scholarly journals OPTIMIZING THE TLD-100H READOUT SYSTEM UNDER VARIOUS RADIOACTIVE I-131 DOSES VIA THE REVISED TAGUCHI DYNAMIC QUALITY LOSS FUNCTION

2020 ◽  
Vol 20 (10) ◽  
pp. 2040024
Author(s):  
LUNG-FA PAN ◽  
YINGYI LE ◽  
YU-CHEN YEN ◽  
JUI-HUNG WENG ◽  
CHIEN-YI CHEN ◽  
...  

The TLD-100H readout system performance under various radioactive I-131 exposure doses was optimized by four key factors via the revised Taguchi dynamic quality loss function. Taguchi dynamic analysis and the orthogonal array reorganizing the essential factors are crucial for the optimization of the thermoluminescent dosimeter (TLD) readout system given strict criteria of multiple irradiated environments and long-term exposure for calibrated TLDs. Accordingly, 96 TLD-100H chips were selected and randomly categorized into three batches with eight groups (four TLD chips in each group). Four factors, namely (1) initial temperature, (2) heating rate, (3) maximal temperature, and (4) TLD preheat time before reading were organized into eight combinations according to Taguchi suggestion, whereas each factor was preset at two levels. All 96 [Formula: see text] chips were put in three concentric circles with 30, 60, and 90 cm radii for 48 h, surrounding the radioactive 150[Formula: see text]mCi ([Formula: see text][Formula: see text]MBq) I-131 capsule and exposed to the cumulative doses of 88.2, 18.6, and 8.6[Formula: see text]mSv for the respective radii, accordingly. The TLD readings obtained from each group were analyzed to derive the sensitivity, coincidence, and reproducibility, then those were reorganized to draw four fish-bone-plots for the optimization. The optimal option for the TLD readout system implied the combination of A1 (a [Formula: see text]C initial temperature), B1 (a [Formula: see text]C/s heating rate), C1 (a [Formula: see text]C maximal temperature), and D2 (a 15[Formula: see text]s preheat time), which was further verified by the follow-up measurements. The dominant factors were A (initial temperature) and B (heating rate), whereas C (maximal temperature) and D (preheat time) were minor and provided negligible contributions to the system performance optimization.


Author(s):  
GUANGMING CHEN ◽  
KAILASH C. KAPUR

Tolerance design technique balances the expected quality loss due to variations of the system performance and the cost due to controlling these variations. Measures of quality are discussed and quality loss function is used for tolerance design. The goal is to minimize the total loss that consists of the quality loss to the customer and the cost increase to the producer. The design methodologies are presented for the tolerances of products before shipping to the customer and the tolerances of lower-level characteristics. The approaches to tolerance design for components and subsystems are also demonstrated using the variation transfer function. Examples are given as illustrations of the methodology.





Author(s):  
Elizabeth Cudney ◽  
Bonnie Paris

Using the quadratic loss function is one way to quantify a fundamental value in the provision of health care services: we must provide the best care and best service to every patient, every time. Sole reliance on specification limits leads to a focus on “acceptable” performance rather than “ideal” performance. This paper presents the application of the quadratic loss function to quantify improvement opportunities in the healthcare industry.



2013 ◽  
Vol 655-657 ◽  
pp. 2331-2334 ◽  
Author(s):  
Qiu Jin ◽  
Shao Gang Liu

The asymmetric quality loss functions with the triangular distribution for determining the optimum process mean are studied. The condition of using the linear and quadratic asymmetric quality loss function in the model is considered. The eight mathematical models under an asymmetric quality loss function with the triangular distribution based on the analysis of the linear and quadratic asymmetric quality loss function are presented. Finally, the validity of models is verified by the examples.



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