Company

Portfolio Data

Back to Company Search

ARCTOS Technology Solutions, LLC

Address

1270 N Fairfield Rd
Dayton, OH, 45432-2636
USA

View website

UEI: HX4BQCW632M9

Number of Employees: 240

HUBZone Owned: No

Woman Owned: No

Socially and Economically Disadvantaged: No

SBIR/STTR Involvement

Year of first award: 1983

Phase I Awards

Phase II Awards

78.57%

Conversion Rate

$1,562,766

Phase I Dollars

$9,491,803

Phase II Dollars

$11,054,569

Total Awarded

Awards

Up to 10 of the most recent awards are being displayed. To view all of this company's awards, visit the Award Data search page.

3D Additive Manufacturing Hybrid-Material Tiles

Amount: $749,953 Topic: AF182-021

The design and fabrication of new aircraft tires is a complex process that is dictated by numerous performance requirements. Typically, tire performance is demonstrated based on the operational loads and speeds required for successful takeoff and landing, however actual tire wear remains uncontrolled. The USAF developed a test program that uses runway surface replicas for tire wear prediction. Currently, these replicas are fabricated by specialized concrete manufacturers, which is expensive, time consuming, and precludes precise imitation of runway surfaces. One way to create exact runway replicas is to scan the actual runway surface to generate 3D data files, and fabricate tiles using additive manufacturing (AM). In Phase I, UTC successfully demonstrated the ability to fabricate replicas of runway surfaces with a Laser Powder Bed Fusion (LPBF) AM technique. In Phase II, UTC will scale the process up to full-size tiles and fully characterize the performance of fabricated parts intended for use by the AF LGTF to support laboratory tire wear testing. AM of test tiles presents an exceptional opportunity for accelerated production of high-fidelity runway surface replicas. Moreover, AM offers production stability as the government could own the equipment or outsource tile fabrication and thus control the production workflow.

SBIR

Phase II

2020

DOW

USAF

In-Situ Fringe Pattern Profilometry for Feed-Forward Process Control

Amount: $749,796 Topic: Z3

In Phase I the research team demonstrated a superior in situ profilometry sensor, based on fringe pattern projection, which quickly measures the whole build plate.nbsp; In this data, significant process phenomena are accurately measured and easily identified, such as spreading defects, rogue particles that have been sintered to the partrsquo;s surface, distortion, surface roughness variation, and virtually any geometric feature.nbsp; Of particular importance is the measurement of powder layer condensation and uniformity. This data serves as input to a model that generates feedforward information to adjust process parameters, resulting in better prediction and control of key material properties such as residual stress and density.nbsp;In Phase II the team will further improve the sensor and test the feedforward model.nbsp; After fine-tuning the modelling capability for stress and distortion, mechanical testing will be conducted to validate model performance and determine the effect of defects (measured with the profilometry) on mechanical performance.nbsp; The result will be real-time determination of part quality by a modelling tool that integrates profilometry-detected defects into the performance predictions. This novel data will then be used to feed and validate a fast-feedback look-up table (generated by inverting the feedforward model), for layer-to-layer laser parameter adjustment during builds.nbsp; Next, a new design of the profilometry sensor will be completed to make it very compact (a few inches) so it can easily be added to OEM AM machines.nbsp;nbsp;nbsp; Then the research team will implement a new sensing technique (with the same hardware) to record video-rate, measurements, at nanometer precision, of thermal expansion and shrinking during the melting process, thereby facilitating novel and powerful analysis of residual stress and/or delamination formation.nbsp; Finally, the research team will demonstrate the whole sensor/modelling package on a NASA geometry of interest.

SBIR

Phase II

2019

NASA

Additive Manufacturing Process Monitoring and Control Technologies

Amount: $999,940 Topic: DLA181-002

This SBIR will demonstrate coaxial thermal imaging using the Stratonics ThermaViz® sensor as a uniquely effective tool for tracking process metrics, at high-speed, during laser powder bed fusion (LPBF). The Phase II project will then develop this sensing technique for LPBF process qualification and closed-loop control. The key is integrating ThermaViz into UTC’s AMSENSE® in situ monitoring architecture, which enables automated data collection, tracking X/Y position of the melt pool on the build surface, and implementing data processing algorithms on time scales suitable for closed-loop control. Next the team will develop and implement algorithms for ThermaViz data that quantify build quality and enable real-time control. In parallel to the algorithm development, the research team will finalize the design of a low-cost “industrial grade” coaxial camera that can be implemented quickly across the DoD supply chain in Phase III, and then mount the final sensor on an EOS M280 system to demonstrate process control and qualification on the brand of LPBF system that is most relevant to the supply chain. Finally, the team will demonstrate that build performance can be equalized across disparate LPBF systems and on a design of interest to our supply chain partner, Honeywell.

