Automated metrology and geometric analysis of additively manufactured lattice structures

McGregor, Davis J.; Tawfick, Sameh; King, William P.

doi:10.1016/j.addma.2019.05.026

Cited by 25 publications

(16 citation statements)

References 21 publications

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“…The EVs were inspected carefully, and in some cases the dimensions of the components were measured with calipers and optical scanners. Key dimensions were extracted using metrology software [ 39 ]. The EVs were also tested for comparison with the RapidVent, described later.…”

Section: Introductionmentioning

confidence: 99%

Emergency ventilator for COVID-19

et al. 2020

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The COVID-19 pandemic disrupted the world in 2020 by spreading at unprecedented rates and causing tens of thousands of fatalities within a few months. The number of deaths dramatically increased in regions where the number of patients in need of hospital care exceeded the availability of care. Many COVID-19 patients experience Acute Respiratory Distress Syndrome (ARDS), a condition that can be treated with mechanical ventilation. In response to the need for mechanical ventilators, designed and tested an emergency ventilator (EV) that can control a patient’s peak inspiratory pressure (PIP) and breathing rate, while keeping a positive end expiratory pressure (PEEP). This article describes the rapid design, prototyping, and testing of the EV. The development process was enabled by rapid design iterations using additive manufacturing (AM). In the initial design phase, iterations between design, AM, and testing enabled a working prototype within one week. The designs of the 16 different components of the ventilator were locked by additively manufacturing and testing a total of 283 parts having parametrically varied dimensions. In the second stage, AM was used to produce 75 functional prototypes to support engineering evaluation and animal testing. The devices were tested over more than two million cycles. We also developed an electronic monitoring system and with automatic alarm to provide for safe operation, along with training materials and user guides. The final designs are available online under a free license. The designs have been transferred to more than 70 organizations in 15 countries. This project demonstrates the potential for ultra-fast product design, engineering, and testing of medical devices needed for COVID-19 emergency response.

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Section: Introductionmentioning

confidence: 99%

Emergency ventilator for COVID-19

et al. 2020

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“…The fact is that the current measurement systems defined in the ISO standard did not consider complex freeform geometries. This becomes more challenging for internal shapes such as conformal cooling channels [130] and lattice structures [131], and it requires advanced imaging techniques such as computed tomography [132,133]. Furthermore, designers face difficulties to define "tolerance zone for these geometries [115].…”

Section: Product Qualitymentioning

confidence: 99%

Advances in Metal Additive Manufacturing: A Review of Common Processes, Industrial Applications, and Current Challenges

et al. 2021

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In recent years, Additive Manufacturing (AM), also called 3D printing, has been expanding into several industrial sectors due to the technology providing opportunities in terms of improved functionality, productivity, and competitiveness. While metal AM technologies have almost unlimited potential, and the range of applications has increased in recent years, industries have faced challenges in the adoption of these technologies and coping with a turbulent market. Despite the extensive work that has been completed on the properties of metal AM materials, there is still a need of a robust understanding of processes, challenges, application-specific needs, and considerations associated with these technologies. Therefore, the goal of this study is to present a comprehensive review of the most common metal AM technologies, an exploration of metal AM advancements, and industrial applications for the different AM technologies across various industry sectors. This study also outlines current limitations and challenges, which prevent industries to fully benefit from the metal AM opportunities, including production volume, standards compliance, post processing, product quality, maintenance, and materials range. Overall, this paper provides a survey as the benchmark for future industrial applications and research and development projects, in order to assist industries in selecting a suitable AM technology for their application.

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“…With a continuous interpolation method denoted as an operator I X nt , data is converted back to a mappingf = I X nt (y) over a continuous region, such thatf ≈ f . This process is shown by Equation (6).…”

Section: Big Data Fusion For Interpolationmentioning

confidence: 99%

“…Spatial and spatiotemporal processes are ubiquitous across all scales in manufacturing. They can manifest themselves in critical product quality characteristics (e.g., surface quality in machining [1][2][3][4], geometric compliance [5,6] and surface finish/texture [7] in additive manufacturing) or degradation of consumable tools (e.g., cutting and lapping tools in machining [8], horn and anvil in ultrasonic welding [9][10][11][12]). Figure 1 shows three examples of spatial and spatiotemporal processes in manufacturing at different scales and highlights the necessity of high-resolution surface measurement.…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Intelligent 3D Surface Measurement in Smart Manufacturing: Review and Outlook

et al. 2021

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High-fidelity characterization and effective monitoring of spatial and spatiotemporal processes are crucial for high-performance quality control of many manufacturing processes and systems in the era of smart manufacturing. Although the recent development in measurement technologies has made it possible to acquire high-resolution three-dimensional (3D) surface measurement data, it is generally expensive and time-consuming to use such technologies in real-world production settings. Data-driven approaches that stem from statistics and machine learning can potentially enable intelligent, cost-effective surface measurement and thus allow manufacturers to use high-resolution surface data for better decision-making without introducing substantial production cost induced by data acquisition. Among these methods, spatial and spatiotemporal interpolation techniques can draw inferences about unmeasured locations on a surface using the measurement of other locations, thus decreasing the measurement cost and time. However, interpolation methods are very sensitive to the availability of measurement data, and their performances largely depend on the measurement scheme or the sampling design, i.e., how to allocate measurement efforts. As such, sampling design is considered to be another important field that enables intelligent surface measurement. This paper reviews and summarizes the state-of-the-art research in interpolation and sampling design for surface measurement in varied manufacturing applications. Research gaps and future research directions are also identified and can serve as a fundamental guideline to industrial practitioners and researchers for future studies in these areas.

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Automated metrology and geometric analysis of additively manufactured lattice structures

Cited by 25 publications

References 21 publications

Emergency ventilator for COVID-19

Emergency ventilator for COVID-19

Advances in Metal Additive Manufacturing: A Review of Common Processes, Industrial Applications, and Current Challenges

Data-Driven Intelligent 3D Surface Measurement in Smart Manufacturing: Review and Outlook

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