Conference Paper

Process control in a high-noise environment using a limited number of measurements

Sch. of Electr. & Comput Eng., Georgia Inst. of Technol., Atlanta, GA, USA
DOI: 10.1109/ACC.2003.1239084 Conference: American Control Conference, 2003. Proceedings of the 2003, Volume: 1
Source: IEEE Xplore

ABSTRACT In this paper, we develop a hybrid control algorithm that produces control values for processes where only a limited number of function evaluations are available for the control law generation. This situation arises, for example, in stencil printing processes in printed circuit board manufacturing, where the cost associated with multiple function evaluations is prohibitive: The proposed control algorithm is given by a modified version of a constrained conjugated-gradient method, transitioned into a windowed-smoothed block-form of the least-squares affine estimator.

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    • "During online optimization, the training of the ANN has to be done concurrently with the data acquisition of recently inspected PCBs. In the offline case, this model can serve as a test bed for optimization and/or tuning of more complex process control algorithms, like the one presented in [6]. The outline of this paper is as follows: In Section II a description of the SPP is given and in particular the performance objectives and process constraints are presented; this is followed by an ANN model analysis for the system in Section III. "
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    ABSTRACT: This paper presents a neural network model for the stencil printing process (SPP) in surface-mount technology (SMT) manufacturing of printed circuit boards (PCBs). A practical model description that decomposes the overall steady-state process in independently modeled subspaces is provided. The neural network model can be updated in real-time procuring a method to control the process by dynamically searching the optimal set point of the control variables. The optimization is performed by minimizing the weighted mean squared error with respect to the desired solder brick height or volume; furthermore, in the case when multiple solutions exist, the set point that yields the lowest variance is used. The process simulator is mainly suitable for offline testing and debugging of more complex closed-loop control algorithms for the SPP optimization providing a common and realistic framework for algorithm performance evaluation. An important consideration in this paper is based on the fact that the estimation of the sampled moments of the probability distributions is made using a statistically significant number of data samples from each board, for each component type, for each printing direction, and for each pad orientation.
    IEEE Transactions on Electronics Packaging Manufacturing 02/2008; 31(1-31):9 - 18. DOI:10.1109/TEPM.2007.914236 · 0.82 Impact Factor
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    • "When surface mount technology (SMT) evolves as driven by the continuing miniaturization of electronic components and ever-growing board complexity, in-line defect inspection has become common for ensuring reliable production. For example, as an in-line measurement technique, visual defect metrology is now widely utilized in assessing process capability (Cunninggham & MacKinnon 1998; Rao et al. 1996; Barajas et al. 2003). In discrete printed circuit board (PCB) assembly, the boards within each shift are visually inspected to monitor the variation on operational conditions. "
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    ABSTRACT: A pattern clustering algorithm is proposed in this paper as a statistical quality control technique for diagnosing the solder paste variability when a huge number of binary inspection outputs are involved. To accommodate this goal, a latent variable model is first introduced and incorporated into classical logistic regression model so that the interdependencies between measured physical characteristics and their relationship to the final solder defects can be explained. This probabilistic model also allows a maximum-likelihood principal component analysis (MLPCA) method to recognize the dimension of systematic causes contributing to solder paste variability. The correlated measurement variables are then projected onto the reduced latent space, followed by an appropriate clustering approach over the inspected solder pastes for variation interpretation and quality diagnosing. An application to a real stencil printing process demonstrates that this method facilitates in identifying the root causes of solder paste defects and thereby improving PCB assembly yield.
    IEEE Transactions on Electronics Packaging Manufacturing 11/2007; 30(4-30):299 - 305. DOI:10.1109/TEPM.2007.907576 · 0.82 Impact Factor
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    ABSTRACT: In this paper a control algorithm, that generates adequate machine settings for the Stencil Printing Process (SPP) in Surface Mount Technology manufacturing, is presented. The SPP is characterized by high process-noise levels, and by requiring constant solder-paste volume deposition at all times. Due to the prohibitive cost associated with extensive testing, only a limited amount of information can be used in the decision-making. The major constraint when controlling the SPP is that it is not possible to evaluate the output of the system an arbitrary number of times, since for each calculation the printing and inspection of at least one or even two new boards is required. These difficulties are addressed by the controller proposed in this paper, which is based on an algorithm for generating a sequence of iterative values that converge to an optimum set of machine parameters for a desired solder paste volume. The merit of the control is that it minimizes the variance and the steady state error of the weighted sample mean versus the desired height, which improves the quality of the process. In addition, it considers print direction and different component types independently. Finally, this controller also automatically corrects for the process errors associated with the loss of the solder-paste working-viscosity-point, which can occur due to unscheduled stops on the line, and for incorrect specification of machine parameters given by the operator.
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