Sensor-based maintenance cost estimation and residual value estimation for medical equipment recycling

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.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Systems & Entrepreneurial Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2018

Author dc:creator

• Liu, Xinlu

Contributors dc:contributor

• Thurston, Deborah

• Sensor
• Residual value estimation

Statement dc:rights

• Copyright 2017 Xinlu Liu

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/99171

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/99171