps and barriers, necessary to shorten design-to-product cycle times in additive manufacturing. These requirements will outline a path for achieving rapid, high fidelity information exchange and use across all stages of design-to-product transformation.

Specifically, the project investigates the gaps and barriers between the information requirements of the different stages of product realization. The stages of product realization begin with its geometry, either a physical component or 3D solid model, and finish with a validated and verified product. The project investigates the information gathered, produced, exchanged, and used by each stage, as well as their systems-level interactions. At the end of the first year, a well-defined requirements workflow for streamlining information throughput during product realization will be delivered, including the identification of areas of high interest where advancements in information representations will have the highest impact.

To support a holistic view of the information systems architecture, information requirements are explored for several key areas:

• Design information- design intent, design rationale, and performance requirements/constraints.
• Geometry information- the preservation of shape and features (including GD&T) during design-to-product transformations.
• Process information- how in situ measurements can be fed back into the digital thread for validation and verification.
• Material information- the role of material information and material properties in an overall AM systems architecture.
• Traceability- the information requirements necessary to verify and validate an AM part throughout design-to-product transformations.
• Disruptive technologies- the information challenges/ opportunities in developing technologies, including topological optimization and part regeneration.

The crosscutting information requirements between these areas are of particular importance. Crosscutting opportunities include developing support for predictive models and addressing information needs for product qualification. Predictive models can shorten cycle time to part qualification by reducing the need for empirical testing and allowing for more reliance on analytical models. These crosscutting efforts also support the information requirements for verification and validation techniquescomplementing design rules currently under development in ASTM F42 and ISO TC261.