Outpatient process quality evaluation and the Hawthorne Effect

2006 ◽  
Vol 63 (9) ◽  
pp. 2330-2340 ◽  
Author(s):  
Kenneth Leonard ◽  
Melkiory C. Masatu
Keyword(s):  
Quality Evaluation ◽  
Process Quality ◽  
Hawthorne Effect

Green Pea and Garlic Puree Model Food Development for Thermal Pasteurization Process Quality Evaluation

2017 ◽  
Vol 82 (7) ◽  
pp. 1631-1639 ◽  
Author(s):  
Ellen R. Bornhorst ◽  
Juming Tang ◽  
Shyam S. Sablani ◽  
Gustavo V. Barbosa-Cánovas ◽  
Fang Liu
Keyword(s):  
Quality Evaluation ◽  
Process Quality ◽  
Model Food ◽  
Green Pea ◽  
Thermal Pasteurization

PEM: The small company-dedicated software process quality evaluation method combining CMMISM and ISO/IEC 14598

2006 ◽  
Vol 14 (1) ◽  
pp. 7-23 ◽  
Author(s):  
Sylvie Trudel ◽  
Jean-Marc Lavoie ◽  
Marie-Claude Paré ◽  
Witold Suryn
Keyword(s):  
Quality Evaluation ◽  
Evaluation Method ◽  
Software Process ◽  
Process Quality ◽  
Small Company

Process Quality Evaluation Based on Maximum Entropy Principle

2014 ◽  
Vol 668-669 ◽  
pp. 1625-1628
Author(s):  
Yu Hong Wang ◽  
Chuan Liang Zhang ◽  
Wei Dai ◽  
Yu Zhao
Keyword(s):  
Maximum Entropy ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Maximum Entropy Principle ◽  
Processing Parameters ◽  
Process Quality ◽  
Physics Of Failure ◽  
Equipment Reliability ◽  
Entropy Principle ◽  
Relation Model

Process quality evaluation plays a significant role in ensuring product quality and improving customer satisfaction. Currently, the research on process quality evaluation lacks consideration of interactive coupling between product processing parameters and equipment reliability. With using the analysis of physics of failure, the relation model between the products quality and the processing equipment reliability was established. Besides, based on Maximum Entropy Principle (MEP), an evaluation method of process quality was provided. Finally, we verified the feasibility of the method through the combination in an application case.

scholarly journals Process-Quality Evaluation for Wire Bonding With Multiple Gold Wires

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 106075-106082 ◽  
Author(s):  
Chun-Min Yu ◽  
Kuei-Kuei Lai ◽  
Kuen-Suan Chen ◽  
Tsang-Chuan Chang
Keyword(s):  
Quality Evaluation ◽  
Process Quality ◽  
Wire Bonding ◽  
Gold Wires

scholarly journals A Model for Evaluating the Performance of the Bearing Manufacturing Process

2019 ◽  
Vol 9 (15) ◽  
pp. 3105 ◽  
Author(s):  
Chen ◽  
Yu ◽  
Hsu ◽  
Cai ◽  
Chiou
Keyword(s):  
Performance Evaluation ◽  
Quality Evaluation ◽  
Process Quality ◽  
Process Performance ◽  
Market Demand ◽  
Quality Indices ◽  
Time Performance ◽  
The Stability ◽  
Accuracy Indices ◽  
Manufacturing Time

Reliability and product process quality are essential in meeting market demand and enhancing competitiveness in the machine tool industry. In addition, manufacturing time performance is also one of the important indices. Therefore, this paper focuses on process quality and manufacturing time and defines a manufacturing time performance index to feedback the acceptance rate of the manufacturing time. The process performance evaluation chart delineated the observations of variations in various workstations, and, hence, in controlling the stability of the work process. The Six Sigma quality indices are constructed by the process accuracy indices and precision indices are represented by X-axis and Y-axis respectively. The process quality evaluation chart evaluates the level of the process quality, as well as proposes the direction of improvement. The manufacturing time performance—Z-axis is used to assess whether the manufacturing time performance meets the requirements. The process performance evaluation chart constructed by this paper makes it easier for researchers to observe which workstations have a process variation in the process, to control the stability of the process effectively, to provide the improvement reference for staff on the scene and to enhance the competitiveness of the industry.

scholarly journals Process Quality Evaluation Model with Taguchi Cost Loss Index

2021 ◽  
Vol 11 (21) ◽  
pp. 10182
Author(s):  
Chiao-Tzu Huang ◽  
Kuei-Kuei Lai
Keyword(s):  
Confidence Interval ◽  
Quality Evaluation ◽  
Evaluation Model ◽  
Process Capability ◽  
Process Quality ◽  
Statistical Testing ◽  
Process Capability Indices ◽  
Capability Indices ◽  
Loss Index ◽  
Quality Evaluation Model

Process Capability Indices (PCIs) are not only a good communication tools between sales departments and customers but also convenient tools for internal engineers to evaluate and analyze process capabilities of products. Many statisticians and process engineers are dedicated to research on process capability indices, among which the Taguchi cost loss index can reflect both the process yield and process cost loss at the same time. Therefore, in this study the Taguchi cost loss index was used to propose a novel process quality evaluation model. After the process was stabilized, a process capability evaluation was carried out. This study used Boole’s inequality and DeMorgan’s theorem to derive the (1 – α) ×100% confidence region of (δ,γ2) based on control chart data. The study adopted the mathematical programming method to find the (1 – α) ×100% confidence interval of the Taguchi cost loss index then employed a (1 – α) ×100% confidence interval to perform statistical testing and to determine whether the process needed improvement.

Where Are We and What Shall We Do Next? A Qualitative Study of the Quality of Home Care in Shanghai, China

2020 ◽  
pp. 104365962091196
Author(s):  
Xianping Tang ◽  
Xuemei Chen ◽  
Bei Wu ◽  
Chenjuan Ma ◽  
Song Ge ◽  
...  
Keyword(s):  
Qualitative Study ◽  
Home Care ◽  
Evaluation System ◽  
Quality Evaluation ◽  
Process Quality ◽  
Outcome Quality ◽  
Structure Quality ◽  
Quality Evaluation System ◽  
Quality Of Home Care

Introduction: With the increasing need for home care in Shanghai, China, it is crucial to ensure its quality. This study aimed to explore quality-related issues of home care in Shanghai, China, and identify strategies for improvement. Method: This is a descriptive qualitative study. Semistructured interviews were conducted among 27 individuals, including home care managers ( n = 8), nurses ( n = 10), and patients and/or their caregivers ( n = 9). Colaizzi’s seven-step analysis method was used to guide data analysis. Results: Three themes emerged regarding the quality of home care in China: unsatisfactory structure quality, unsatisfactory process quality, and imperfect outcome quality evaluation system. Recommended strategies for quality improvement included issuing standards for home care evaluation, refining structure quality and process quality, and establishing an outcome quality evaluation system. Conclusions: Concerns about the quality of home care in China were identified by providers and patients. More research especially studies quantifying the care quality and its influencing factors are needed.

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