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.

Yielding Behaviour of Electron Beam Lithography and Focused Ion Beam Made Nanocrystalline Micro/Nanopillars

Electron beam lithography (EBL) and focused ion beam (FIB) methods were developed in house to fabricate nanocrystalline nickel micro/nanopillars so to compare the effect of fabrication on plastic yielding. EBL was used to fabricate 3 μm and 5 μm thick poly-methyl methacrylate patterned substrates in which nickel pillars were grown by electroplating with height to diameter aspect ratios from 2:1 to 5:1. FIB milling was used to reduce larger grown pillars to sizes similar to EBL grown pillars. X-ray diffraction, electron back-scatter diffraction, scanning electron microscopy, and FIB imaging were used to characterize the nickel pillars. The measured grain size of the pillars was 91±23 nm, with strong <110> and weaker <111> and <110> crystallographic texture in the growth. Load-controlled compression tests were conducted using a MicroMaterials nano-indenter equipped with a 10 μm flat punch at constant rates from 0.0015 to 0.03 mN/s on EBL grown pillars, and 0.0015 and 0.015 mN/s on FIB-milled pillars. The measured Young’s modulus ranged from 55 to 350 GPa for all pillars, agreeing with values in the literature. EBL grown pillars exhibited stochastic strain-bursts at slow loading rates, attributed to local micro yield events, followed by work hardening. Sharp yield points were also observed and attributed to the gold seed layer de-bonding between the nickel pillar and substrate due to the shear stress associated with end effects that arise from the substrate constraint. The onset of yield ranged from 108 to 1800 MPa, which is greater than bulk nickel, but within values given in the literature. FIB-milled pillars demonstrated stochastic yield behaviour at all loading rates tested, yielding between 320 and 625 MPa. Deformation was apparent at FIB-milled pillar tops, where the smallest cross-sectional area was measured, but still exhibited superior yield strength to bulk nickel. The gallium damage at the outer surface of the pillars likely aids in dislocation nucleation and plasticity, leading to lower yield strengths than for the EBL pillars. Thermal drift, substrate effects, and noise due to vibrations within the indenter system contributed to variance and inconsistency in the data.

Communication-efficient decentralized sequential detection

The problem of decentralized sequential detection is studied in this thesis, where local sensors are memoryless, receive independent observations, and no feedback from the fusion center. In addition to traditional criteria of detection delay and error probability, we introduce a new constraint: the number of communications between local sensors and the fusion center. This metric is able to reflect both the cost of establishing communication links as well as overall energy consumption over time. A new formulation for communication-efficient decentralized sequential detection is proposed where the overall detection delay is minimized with constraints on both error probabilities and the communication cost. Two types of problems are investigated based on the communication-efficient formulation: decentralized hypothesis testing and decentralized change detection. In the former case, an asymptotically person-by-person optimum detection framework is developed, where the fusion center performs a sequential probability ratio test based on dependent observations. The proposed algorithm utilizes not only reported statistics from local sensors, but also the reporting times. The asymptotically relative efficiency of proposed algorithm with respect to the centralized strategy is expressed in closed form. When the probabilities of false alarm and missed detection are close to one another, a reduced-complexity algorithm is proposed based on a Poisson arrival approximation. In addition, decentralized change detection with a communication cost constraint is also investigated. A person-by-person optimum change detection algorithm is proposed, where transmissions of sensing reports are modeled as a Poisson process. The optimum threshold value is obtained through dynamic programming. An alternative method with a simpler fusion rule is also proposed, where the threshold values in the algorithm are determined by a combination of sequential detection analysis and constrained optimization. In both decentralized hypothesis testing and change detection problems, tradeoffs in parameter choices are investigated through Monte Carlo simulations.

A Fabry-Perot Refractometer for Chemical Vapor Sensing by Solid-Phase Microextraction

The contour lithography method [1] is used to improve the fabrication yield of previously demonstrated [2] microfluidic Fabry-Perot (FP) refractive index (RI) sensors. The sensors are then coated with polydimethylsiloxane (PDMS) based polymers to detect vapor analytes by solid-phase microextraction (SPME). Preliminary characterization of devices coated with two different polymers and exposed to xylenes vapors yields a maximum sensitivity of 0.015 nm/ppm and a detection limit below 120 ppm.