Prof. Somkiat Tangjitsitcharoen, Ph.D.
- 8th Floor of Engineering 4 Bldg., Room 802
- +66-2218-6853
- somkiat.ta@eng.chula.ac.th
Overview
Professor Dr. Somkiat Tangjitsitcharoen is currently Head of Advanced Manufacturing and Precision Engineering Research Center at the Industrial Engineering, Chulalongkorn University, Thailand. His research interests include in-process monitoring and optimization of manufacturing processes, micro-machining and micro-assembly, high precision cutting, and intelligent manufacturing system and machine tool.
Education
D.Eng. Mechanical Engineering
Kobe University, Japan, 2004
M.Eng. Industrial Engineering
Chulalongkorn University, Thailand, 1998
B.Eng. Production Engineering
King Mongkut’s Universtiy of Technology Thonburi, Thailand, 1995
Expertise
Manufacturing & Service Systems
Publications
2018
Pattamon Jearaphun, Somkiat Tangjitsitcharoen
Reduction of breakdown for gas turbine in combined cycle power plant Journal Article
In: International Journal of Mechanical Engineering and Robotics Research, vol. 7, no. 6, pp. 630 – 634, 2018, (Cited by: 2).
@article{Jearaphun2018630,
title = {Reduction of breakdown for gas turbine in combined cycle power plant},
author = {Pattamon Jearaphun and Somkiat Tangjitsitcharoen},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056585136&doi=10.18178%2fijmerr.7.6.630-634&partnerID=40&md5=a723bf2fe0241cd64e4c9d521428c8a9},
doi = {10.18178/ijmerr.7.6.630-634},
year = {2018},
date = {2018-01-01},
journal = {International Journal of Mechanical Engineering and Robotics Research},
volume = {7},
number = {6},
pages = {630 – 634},
publisher = {International Journal of Mechanical Engineering and Robotics Research},
abstract = {The objective of this research is to reduce the breakdown for the gas turbine in a combined cycle power plant through the collected gas turbine breakdown. The use of Pareto diagram is apply to select the issues. The electricity production in the current condition is then studied by focusing on the operation, equipment, and other machinery that affect breakdowns. The breakdown causes are then analyzed using be cause and effect diagram. The failure mode and effect analysis (FMEA) is then performed to determine the cause of the breakdown. The criteria are set and evaluated to calculate the risk priority number (RPN) to prioritize the selection of the breakdown causes that need to be improved. It is found that the current availability increased by 1.47% and the amount of breakdowns cost in power generation decreased by 79%. © 2018 Int. J. Mech. Eng. Rob. Res.},
note = {Cited by: 2},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The objective of this research is to reduce the breakdown for the gas turbine in a combined cycle power plant through the collected gas turbine breakdown. The use of Pareto diagram is apply to select the issues. The electricity production in the current condition is then studied by focusing on the operation, equipment, and other machinery that affect breakdowns. The breakdown causes are then analyzed using be cause and effect diagram. The failure mode and effect analysis (FMEA) is then performed to determine the cause of the breakdown. The criteria are set and evaluated to calculate the risk priority number (RPN) to prioritize the selection of the breakdown causes that need to be improved. It is found that the current availability increased by 1.47% and the amount of breakdowns cost in power generation decreased by 79%. © 2018 Int. J. Mech. Eng. Rob. Res.
Somkiat Tangjitsitcharoen, Haruetai Lohasiriwat
Intelligent monitoring and prediction of tool wear in CNC turning by utilizing wavelet transform Journal Article
In: International Journal of Advanced Manufacturing Technology, vol. 99, no. 9-12, pp. 2219 – 2230, 2018, (Cited by: 17).
