We report progress towards development of a cyber-physical trust anchor for additive manufacturing systems. The additive manufacturing commercial sector needs cyber-physical trust anchors to establish a secure supply chain, to detect counterfeiting and to ensure part provenance. However, the underlying technology of cyber-physical trust anchors requires optimization and spans several sectors ranging from mathematics, additive manufacturing, materials science, nondestructive evaluation, to cyber science. The fast and effective deployment of cyber-physical trust anchors requires an educational component. This project present a novel method for authenticating additively manufactured parts. Features are extracted using advanced X-ray imaging, transformed into unique identifiers, and bound with security features for cloud-based blockchain authentication. A plan for the low-cost and safe incorporation of cyber-physical trust anchor research in education is included. The anticipated outcome is an optimized trust anchor prototype and educational product suitable for interdisciplinary research and coursework to develop the workforce needed for cyber-secured physical supply chainsd.
This content will become publicly available on September 11, 2024
The geographical separation between various supply chain participants creates challenges in ensuring the integrity of the parts under circulation. These supply chains have to regularly deal with counterfeiting, a significant problem with an estimated value equivalent to at least the tenth-largest global economy. Industries are constantly upgrading their anti-counterfeiting methods to tackle this ever-increasing issue. Traditionally, a physical or cyber-physical part identifier is used to assert the integrity and identity of parts moving through the supply chain. For this work, we propose the use of electromechanical impedance measurements to generate a robust, unique part identifier linked to physical attributes. Electromechanical impedance measurements have been employed as a basis for non-destructive evaluation techniques in damage detection and health monitoring. We propose using these high-frequency measurements recorded through bonded piezoceramic transducers to help uniquely identify parts.
For this study, identical piezoceramic transducers (cut from the same wafer to minimize variations) were mounted on identically manufactured specimens. The only distinction between these specimens was the physical variation introduced during manufacturing and instrumentation. Multiple measurements for each specimen were recorded. A unique part identification methodology based on linear projection was created using these measurements. Lastly, a leave-one-out-study was performed to uniquely identify the left-out specimen. This was used to validate the part identification methodology. This paper introduces the use of electromechanical impedance measurements (widely adopted for damage detection) as a unique part identifier, with a basic experimental implementation of the proposed mechanism on identically manufactured parts. The paper also highlights some challenges and future work needed to make this methodology robust and adaptable.
more » « less- Award ID(s):
- 1932213
- NSF-PAR ID:
- 10486351
- Publisher / Repository:
- American Society of Mechanical Engineers
- Date Published:
- Journal Name:
- Proceedings of the ASME 2023 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
- Format(s):
- Medium: X
- Location:
- Austin, Texas, USA
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Abstract -
more » « less
Abstract Electromechanical impedance-based (EMI) techniques using piezoelectric transducers are promising for structural damage identification. They can be implemented in high frequency range with small characteristic wavelengths, leading to high detection sensitivity. The impedance measured is the outcome of harmonic and stationary excitation, which makes it easier to conduct inverse analysis for damage localization and quantification. Nevertheless, the EMI data measurement points are usually limited, thus oftentimes resulting in an under-determined problem. To address this issue, damage identification process can be converted into a multi-objective optimization formulation which naturally yields multiple solutions. While this setup fits the nature of damage identification that a number of possibilities may exist under given observations/measurements, existing algorithms may suffer from premature convergence and entrapment in local extremes. Consequently, the solutions found may not cover the true damage scenario. To tackle these challenges, in this research, a series of local search strategies are tailored to enhance the global searching ability and incorporated into particle swarm-based optimization. The Q-table is utilized to help the algorithm select proper local search strategy based on the maximum Q-table values. Case studies are carried out for verification, and the results show that the proposed memetic algorithm achieves good performance in damage identification.
-
Currently, verifying additively manufactured (AM) parts requires time consuming and expensive nondestructive evaluation (NDE) processes such as computed tomography (CT) x-ray scanning. While such methods provide details on flaw type and location, they require significant cost and time. Often, in production environments, significant value is gained by rapidly screening part specimens for flaws at all. Cost-effective per-specimen testing for production runs of AM parts is important for their use to be economically justified. In this work, Northrop Grumman Corporation and Virginia Tech explored impedance-based testing as a means to evaluate AM titanium specimens. Specimens with and without manually-designed flaws were fabricated through a metal- based AM process and evaluated using the impedance-based technique. CT scans confirmed that the intended flaws in the experimental specimens were present. Impedance-based examination also showed the presence of unintended defects. After machining away the unintended defective regions, the flaw-containing defective specimen had a clearly different impedance ‘signature’ than non-flawed baseline specimens. Additional analysis confirmed that the impedance test method required cheaper capital equipment and required less technician time to examine test results. Taken together, this means that the impedance-based this method can reduce the total cost of utilizing AM for metal part manufacturing.more » « less
-
Additive Manufacturing (AM) allows increased complexity which poses challenges to quality-control (QC) and non-destructive evaluation (NDE) of manufactured parts. The lack of simple, reliable, and inexpensive methods for NDE of AM parts is a significant obstacle to wider adoption of AM parts. Electromechanical impedance measurements have been investigated as a means to detect manufacturing defects in AM parts. Impedance-based NDE utilizes piezoelectric wafers as collocated sensors and actuators. Taking advantage of the coupled electromechanical characteristics of piezoelectric materials, the mechanical characteristics of the part under test can be inferred from the electrical impedance of the piezoelectric wafer. Previous efforts have used piezoelectric wafers bonded directly to the part under test, which imposes several challenges regarding the applicability and robustness of the technique. This paper investigates the use of an instrumented clamp as a solution for measuring the electromechanical impedance of the part under test. The effectiveness of this approach in detecting manufacturing defects is compared to directly bonded wafers.more » « less
-
Additive Manufacturing (AM) allows increased complexity which poses challenges to quality-control (QC) and non-destructive evaluation (NDE) of manufactured parts. The lack of simple, reliable, and inexpensive methods for NDE of AM parts is a significant obstacle to wider adoption of AM parts. Electromechanical impedance measurements have been investigated as a means to detect manufacturing defects in AM parts. Impedance-based NDE utilizes piezoelectric wafers as collocated sensors and actuators. Taking advantage of the coupled electromechanical characteristics of piezoelectric materials, the mechanical characteristics of the part under test can be inferred from the electrical impedance of the piezoelectric wafer. Previous efforts have used piezoelectric wafers bonded directly to the part under test, which imposes several challenges regarding the applicability and robustness of the technique. This paper investigates the use of an instrumented clamp as a solution for measuring the electromechanical impedance of the part under test. The effectiveness of this approach in detecting manufacturing defects is compared to directly bonded wafers.more » « less
