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oai:www.ideals.illinois.edu:2142/99171 2023-07-11 col_2142_5131 col_2142_16359 com_2142_5130 com_2142_16358 com_2142_234

Thurston, Deborah Liu, Xinlu 2018-03-13T15:20:55Z 2018-03-13T15:20:55Z 2020-03-14T09:15:16Z 2017-09-13 2017-12 Medical equipment manufacturing companies that provide maintenance and product take-back programs have limited information about location and severity of defects, and the condition of the product before making decisions about whether to repair, recycle, remanufacture, refurbish or call-back and scrap the product. The first step is to estimate the residual value of the product. The current methods depends on the owner-claimed condition of the product and the number of accessories. However, the claimed condition is highly subjective and of high degree of variability, even of the same claimed condition and number of accessories. Such high variability in real value is considered to be caused by different working environments and customer user behavior. This thesis proposes a sensor based model to more accurately predict residual value and the actual condition of the product based on measuring the environment and working condition of the product real-time. The model provides suggestions for each individual product based on its quality level and component reliability level. A patient monitor was used as an example. The simulated result showed that the proposed method could significantly reduce the loss from variance in quality of products. Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2019-12-01 The student, Xinlu Liu, accepted the attached license on 2017-08-28 at 11:29. The student, Xinlu Liu, submitted this Thesis for approval on 2017-08-28 at 11:36. This Thesis was approved for publication on 2017-09-13 at 14:12. DSpace SAF Submission Ingestion Package generated from Vireo submission #11618 on 2018-03-13 at 09:54:43 Made available in DSpace on 2018-03-13T15:20:55Z (GMT). No. of bitstreams: 2 LIU-THESIS-2017.pdf: 1813471 bytes, checksum: 5f8506e34339ca531541eafb751e67c4 (MD5) LICENSE.txt: 4206 bytes, checksum: 0cf4764b0f36c26da700642bca53182d (MD5) Previous issue date: 2017-09-13 Embargo set by: Seth Robbins for item 105133 Lift date: 2020-03-13T15:21:19Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system Embargo set by: Seth Robbins for item 105133 Lift date: 2020-03-13T15:25:40Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system Embargo set by: Seth Robbins for item 105133 Lift date: 2020-03-13T15:28:52Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system U of I Only Restriction Lifted for Item 105133 on 2020-03-14T09:15:16Z. application/pdf http://hdl.handle.net/2142/99171 en Copyright 2017 Xinlu Liu Sensor Residual value estimation Sensor-based maintenance cost estimation and residual value estimation for medical equipment recycling text text Industrial&Enterprise Sys Eng Systems & Entrepreneurial Engr University of Illinois at Urbana-Champaign Thesis M.S.