Statistics for Spatial Data.

http://www-personal.umich.edu/~ykoren/uploads/Design_of_Reconfigurable_Manufacturing_Systems.pdf

Design of reconfigurable manufacturing systems

System of experimental design : engineering methods to optimize quality and minimize costs

The sol-gel process

Stereolithography is a solid freeform technique (SFF) that was introduced in the late 1980s Although many other techniques have been developed since then, stereolithography remains one of the most powerful and versatile of all SFF techniques It has the highest fabrication accuracy and an increasing number of materials that can be processed is becoming available In this paper we discuss the characteristic features of the stereolithography technique and compare it to other SFF techniques The biomedical applications of stereolithography are reviewed, as well as the biodegradable resin materials that have been developed for use with stereolithography Finally, an overview of the application of stereolithography in preparing porous structures for tissue engineering is given

A review on stereolithography and its applications in biomedical engineering

In this paper, a state space model is developed to describe the dimensional variation propagation of multistage machining processes. A complicated machining system usually contains multiple stages. When the workpiece passes through multiple stages, machining errors at each stage will be accumulated and transformed onto the workpiece. Differential motion vector, a concept from the robotics field, is used in this model as the state vector to represent the geometric deviation of the workpiece. The deviation accumulation and transformation are quantitatively described by the state transition in the state space model. A systematic procedure that builds the model is presented and an experimental validation is also conducted. The validation result is satisfactory. This model has great potential to be applied to fault diagnosis and process design evaluation for complicated machining processes.

/pdf/state-space-modeling-of-dimensional-variation-propagation-in-2ql79j4wyv.pdf

State space modeling of dimensional variation propagation in multistage machining process using differential motion vectors

Dimensional accuracy is a key control issue in direct three-dimensional (3D) printing. Part shrinkage due to material phase changes often leads to deviations in the final shape, requiring extra post-machining steps for correction. Shrinkage has traditionally been analyzed through finite element simulation and experimental investigations. Systematic models for accuracy control through shrinkage compensation are rarely available, particularly for complete control of all local features. To fill the gap for direct printing and compensate for shape shrinkage, this article develops a new approach to (i) model and predict part shrinkage and (ii) derive an optimal shrinkage compensation plan to achieve dimensional accuracy. The developed approach is demonstrated both analytically and experimentally in a stereolithography process, one of the most widely employed 3D printing techniques. Experimental results demonstrate the ability of the proposed compensation approach to achieve an improvement of an order of magnit...

Optimal offline compensation of shape shrinkage for three-dimensional printing processes

Geometric fidelity of 3D printed products is critical for additive manufacturing (AM) to be a direct manufacturing technology. Shape deviations of AM built products can be attributed to multiple variation sources such as substrate geometry defect, disturbance in process variables, and material phase change. Three strategies have been reported to improve geometric quality in AM: (1) control process variables x based on the observed disturbance of process variables Δx, (2) control process variables x based on the observed product deviation Δy, and (3) control input product geometry y based on the observed product deviation Δy. This study adopts the third strategy which changes the computer-aided design (CAD) design by optimally compensating the product deviations. To accomplish the goal, a predictive model is desirable to forecast the quality of a wide class of product shapes, particularly considering the vast library of AM built products with complex geometry. Built upon our previous optimal compensation study of cylindrical products, this work aims at a novel statistical predictive modeling and compensation approach to predict and improve the quality of both cylindrical and prismatic parts. Experimental investigation and validation of polyhedrons a indicates the promise of predicting and compensating a wide class of products built through 3D printing technology.

Statistical Predictive Modeling and Compensation of Geometric Deviations of Three-Dimensional Printed Products

Machine learning in tolerancing for additive manufacturing

In a multi-operational machining process (MMP), the ﬁnal product variation is an accu-mulation or stack-up of variation from all machining operations. Modeling and control ofthe variation propagation is essential to improve product dimensional quality. This paperpresents a state space model and its modeling strategies to describe the variation stack-upin MMPs. The physical relationship is explored between part variation and operationalerrors. By using the homogeneous transformation approach, kinematic modeling of setupand machining operations are developed. A case study with real machined parts is pre-sented in the model validation. @DOI: 10.1115/1.1532007#

Qiang Huang

Papers

State space modeling of dimensional variation propagation in multistage machining process using differential motion vectors

Optimal offline compensation of shape shrinkage for three-dimensional printing processes

Statistical Predictive Modeling and Compensation of Geometric Deviations of Three-Dimensional Printed Products

Machine learning in tolerancing for additive manufacturing

Part Dimensional Error and Its Propagation Modeling in Multi-Operational Machining