SBIR

Phase II

2019

DOW

DLA

Additive Manufacturing Sensor Fusion Technologies for Process Monitoring and Control.

Amount: $999,973 Topic: DLA18A-001

This Phase II project aims to assemble the key set of sensor modalities that are needed to reliably view the key process anomalies and properties of laser powder bed fusion. The research team will down-select from the Phase I sensors investigated and integrate the sensors into a sensor fusion software package that facilitates data collection and synchronization, and eventually feedback control of the AM process. The research team will then prove the sensors see all key process variations, and perform robust effect of defect studies that will supply the data needed for developing accurate process windows, and hence closed-loop feedback control algorithms. Next the team will determine what corrective actions are needed to fix the specific process variations that occur and implement those actions in the software system. The algorithms and sensing techniques will be demonstrated against baseline builds on multiple AM systems to prove their validity and capability, and a plan for transitioning the technology into the DoD supply chain will be developed.

STTR

Phase II

2019

DOW

DLA

Additive Manufacturing Process Monitoring and Control Technologies

Amount: $99,990 Topic: DLA181-002

This project aims to make Laser Powder Bed Fusion (LPBF) additive manufacturing a practical tool for supply chain management for the Defense Logistics Agency.The key step is developing process standardization to make LBPF quality vendor independent. This project will seek to demonstrate the use of a promising high speed melt pool monitoring device as a practical means to establish such process standardization. The do this, the R&D team will first identify a LPBF commercial machine model that is of the most value to the DoD (i.e. is used most heavily).Then an open-architecture LPBF system, equipped with the melt pool sensor, will be configured to replicate the build conditions and capability of the target commercial system.Experiments will be conducted to show that the sensor identifies critical process control information in this configuration, and then also in an alternative configuration.The sensors quantification of the difference in performance between the two configurations will then (in Phase II) serve as input to effect process modifications in each configuration, via closed loop feedback control, to equalize the build performance of the systems, thereby showing a practical method for build standardization.

SBIR

Phase I

2018

DOW

DLA

Dynamic Collaborative Visualization Ecosystem (DynaCoVE)

Amount: $99,945 Topic: A18-032

There is no one display device that is ideally suited for visualizing non-spatial, 1D, 2D, 3D, and 4D data. For this reason, a visualization ecosystem that unifies many components from the fields of scientific visualization, infovis, data analytics, big data, and display technologies is needed. This new tool will enable interactive scientific visualization across many different 2D, 2.5D and 3D display devices. The framework must be user and data centric. This will be accomplished via meta-data categorization to automatically establish a suite of algorithms and technologies that are suitable for the data, user, and display hardware at hand. In addition, the framework must remain algorithm and display technology agnostic. This will be done via a consistent interactive meta-visualization graph used across all devices. The system will abstract out cumbersome details such as format conversion and load balancing away from users to allow them to focus on visualizing their data. The new tool will be demonstrated on the many 2D, 2.5D, and 3D display devices in the Wright State University Appenzeller Visualization Laboratory. Test cases for the proof-of-concept will include interactive visualizations capturing 3D data on immersive displays with support from infovis methods on 2D displays.

SBIR

Phase I

2018

DOW

ARMY

The Hexahedralization Sensation

Amount: $150,000 Topic: AF173-007

Automatic conversion of computer aided drafting (CAD) geometry to computational grids appropriate for high fidelity hypersonic analysis is needed. With respect to grid quality, the output must be purely hexahedral and C2 continuous, even at extraordinary vertices. To accomplish this, a pipeline of local and global CAD repair algorithms will feed into a feature-preserving quadrangulation module with optional adaptive surface refinement. Catmull-Clark subdivision surfaces will be iteratively aligned to the quadrilateral surface meshes to provide a lightweight parametric representation. Recent advances from the computer graphics community will be employed to assure C2 continuity at extraordinary vertices. These techniques map a C2 continuous polynomial onto the subdivision surface with a C2 continuous compact weight function. The result will be projected back into the UV space of the input CAD to enable geometric surface sensitivities. Proven quadrangulation algorithms will then be extended to 3D hexahedralization to enable the automatic generation of purely hexahedral volumetric grids. Similarly, 3D subdivision volumes will map hexahedra to continuous, lightweight parametric representations. An additional library will be created to discretize the parametric grids and push them directly into processor memory. Bypassing the hard drive in this way is essential for parallel scalability to billions of grid cells.

