Abstract
Six Sigma is a well-regarded and proven methodology for improving the quality of products and services by removing inconsistencies in processes. Insomuch of the early Six Sigma initiatives was focused on process effectiveness in meeting quality expectations and process efficiency for achieving maximum producer value; the future trends is moving towards utilizing feedback loops to create intelligent processes that enhances the adaptability to changing conditions. The purpose of this chapter is to extend understanding of what performance measures can be applied to processes in order to gain useful information and the emerging application of artificial neural networks to handle concurrent multiple feedback loops.
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Fogal, J. (2016). Process Improvement Using Intelligent Six Sigma. In: Kahraman, C., Yanik, S. (eds) Intelligent Decision Making in Quality Management. Intelligent Systems Reference Library, vol 97. Springer, Cham. https://doi.org/10.1007/978-3-319-24499-0_12
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DOI: https://doi.org/10.1007/978-3-319-24499-0_12
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