Process Monitoring and Defect Detection of Additive Manufacturing Using Inline Coherent Imaging

With applications ranging from aerospace to biomedicine, additive manufacturing (AM) has been revolutionizing the manufacturing industry. The ability of additive techniques, such as selective laser melting (SLM), to create fully functional, geometrically complex, and unique parts out of high strength materials is of great interest. Unfortunately, despite numerous advantages afforded by this technology, its widespread adoption is hindered by a lack of on-line, real time feedback control and quality assurance techniques. In this thesis, inline coherent imaging (ICI), a broadband, spatially coherent imaging technique, is used to observe the SLM process in 15 - 45 $\mu m$ 316L stainless steel. Imaging of both single and multilayer builds is performed at a rate of 200 $kHz$, with a resolution of tens of microns, and a high dynamic range rendering it impervious to blinding from the process beam. This allows imaging before, during, and after laser processing to observe changes in the morphology and stability of the melt. Galvanometer-based scanning of the imaging beam relative to the process beam during the creation of single tracks is used to gain a unique perspective of the SLM process that has been so far unobservable by other monitoring techniques. Single track processing is also used to investigate the possibility of a preliminary feedback control parameter based on the process beam power, through imaging with both coaxial and 100 $\mu m$ offset alignment with respect to the process beam. The 100 $\mu m$ offset improved imaging by increasing the number of bright A-lines (i.e. with signal greater than the 10 $dB$ noise floor) by 300\%. The overlap between adjacent tracks in a single layer is imaged to detect characteristic fault signatures. Full multilayer builds are carried out and the resultant ICI images are used to detect defects in the finished part and improve upon the initial design of the build system. Damage to the recoater blade is assessed using powder layer scans acquired during a 3D build. The ability of ICI to monitor SLM processes at such high rates with high resolution offers extraordinary potential for future advances in on-line feedback control of additive manufacturing.

Ablation of Steel by Microsecond Pulse Trains

Laser micromachining is an important material processing technique used in industry and medicine to produce parts with high precision. Control of the material removal process is imperative to obtain the desired part with minimal thermal damage to the surrounding material. Longer pulsed lasers, with pulse durations of milli- and microseconds, are used primarily for laser through-cutting and welding. In this work, a two-pulse sequence using microsecond pulse durations is demonstrated to achieve consistent material removal during percussion drilling when the delay between the pulses is properly defined. The light-matter interaction moves from a regime of surface morphology changes to melt and vapour ejection. Inline coherent imaging (ICI), a broadband, spatially-coherent imaging technique, is used to monitor the ablation process. The pulse parameter space is explored and the key regimes are determined. Material removal is observed when the pulse delay is on the order of the pulse duration. ICI is also used to directly observe the ablation process. Melt dynamics are characterized by monitoring surface changes during and after laser processing at several positions in and around the interaction region. Ablation is enhanced when the melt has time to flow back into the hole before the interaction with the second pulse begins. A phenomenological model is developed to understand the relationship between material removal and pulse delay. Based on melt refilling the interaction region, described by logistic growth, and heat loss, described by exponential decay, the model is fit to several datasets. The fit parameters reflect the pulse energies and durations used in the ablation experiments. For pulse durations of 50 us with pulse energies of 7.32 mJ +/- 0.09 mJ, the logisitic growth component of the model reaches half maximum after 8.3 us +/- 1.1 us and the exponential decays with a rate of 64 us +/- 15 us. The phenomenological model offers an interpretation of the material removal process.

Adding Run-Time Monitoring to UML-RT by Modifying the Papyrus-RT Code Generator

In Model-Driven Engineering (MDE), the developer creates a model using a language such as Unified Modeling Language (UML) or UML for Real-Time (UML-RT) and uses tools such as Papyrus or Papyrus-RT that generate code for them based on the model they create. Tracing allows developers to get insights such as which events occur and timing information into their own application as it runs. We try to add monitoring capabilities using Linux Trace Toolkit: next generation (LTTng) to models created in UML-RT using Papyrus-RT. The implementation requires changing the code generator to add tracing statements for the events that the user wants to monitor to the generated code. We also change the makefile to automate the build process and we create an Extensible Markup Language (XML) file that allows developers to view their traces visually using Trace Compass, an Eclipse-based trace viewing tool. Finally, we validate our results using three models we create and trace.

Supporting the Model-Driven Development of Real-time Embedded Systems with Run-Time Monitoring and Animation via Highly Customizable Code Generation

This paper presents a vision that allows the combined use of model-driven engineering, run-time monitoring, and animation for the development and analysis of components in real-time embedded systems. Key building block in the tool environment supporting this vision is a highly-customizable code generation process. Customization is performed via a configuration specification which describes the ways in which input is provided to the component, the ways in which run-time execution information can be observed, and how these observations drive animation tools. The environment is envisioned to be suitable for different activities ranging from quality assurance to supporting certification, teaching, and outreach and will be built exclusively with open source tools to increase impact. A preliminary prototype implementation is described.