SBIR

Phase I

2018

DOW

USAF

Additive Manufacturing Sensor Fusion Technologies for Process Monitoring and Control.

Amount: $99,989 Topic: DLA18A-001

Universal Technology Corporation (UTC) has teamed with the University of Dayton Research Institute (UDRI), Stratonics, and Macy Consulting to demonstrate not only the transitionability into commercial systems, but also to develop the data analytics and monitoring and control requirements to extract the full value fromseveral sensors, including the Stratonics ThermaViz, acoustic and profilometry sensors acquired by UDRI, and a low-cost sensor fusion system, AMSENSE, developed and sold by UTC.This project will judge the efficacy of each sensor for in-process monitoring and control of Laser Powder Bed Fusion (LPBF), and then decide which sensors should be combined into a new sensor fusion system that will finally enable qualified AM processes to exist en masse within the DoD supply chain.These decisions will be based on correlations between sensor data and final build results measured on physical test specimens.At the end of this project the research team will identify what future work is needed to implement the new sensor fusion system on DoD LPBF systems for real-time process control.

STTR

Phase I

2018

DOW

DLA

In-Situ Fringe Pattern Profilometry for Feed-Forward Process Control

Amount: $124,990 Topic: Z3

This project aims to implement novel techniques for feedforward and feedback controlthat will allowbetter control, validation, and documentation of Selective Laser Melting (SLM) additive manufacturing (AM). Three complimentary key innovations will be realizedin this project (two in Phase I and a third in Phase II) by combining and improving two current technologies. The first is the integration of Fringe Pattern Projection Profilometry (FPPP) into the SLM process. FPPP is the first profilometry technique that can capture high resolution dimensional measurements of the entire SLM build platform, in situ and nearly instantaneously. This facilitates direct dimensional measurement and validation of every single layer, and post-process 3D models (built from the measurements) for the digital twin. By capturing all dimensional information (including residual stress induced distortion) the FPPP sensor willprovidea unique set of data for calibration of AM modelling software, which is the second key innovation.The FPPP data will identify defects in layer morphologies that can be used to train unique integrated computational adaptive additive manufacturing (iCAAM) feedforward modeling tools (distortion is predicted and compensated for with the build strategy before the build starts). In most simulators, the layer thickness is assumed to be constant and perfect, but it is not.FPPP data will quantify the true variability present in layer thickness as the part is built. Access to this information will allow more accurate calibrationofthe modelso final part distortion can be virtually eliminated. In Phase II the model will also be inverted and turned into a fast-feedback lookup table for further tuning the build process to compensate forsuboptimal layer morphologies that may arise, which is the third key innovation. The result will be a combination of hardware and software tools that eliminate distortion and capture critical information for the digital twin.

SBIR

Phase I

2018

NASA

Acquisition, Control, and Visualization Platform for Occupancy Sensing and Related Smart Building Technologies

Amount: $149,960 Topic: AF173-001

Real-time occupancy sensing is one of the constant goals for energy managers across all facilities, buildings, and plants.The ability to know who or what is in a building and its characteristics for heating and cooling can give insight into improving building cost/energy efficiency and automatically respond to changes in environment, use, occupancy, and related parameters. There are a plethora of sensor types that should be integrated into such a system; however, COTS solutions in this field are generally proprietary and thus limited in compatibility from many perspectives.The UTC solution is a unified technology platform; a total solution that can be used for anything from testing new occupancy strategies to implementing automated HVAC controls.By building the foundation of this solution on an open-source, tested, interoperable framework, the UTC approach will deliver a solution that can detect and react based on pre-defined sensor patterns without compatibility or implementation limitations typical of existing COTS smart building packages.The UTC team, including UDRI, SlickLabs, Harbor Link, and Greenspace, has the BAS interoperability experience from previous efforts with AFCEC, experience with facility-related control systems (FRCS), and innovators in the occupancy sensing space.

SBIR

Phase I

2018

DOW

USAF