Abstract
Machine learning offers algorithms for extraction of knowledge in an understandable form based on historical data. It is viewed as a key tool in development of autonomous systems. This chapter shows that learning algorithms can be used for novel problem solving in engineering design and manufacturing. Decomposition is a key problem in the latter two application areas. A data mining approach is used for matrix decomposition for the case with unknown and known decisions associated with each object in the matrix. Of particular interest to control of manufacturing processes is the case when decisions, e.g., product quality, are ill-defined. Data mining is a viable tool for solving problems with ill-defined outcomes.
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Kusiak, A. (2001). Non-Traditional Applications of Data Mining. In: Braha, D. (eds) Data Mining for Design and Manufacturing. Massive Computing, vol 3. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-4911-3_17
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DOI: https://doi.org/10.1007/978-1-4757-4911-3_17
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