Optimal lamination test of ethylene vinyl acetate sheets for solar modules

Chih-Chun Tsai

Journal of Applied Statistics, 2019, vol. 46, issue 13, 2388-2408

Abstract: Solar power is inexhaustible and has become one of the most appreciated alternative energy choices. In the development stage, solar modules are subjected to relevant reliability tests to ensure a long lifetime and optimal power generation efficiency. After the lamination process, the performance of solar modules is closely related to the degree of crosslinking of ethylene vinyl acetate (EVA) sheets. Traditionally, the degree of crosslinking on EVA sheets is obtained using the chemical extraction method to measure the gel content of these sheets. Motivated by lamination data, this study first constructed a statistical model to describe the relationship between the degree of crosslinking on EVA sheets and lamination time. Next, under the specification limits of the gel content of EVA sheets, the optimal lamination time of solar modules was derived, and the optimal allocation for measuring EVA sheets was addressed. The chemical extraction method is time consuming and leads to high pollution. The latest method is differential scanning calorimetric (DSC), which measures the curing degree of EVA sheets as the degree of crosslinking on these sheets. This study determined the specification limits of the curing degree under the DSC method. An example is presented to elucidate the proposed procedure.

Date: 2019
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/02664763.2019.1596230 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:46:y:2019:i:13:p:2388-2408

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CJAS20

DOI: 10.1080/02664763.2019.1596230

Access Statistics for this article

Journal of Applied Statistics is currently edited by Robert Aykroyd

More articles in Journal of Applied Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().