Developing a should-cost model to predict display pricing in smartphones Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/kp78gk57v

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  • Companies working on new product development of smartphones seek to adopt designs and methodologies to help them stay competitive. Due to its high cost contribution to a smartphone, optimizing display cost is an important part of a smartphone's cost reduction activity. Hence, strategically sourcing displays in the development of smartphones leads to a significant decrease in production costs. The objective of this study is to utilize data available from the smartphone industry and separate the display cost based on the technical features of a display. Reports containing data on three hundred and fifty eight smartphones were collected from smartphone research firms and similar sources. Based on available data and by reviewing the literature on the subject, features of sub-components of a smartphone were identified to build a Bill-of-Material (BOM). The BOM was utilized to filter the database of smartphones at each stage of the analysis. A step wise analysis was performed to identify components that help define the retail price of the smartphones. After performing analysis to predict retail prices, the analysis is narrowed down to a smaller subset of detailed data to separate display features. A regression model with only display features was created. Cross-validation of data was performed to include all smartphone samples collected in the testing of the analysis. The outcome of the regression analysis was used to build a Should-Cost Model to predict display pricing. The resulting should-cost model can help analyze various causes that add to the cost of sourcing and hence serve as a good first hand basis for analyzing components/materials. As a result, this model would assist in effective negotiations ahead of sourcing.
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  • description.provenance : Submitted by Viswanath Parameshwaran Kashi (paramesv@onid.orst.edu) on 2014-10-20T20:19:42Z No. of bitstreams: 1 ParameshwaranKashiViswanath2014.pdf: 2169137 bytes, checksum: e382cd6fba7560ac8e4479c9c25aabda (MD5)
  • description.provenance : Made available in DSpace on 2014-10-21T18:07:59Z (GMT). No. of bitstreams: 1 ParameshwaranKashiViswanath2014.pdf: 2169137 bytes, checksum: e382cd6fba7560ac8e4479c9c25aabda (MD5) Previous issue date: 2014-09-15
  • description.provenance : Submitted by Viswanath Parameshwaran Kashi (paramesv@onid.orst.edu) on 2014-10-10T19:01:23Z No. of bitstreams: 1 ParameshwaranKashiViswanath2014.pdf: 2123143 bytes, checksum: 89ed5235a91c7269a4a67392ed8025b6 (MD5)
  • description.provenance : Approved for entry into archive by Julie Kurtz(julie.kurtz@oregonstate.edu) on 2014-10-21T16:33:25Z (GMT) No. of bitstreams: 1 ParameshwaranKashiViswanath2014.pdf: 2169137 bytes, checksum: e382cd6fba7560ac8e4479c9c25aabda (MD5)
  • description.provenance : Rejected by Julie Kurtz(julie.kurtz@oregonstate.edu), reason: Rejecting to remove the page numbers (Roman numerals) in the pretext pages starting with the Table of Contents. Also add the underlines back on the Abstract page under, your name, Master of Science, Industrial Engineering, September 15, 2014 and thesis title. Everything else looks good. Once revised, log back into ScholarsArchive and go to the upload page. Replace the attached file with the revised PDF and resubmit. Thanks, Julie on 2014-10-17T21:14:39Z (GMT)
  • description.provenance : Approved for entry into archive by Laura Wilson(laura.wilson@oregonstate.edu) on 2014-10-21T18:07:59Z (GMT) No. of bitstreams: 1 ParameshwaranKashiViswanath2014.pdf: 2169137 bytes, checksum: e382cd6fba7560ac8e4479c9c25aabda (MD5)

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