Yuangyai, Chumpol

Preferred name

Yuangyai, Chumpol

Alternative Name

Yuangyai, Čhumpol

Yuangyai, C.

Main Affiliation

School of Engineering

chumpol.yu@kmitl.ac.th

Now showing 1 - 10 of 18

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Investigating of antenna selection for the adaptive centroid localization systems
(2015-09-01)
Yuangyai, Chumpol
;
Pan, Chung Yu
;
Lin, Yi Jou
;
Cheng, Chen Yang
Location-based services are widely integrated in our daily lives, and they are used in various ways such as for investigating inventory goods and personal tracking in healthcare. With increasing applications of wireless localization, accuracy of location estimation requirements has become more critical. However, indoor localization suffers from multi-path interference that affects the traditional algorithmic calculation methods based on radio signal strength. The strength of radio signal depends significantly on antenna types and the deployment of wireless sensor network. Therefore, the aim of this paper is to investigate a robust deployment of wireless sensor network considering antennas and optimal signal range to increase signal strength and to reduce receiving signal missing. A bi-response design approach was taken to evaluate antenna selection, signal range, and antenna power rate. The experiment result was applied with existing algorithm to prove effectives. Further, to avoid wireless sensors collision which may result in low accuracy of receiving radio signal, adaptive weight center of gravity localization (AWCG) were proposed. AWCG is based on an assumption of the dynamic relationship between the radio signal strength and the distance in different environments at different times. In the proposed localization algorithm, the error distance was approximately one meter. It is expected to significantly improve the location estimation accuracy with the suggested deployment and proposed algorithm.
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Effect of Si on Microstructure and Corrosion Behavior of CoCrMo Alloys
(2018-06-04)
Peaubuapuan, Chonlawit
;
Tunthawiroon, Phacharaphon
;
Kanlayasiri, Kannachai
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Yuangyai, Chumpol
The aim of this research was to investigate the effect of silicon (Si) on the microstructure and corrosion behavior of CoCrMo alloys. The concentration of Si added in CoCrMo alloys was 0.1, 0.5 and 1 wt %. The corrosion behavior of the present alloys was investigated using potentiodynamic polarization measurements. The normal saline solution with 0.9 wt % was used as an electrolyte. Polarization curves obtained from the polarization test were used to evaluate in terms of corrosion current density (i<inf>corr</inf> ), corrosion potential (E<inf>corr</inf> ) and corrosion parameters that be used to compute corrosion resistant property of CoCrMo alloys. The microstructure of a sample during the polarization test was compared using X-ray diffraction (XRD) and optical microscope (OM). The results indicated that the increase in Si slightly changed the microstructure of CoCrMo alloys and could enhance the resistance to corrosion of CoCrMo alloys in NaCl solution. In addition, the reduction of Cr and Mo concentration in CoCrMo alloys was found to be a significant influence on the decrease in corrosion resistance.
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Statistical process control with autocorrelated data using neural networks
(2011-10-24)
Yuangyai, Chumpol
;
Abrahams, Rachel
Statistical Process Control (SPC) is widely used for monitoring the performance of processes in manufacturing. Traditional SPC methods require trained individuals to read data which results in slow and limited detection. Much research has been devoted into developing an online automated system for SPC, so that the abnormality can be detected quickly and corrected by the process operation. To build a system as such, artificial neural networks (ANN) are widely used as tools where complex patterns can be difficult to recognize. Many research projects involve using random data patterns for training and recognition of patterns for ANN/SPC applications. However, many manufacturing processes involve autocorrelated data, to determine the effect of autocorrelated data, green sand data was analyzed and a neural network was built and trained to analyze a number of out of control patterns. Overall, the network performed best for detecting larger mean shifts. © 2011 IEEE.
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Multiple-performance optimization for human-robot collaboration: A translation motion in a tele-sandblasting maintenance system
(2016-01-01)
Jientrakul, Ranon
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Yuangyai, Chumpol
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Chotiprayanakul, Pholchai
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Limnararat, Sunpasit
Human-robot collaboration is a vital part of teleoperation systems. Determining the design parameters satisfying the optimal human performance is very important in the design of a teleoperation system for a specific task. Specifically, to thoroughly represent human performance for a task, multiple performance measures in a teleoperation system are evaluated. The experiment was also conducted on a mixed-reality tele-sandblasting system which is setup to study 2D-motion translation in tele-sandblasting task. Then, identifying the design setting to satisfy the optimal measures are difficult due to conflicts among them. Therefore, this paper presents a multipleperformance optimization using a desirability function. The results provide the range of setting condition promoting the optimal human performance measures. © IEOM Society International.
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Variation minimization in tele-sandblasting system: The effect of human-arm movement error
(2018-08-14)
Jientrakul, Ranon
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Attavanish, Pornsak
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Chotiprayanakul, Pholchai
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Limnararat, Sunpasit
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Yuangyai, Chumpol
In tele-sandblasting task, human arm movement is a critical source of producing variation in position of sandblasting nozzle resulting in high operating cost and low productivity. Each operator behaves differently leading to unpredictable movements. Skilled operators are able to reduce the variation; however, developing skills requires a training period. In this paper, we proposed a new approach which is the use of a novel operator's arm movement pattern incorporated with a Kalman filter to reduce the effect of human-arm movement error. A virtual tele-sandblasting system is used to validate our approach. The experimental results verify that our proposed approach is able to significantly reduce the effect of human arm movement error. The approach helps operators to perform the task more comfortably and takes short training time.
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Decentralized Network Building Change in Large Manufacturing Companies towards Industry 4.0
