Analysis of energy efficiency and productivity in dry process in PCB manufacturing
Generally, the cleaning process in printed circuit board (PCB) manufacturing consists of prewash, wash, rinse, and drying stages. The prewash stage rinses off the gross contaminants from the board before the wash stage. In the wash stage, spray bar and nozzle assembly is used to remove all remaining...
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Veröffentlicht in: | International journal of precision engineering and manufacturing 2013-07, Vol.14 (7), p.1213-1221 |
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Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Generally, the cleaning process in printed circuit board (PCB) manufacturing consists of prewash, wash, rinse, and drying stages. The prewash stage rinses off the gross contaminants from the board before the wash stage. In the wash stage, spray bar and nozzle assembly is used to remove all remaining contaminants. An anti-dragout section exists between the wash and the rinse stages. The use of an air in this section helps prevent any liquid dragout from the wash to the rinse tank. Some cleaners also have a wet isolation that provides further rinsing off the wash water from the PCB. As the last stage of the cleaning process, at drying stage, high temperature and high pressure air is used to get rid of the remaining moist thoroughly. By the way, it is known that the dry process consumes a moderately large amount of electric power since high temperature and high pressure air are required in this stage. However, if the due date of a certain PCB product is not too much tight, it would be not necessary to increase the temperature and pressure to proceed with drying. Thus, in this research, after collecting the experimental data and modeling the situations with appropriate statistical models, we develop a heuristic approach to the dry process in order to find optimal operating condition which minimizes the energy consumption while meeting the due dates of the ordered products as exactly as possible. Through the heuristic algorithm, that is, interchange-crossover algorithm, we provide an optimal (or near optimal) operating condition which can minimize both the total energy consumption and total penalty cost incurred by earliness and tardiness at the same time. The performance of the other approach is also investigated and compared to that of the developed heuristic approach. |
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ISSN: | 2234-7593 2005-4602 |
DOI: | 10.1007/s12541-013-0165-0 |