The Experts below are selected from a list of 52014 Experts worldwide ranked by ideXlab platform
Yu Bian - One of the best experts on this subject based on the ideXlab platform.
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Establishment of Vision Effect Diagram for Optimization of Smart LED Lighting
IEEE Photonics Journal, 2016Co-Authors: Qi Yao, Lei Yuan, Yu BianAbstract:In this paper, a Diagram illustrating the combined circadian Effect and mesopic vision Effect caused by cirtopic, scotopic, and photopic photoreceptors, i.e., a vision ef- fect Diagram, was established using a chromaticity Diagram based on L, M, and S cone cells for reference. The characteristics of the vision Effect Diagram were studied, and many features were found to be similar to those of the reference chromaticity Diagram. The relationship between the vision Effect and the chromaticity Diagrams was also stud- ied to ensure that the circadian and mesopic vision Effects would be present in the de- sired chromaticity range. The vision Effect Diagram is a mathematical tool that can be used to calculate and predict circadian and mesopic vision Effects of light sources, as well as to optimize light sources to induce these Effects. Optimized light sources with both desirable circadian and mesopic vision Effects would not only be useful when these two vision Effects are stimulated together but would do well in future smart light-emitting diode (LED) lighting with adjustable luminance in many outdoor applications as well.
T. Senthilvelan - One of the best experts on this subject based on the ideXlab platform.
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Optimizing Process Parameters of Screw Conveyor (Sugar Mill Boiler) Through Failure Mode and Effect Analysis (FMEA) and Taguchi Method
Journal of Failure Analysis and Prevention, 2014Co-Authors: A. Mariajayaprakash, T. SenthilvelanAbstract:This paper exhibits the failures of the boiler during the cogeneration process and provides solution to overcome the failures. The failures are frequently occurring in the screw conveyor of fuel-feeding system of the boiler and rarely occurring in the grate of the boiler. In this research work, three important statistical tools are employed to identify and further rectify the failures of the screw conveyor. The different techniques, viz., cause-and-Effect Diagram, failure mode and Effect analysis (FMEA), and the Taguchi method have been applied. The cause-and-Effect Diagram, is the primary tool used to sort out all the possible root causes of the failures. The process parameters that cause the failures in the screw conveyor are identified by FMEA. Since the conventional FMEA has some limitations, fuzzy FMEA is employed. The most critical parameters selected by conventional FMEA and fuzzy FMEA are fuel type, fuel moisture, drum speed, and air flow. Finally, the selected process parameters are optimized by the Taguchi method to prevent the failures occurring in the screw conveyor. Among the various process parameters, the parameter, fuel type, significantly affects the performance of the screw conveyor.
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failure detection and optimization of sugar mill boiler using fmea and taguchi method
Engineering Failure Analysis, 2013Co-Authors: A. Mariajayaprakash, T. SenthilvelanAbstract:Abstract Sugar industry plays an important role in economic development of country. Cogeneration is an important source of income for sugar industries. Boiler is one of the essential components used in cogeneration process. Unscheduled boiler outages in sugar mills are major problem resulting loss of production. The boiler may be failed due to number of reasons; some of the reasons such as mechanical failure, electrical failure and temperature sensors failure. This paper describes the failures of the fuel feeding system frequently occurred in the cogeneration boiler and gives the solution to rectify these failures by using three important tools, namely, cause and Effect Diagram, Failure Mode and Effect Analysis and Taguchi method.
Qi Yao - One of the best experts on this subject based on the ideXlab platform.
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Establishment of Vision Effect Diagram for Optimization of Smart LED Lighting
IEEE Photonics Journal, 2016Co-Authors: Qi Yao, Lei Yuan, Yu BianAbstract:In this paper, a Diagram illustrating the combined circadian Effect and mesopic vision Effect caused by cirtopic, scotopic, and photopic photoreceptors, i.e., a vision ef- fect Diagram, was established using a chromaticity Diagram based on L, M, and S cone cells for reference. The characteristics of the vision Effect Diagram were studied, and many features were found to be similar to those of the reference chromaticity Diagram. The relationship between the vision Effect and the chromaticity Diagrams was also stud- ied to ensure that the circadian and mesopic vision Effects would be present in the de- sired chromaticity range. The vision Effect Diagram is a mathematical tool that can be used to calculate and predict circadian and mesopic vision Effects of light sources, as well as to optimize light sources to induce these Effects. Optimized light sources with both desirable circadian and mesopic vision Effects would not only be useful when these two vision Effects are stimulated together but would do well in future smart light-emitting diode (LED) lighting with adjustable luminance in many outdoor applications as well.
Chen Zong-min - One of the best experts on this subject based on the ideXlab platform.
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Mathematics Theory Statistic Method in Quality Control of Casting
Hot Working Technology, 2004Co-Authors: Chen Zong-minAbstract:The basic applications of statistic methods and instruments in quality control of casting production such as pareto Diagram, cause and Effect Diagram, histogram, scattering Diagram, control Diagram are introduced through practical examples.
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Statistical methods in quality control of casting
2004Co-Authors: Chen Zong-minAbstract:Statistics is an Effective method for quality analysis. The most important in production are seven statistical methods and new seven QC tools. The production process of lathe bed casting being taken as an example, the methods of how to use pareto Diagram, cause and Effect Diagram, scatter Diagram, histogram and control chart during casting production are introduced.
Jari Vanhanen - One of the best experts on this subject based on the ideXlab platform.
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Diagrams or structural lists in software project retrospectives - An experimental comparison
Journal of Systems and Software, 2015Co-Authors: Timo O.a. Lehtinen, Mika V. Mäntylä, Juha Itkonen, Jari VanhanenAbstract:Root cause analysis (RCA) is a recommended practice in retrospectives and cause-Effect Diagram (CED) is a commonly recommended technique for RCA. Our objective is to evaluate whether CED improves the outcome and perceived utility of RCA. We conducted a controlled experiment with 11 student software project teams by using a single factor paired design resulting in a total of 22 experimental units. Two visualization techniques of underlying causes were compared: CED and a structural list of causes. We used the output of RCA, questionnaires, and group interviews to compare the two techniques. In our results, CED increased the total number of detected causes. CED also increased the links between causes, thus, suggesting more structured analysis of problems. Furthermore, the participants perceived that CED improved organizing and outlining the detected causes. The implication of our results is that using CED in the RCA of retrospectives is recommended, yet, not mandatory as the groups also performed well with the structural list. In addition to increased number of detected causes, CED is visually more attractive and preferred by retrospective participants, even though it is somewhat harder to read and requires specific software tools. Root cause analysis is a recommended practice in retrospectives.We compare the use of cause-Effect Diagram to the use of structural lists in root cause analysis.Cause-Effect Diagram improves the root cause analysis.Cause-Effect Diagram is preferred by participants (75%).