(2017-01-01)
Poonpakdee, P.
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Koiwanit, J.
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Yuangyai, C.
In complex industrial ecosystems together with an increasing global competition, success depends on a complete value chain transformation. The use of Industry 4.0 standards is therefore gradually emerging in many industries to ensure significantly higher factory productivity, flexibility, and efficiency. However, selected methodology and results are required to be studied to fully understand the digital transformation as well as its characteristics. This research presents a system conversion study, from centralized to decentralized systems, using epidemic membership protocols on a large manufacturing company towards Industry 4.0. The system conversion shows that the epidemic membership protocols provide an ability to rewrite the structure of the overlay topology. The experimental results are presented in two categories: (1) convergence speed and (2) accuracy of the epidemic applications. These provide the information for the performance guarantee of the global aggregate computation. The expectation of this paper is to present a preliminary study focusing on the system conversion methodology in the context of Industry 4.0. There are several recent publications based on Industry 4.0; however, nothing has been done to address any methodologies applied in Industry 4.0 or their simulation results.
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Epidemic Algorithms on Distributed Systems Towards Industry 4.0
(2018-08-21)
Poonpakdee, Pasu
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Koiwanit, Jarotwan
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Yuangyai, Chumpol
In today changing world, with the advent of technology and a challenging competition, reliable information methodologies and tools are required to collaborate big data and various components in both vertical and horizontal integrations over the value chain. Cyber-Physical System or CPS is one of available technologies serving industries' needs and desires. However, its important properties are required to be investigated to fully understand its characteristics and performance. This study present an epidemic-based communication and the results show that the base station could obtain the higher accuracy of the information while the method was adopted.
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Intelligent robot of inclined assembly sequence planning in Industrial 4.0
(2018-08-14)
Chiang, Yu Cheng
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Yuangyai, Chumpol
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Cheng, Chen Yang
In the industry 4.0, the Cyber-physical system (CPS) is one of the most important core which makes the manufacturing process more intelligent. Intelligent assembly operation is an important key in intelligent manufacturing of CPS. To complete the intelligent assembly operation, the cooperation between assembly robotic arm and assembly sequence planning (ASP) is necessary. However, the ASP and writing robotic codes manually is time consuming and requires professional knowledge and experience. Because the Local Coordinate System (LCS) is often ignored when checking for interference. If product have inclined interference and without considering LCS and causing and infeasible ASP. Therefore, this paper proposes a LCCPIAS (Local Coordinate Cyber-Physical Intelligent Assembly System) system to achieve three objective functions. First, this paper presents a dual-projected-based interference analysis approach (DPIAA) that analyzes the relations between components. Second, this paper generates optimal assembly sequence automatically to let the assembly sequence more suitable for the robotic arm to perform the assembly operation. The last one is LCS can recognize inclined interference between components and generate feasible ASP. Furthermore, this paper uses CAD model to verify that the DPIAA is faster and consider LCS interference can solve inclined interference problem. In the future assembly factory, the proposed method can help to realize intelligent manufacturing.
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Robust parameter design for multiple-stage nanomanufacturing
(2012-07-01)
Yuangyai, Chumpol
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Nembhard, Harriet Black
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Hayes, Gregory
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Adair, James H.
Process reproducibility is a major concern for scientists and engineers, especially when new processes or new products are transitioned from laboratory-scale to full-scale manufacturing. Robust Parameter Design (RPD) is often used to mitigate this problem. However, in multiple-stage manufacturing process environments, it is difficult to employ the RPD concept because experiments cannot strictly follow the principle of complete randomization. Furthermore, the stages can be located at different sites, leading to multiple sets of noise factors. In the existing literature, only a single set of noise factors is considered. Therefore, in this research, the foundation of using the RPD concept with multistage experiments is developed and discussed. Some optimal design catalogs are provided based on a modified minimum aberration criterion. The context for this work is the development of a medical device made of nanoscale composites using a multiple-stage manufacturing process. © 2012 "IIE".
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Image analysis and high dimensional control chart for inspection of sausage color homogeneity and uniformity
(2016-09-01)
Kaewsuwan, Piraya
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Yuangyai, Chumpol
;
Cheng, Chen Yang
;
Janjarassuk, Udom
Sausage color usually influences consumers' selection due to the perceptions of quality. Extensive studies have applied image processing to capture the characteristics of food products according to the high-dimensional nature of the resultant images. However, the color homogeneity (i. e. "within pack" variation) and uniformity (i. e. "between-pack" variation) have rarely been studied. Therefore, this paper proposes a new framework to detect both variations using images. In addition, a new approach has been developed to deal with high-dimension data involving colorimetric characteristics, namely L∗, a∗, b∗, hue (h) and chroma (C∗). These high-dimensional data are transformed to represent color homogeneity and uniformity. Hotelling T2 chart is used to detect color abnormalities. Our approach indicates that the out-of-control items can be identified with the control chart signals. Nonetheless, the out-of-control signals alone are inadequate for determination of the possible causes. Then, the proposed analysis framework was subsequently applied to identify possible causes that contributed to the process deviations. Furthermore, prior to the experiments with sausages, the image inspection device was tested for gauge repeatability and reproducibility.

Yuangyai, Chumpol

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