| Summary: | 碩士 === 元智大學 === 工業工程研究所 === 89 === Data visualization converts large amount of data into graphs to take advantages of human''s natural strength in rapid visual pattern recognition to enable easier, effective comprehension of data. In a previous research【sung ,1999】,we have developed a PCB WIP pattern visualization system that provides production managers a means to rapidly understand current production status, discover useful production information, and find out possible production problems from large amount of production data. The WIP Pattern of a product is converted into a small graph called a “smashed table” by smashing numbers in a table into small square dots. The smashed tables of multiple products are on the placed on the display screen according to the small multiple design principle【Tuffe,1983】.
Since WIP patterns are closely related to production status, products with similar WIP patterns should have similar production status. Based on this property, in this research we use the Hidden Markov Model to develop an automatic WIP pattern recognition technique to identify products that have similar WIP patterns and group these products together to enhance comparison and improve the effectiveness of visualization.
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