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The purpose of this special issue of IISE Transactions on Additive Manufacturing is to create a repository of cuttingedge industrial engineering research work illustrating the impact of additive manufacturing on design and manufacturing. An open call for papers on IISE Transactions was announced in March 2017. The eight articles published herein were selected among 20 submitted manuscripts, following the standard, rigorous review procedure of IISE Transactions. The topics can be classified into four categories. The first category includes three articles on AM process modeling that study the spatial distribution of porosity (by J. Liu, C. Liu, Y. Bai, P. Rao, C. Williams and Z. Kong), surface roughness (by L. Li, A. Haghighi and Y. Yang), and heat distribution (by K. Karayagiz, A. Elwany, G. Tapia, B. Franco, L. Johnson, J. Ma, I. Karaman & R. Arr oyave). The second category includes two articles on AM process monitoring that develop new catadioptric stereo system for droplet monitoring (by T. Wang, C. Zhou and W. Xu) and physics based compressive sensing (by Y. Lu and Y. Wang). The third category includes two articles that study AM production control, i.e., job sizing and sequencing (by Y. Luzon and E. Khmelnitsky) and tool path planning (by Y. Jin, H. A. Pierson and H. Liao). The last category includes one article on AM processing techniques related to surface texture generation (by U. Yaman, M. Dolen and C. Hoffmann). The first paper entitled “Layer-Wise Spatial Modeling of Porosity in Additive Manufacturing” by J. Liu, C. Liu, Y. Bai, P. Rao, C. Williams and Z. Kong models and quantifies the layerwise spatial evolution of porosity in parts made using AM processes to address porosity’s impact on the functional integrity of AM parts such as their fatigue life and strength. An Augmented Layer-wise Spatial log Gaussian Cox process (ALS-LGCP) model is proposed to understand where (at what location), when (at which layer), and to what severity (size and number) pores are formed. The ALS-LGCP approach is tested for metal parts made using a binder jetting AM process to model the layer-wise spatial behavior of porosity. Based on offline, nondestructive X-Ray computed tomography (XCT) scan data of the part the approach identifies those areas with high risk of porosity with statistical fidelity approaching 85% (F-score). The second paper entitled “Theoretical Modeling and Prediction of Surface Roughness for Hybrid AdditiveSubtractive Manufacturing Processes” by L. Li, A. Haghighi and Y. Yang, develops a new analytical model to predict the surface roughness of parts fabricated by AM processes as well as hybrid additive-subtractive manufacturing processes. A novel surface profile representation scheme is also proposed to increase the prediction accuracy. Case studies are performed to validate the effectiveness of the proposed model. The third paper entitled “Numerical and Experimental Analysis of Heat Distribution in the Laser Powder Bed Fusion of Ti-6Al-4V” by K. Karayagiz, A. Elwany, G. Tapia, B. Franco, L. Johnson, J. Ma, I. Karaman & R. Arr oyave presents a three-dimensional finite element (FE) model to study the thermal behavior during SLM of Ti-6Al-4V alloy. The model considers different phase transitions: solid-toliquid and liquid-to-gas. It is demonstrated that metal evaporation has a notable effect on the thermal history that evolves during fabrication. The model is validated through experimental measurements of different features including the size and morphology of heat affected zone (HAZ), size of melt, thermal history, and sample cooling rate. The fourth paper entitled “Online Droplet Monitoring in Inkjet 3D Printing Using Catadioptric Stereo System” by T. Wang, C. Zhou and W. Xu develops a novel catadioptric stereo system for online droplet monitoring in inkjet 3D printing process with multi-material deposition capability. In this system, a CCD camera is coupled with a flat mirror and magnification lens system to capture the tiny droplet images to detect the droplet location in 3D space. A mathematical model is formulated to calculate the droplet location in 3D world space from 2D image space. A holistic hardware and software framework are constructed to evaluate the performance of the proposed system in terms of resolution, accuracy, efficiency and versatility both theoretically and experimentally. The results show that the proposed catadioptric stereo system can achieve single micron resolution and accuracy, which is one order of magnitude higher than the 3D printing system itself. The fifth paper entitled “An Efficient Transient Temperature Monitoring of Fused Filament Fabrication Process with PhysicsBased Compressive Sensing” by Y. Lu and Y. Wang aims to reduce the number of sensors in AM process monitoring using a physics based compressive sensing (PBCS) approach. This approach improves the compression ratio by formulating a transient thermal model. Three-dimensional thermal distributions can be efficiently monitored by reconstructing distributions from sparse sampling in both spatial and temporal domains. The systematic error from reconstruction can also be predicted and compensated based on a Gaussian process uncertainty quantification approach. This new process monitoring approach is demonstrated with material extrusion process. The sixth paper entitled “Job Sizing and Sequencing in Additive Manufacturing to Control Process Deterioration” by Y. Luzon and E. Khmelnitsky addresses the problem of sequencing an AM process under the uncertainty of printing failures. They also consider a more complicated environment in which the work may arrive over time. Authors adopt a stochastic preemptive-repeat scheduling model, generalize it to incorporate the process age and develop the formalization of two main measures of a given schedule: the expected completion time and the total expected flow time. Their formalization enables the determination of a schedule that minimizes these