January 6th, 2021
In a previous blog we provided an overview of Foundry, Digital Alloys’ software platform for implementing Joule Printing™ in production applications and delivering efficient operation of printers at factory-scale. Subsequent posts provided overviews of a few of the modules in Foundry - Build Planner, and Printer Console & Operations Manager. This blog describes Data Analyzer, our software platform for quality assurance and data analysis. Data Analyzer, together with the other software modules, provides for non-destructive inspection of printed parts - a powerful capability for quality control in a Joule Printing™ factory.
Successful use of 3D printing in production requires a consistent and repeatable production process that delivers high quality parts. Joule Printing™ and Foundry deliver such a process through three components. Printer Console powers the first two components: closed-loop process control, and process data management. The third component, powered by Data Analyzer, is QA & data analysis using the data captured by Printer Console.
Joule Printing™ provides fine-grained real-time process control of the elements essential for quality metal 3D printing, and records data from the control system in real-time at millisecond intervals. Sophisticated embedded algorithms control the three key elements:
- Printer Management - The system provides a smooth, automated and intuitive interface for operating each printer. It also provides remote monitoring for supervision of a fleet of printers.
- Process Control - The Printer Console operates sophisticated embedded control algorithms that ensure that the Joule Printer™ delivers fast, low-cost, high-quality parts in a consistent and reliable fashion.
- Print Data Management - The software captures essential data for post-print analysis and quality assurance (QA), including print configuration, process data, video, and metadata for cataloguing a large number of prints.
- Data Management for Manufacturing Execution System and Enterprise Resource Planning (MES/ERP) - A Joule Printer™ fleet will be part of a larger production facility. As such, it should be easy to integrate with MES/ERP systems, and provide data for cost analysis, inventory management, and optimizing the scheduling and utilization of printers.
- Maintenance, Repair and Operation (MRO) - Foundry provides capability for monitoring and tracking needed for maintenance and repair of the printer fleet.
The tight control of process parameters allows the system to deliver consistently dense (99.5%+), strong, isotropic parts. Printer Console logs the process data together with video of the print, configuration parameters, and other key measurements to provide the capability for post-print analysis.
The system captures both print video and process control data.
After printing, the operator or QA technician can use the Foundry Operations Manager to retrieve data for any print run. A table of prints provides a real time view of activity with links to Data Analyzer. With a single click, the user can select a specific part ID to launch Data Analyzer and open a complete record of the print, including configuration data, video, and recorded process data. The rich platform and tool set of Data Analyzer is then used for QA & data analysis.
Data Analyzer allows viewing and analyzing data from the many sources captured in Foundry. It provides a simple GUI for selecting, filtering, and plotting data streams – eliminating the need to download data files to an external software package. Data Analyzer allows the creation of custom plots for process signals. The graphs can then be manipulated and navigated to focus the data on informative events (as shown in Figure 4). As an example, a QA technician could use this capability to identify regions where a print process deviated from preset operating bounds.
Data Analyzer includes a development environment that allows researchers and QA analysts to rapidly create python scripts for advanced analysis. Figure 5 shows an example. For this analysis, an operator created a plot showing process power for every location in nine layers of a printed watch case. If there were peaks and valleys in process power that exceeded threshold values, that could indicate variations in material properties or defects.
Peaks and valleys in process power would indicate potential defects in the part.
Data Analyzer also provides for integrating external data sources with print data. Figure 6 shows an example using three-dimensional profilometry data. The platform was used to correlate surface roughness with print process parameters, allowing a researcher to enhance control system parameters. Other applications include correlating part defects from a CAT scan or other measurements with print process parameters, accelerating our understanding of how process settings drive quality.
The strong capabilities of Data Analyzer - including the ability to explore correlations between process parameters, material properties, and defects - provide a strong backbone for non-destructive quality assurance of printed parts. Looking forward, Data Analyzer provides a data backbone that will be used to power a machine learning approach to automating the QA process. We are excited about future products we will announce in this arena.
Please check out other posts in our blog series:
Digital Alloys’ Guide to Metal Additive Manufacturing
Learn about the technology behind our process:
Duncan McCallum
CEO
Digital Alloys is committed to providing the technology and expertise manufacturers need to use metal additive manufacturing in production — enabling them to save time, shrink costs, and produce valuable new product.