@article{Tangjitsitcharoen20182219,
title = {Intelligent monitoring and prediction of tool wear in CNC turning by utilizing wavelet transform},
author = {Somkiat Tangjitsitcharoen and Haruetai Lohasiriwat},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85037734965&doi=10.1007%2fs00170-017-1424-5&partnerID=40&md5=ce0e22f8a2a269e39154caacfcf732a7},
doi = {10.1007/s00170-017-1424-5},
year = {2018},
date = {2018-01-01},
journal = {International Journal of Advanced Manufacturing Technology},
volume = {99},
number = {9-12},
pages = {2219 – 2230},
publisher = {Springer London},
abstract = {In order to realize an intelligent CNC machine, this research proposed the in-process tool wear monitoring system regardless of the chip formation in CNC turning by utilizing the wavelet transform. The in-process prediction model of tool wear is developed during the CNC turning process. The relations of the cutting speed, the feed rate, the depth of cut, the decomposed cutting forces, and the tool wear are investigated. The Daubechies wavelet transform is used to differentiate the tool wear signals from the noise and broken chip signals. The decomposed cutting force ratio is utilized to eliminate the effects of cutting conditions by taking ratio of the average variances of the decomposed feed force to that of decomposed main force on the fifth level of wavelet transform. The tool wear prediction model consists of the decomposed cutting force ratio, the cutting speed, the depth of cut, and the feed rate, which is developed based on the exponential function. The new cutting tests are performed to ensure the reliability of the tool wear prediction model. The experimental results showed that as the cutting speed, the feed rate, and the depth of cut increase, the main cutting force also increases which affects in the escalating amount of tool wear. It has been proved that the proposed system can be used to separate the chip formation signals and predict the tool wear by utilizing wavelet transform even though the cutting conditions are changed. © 2017, Springer-Verlag London Ltd., part of Springer Nature.},
note = {Cited by: 17},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In order to realize an intelligent CNC machine, this research proposed the in-process tool wear monitoring system regardless of the chip formation in CNC turning by utilizing the wavelet transform. The in-process prediction model of tool wear is developed during the CNC turning process. The relations of the cutting speed, the feed rate, the depth of cut, the decomposed cutting forces, and the tool wear are investigated. The Daubechies wavelet transform is used to differentiate the tool wear signals from the noise and broken chip signals. The decomposed cutting force ratio is utilized to eliminate the effects of cutting conditions by taking ratio of the average variances of the decomposed feed force to that of decomposed main force on the fifth level of wavelet transform. The tool wear prediction model consists of the decomposed cutting force ratio, the cutting speed, the depth of cut, and the feed rate, which is developed based on the exponential function. The new cutting tests are performed to ensure the reliability of the tool wear prediction model. The experimental results showed that as the cutting speed, the feed rate, and the depth of cut increase, the main cutting force also increases which affects in the escalating amount of tool wear. It has been proved that the proposed system can be used to separate the chip formation signals and predict the tool wear by utilizing wavelet transform even though the cutting conditions are changed. © 2017, Springer-Verlag London Ltd., part of Springer Nature.
Somkiat Tangjitsitcharoen, Haruetai Lohasiriwat
vol. 25, Elsevier B.V., 2018, (Cited by: 10; All Open Access, Gold Open Access).
@conference{Tangjitsitcharoen2018279,
title = {Hybrid Monitoring of Chip Formation and Straightness in CNC Turning by Utilizing Daubechies Wavelet Transform},
author = {Somkiat Tangjitsitcharoen and Haruetai Lohasiriwat},
editor = {Ji W. and Wang L. and Wang X.V. and Onori M.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065677264&doi=10.1016%2fj.promfg.2018.06.084&partnerID=40&md5=8b22ef489078e9059f14442cfdef4e5a},
doi = {10.1016/j.promfg.2018.06.084},
year = {2018},
date = {2018-01-01},
journal = {Procedia Manufacturing},
volume = {25},
pages = {279 – 286},
publisher = {Elsevier B.V.},
abstract = {The relations of straightness, chip formation, and cutting forces are investigated during the CNC turning process. Utilizing the Daubechies wavelet transform, the dynamic cutting forces are decomposed to classify the straightness and broken chip signals according to the frequency ranges. The straightness frequency occurs at the lower frequency on the higher level of wavelet transform. The chip breaking frequency appears at the higher frequency on the lower level of wavelet transform according to the chip length. The results supported the use of the decomposed feed forces to estimate the straightness error during the cutting process. © 2018 Elsevier B.V. All rights reserved.},
note = {Cited by: 10; All Open Access, Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
The relations of straightness, chip formation, and cutting forces are investigated during the CNC turning process. Utilizing the Daubechies wavelet transform, the dynamic cutting forces are decomposed to classify the straightness and broken chip signals according to the frequency ranges. The straightness frequency occurs at the lower frequency on the higher level of wavelet transform. The chip breaking frequency appears at the higher frequency on the lower level of wavelet transform according to the chip length. The results supported the use of the decomposed feed forces to estimate the straightness error during the cutting process. © 2018 Elsevier B.V. All rights reserved.
2017
Somkiat Tangjitsitcharoen, Kanyakarn Samanmit
Monitoring of chip breaking and surface roughness in computer numerical control turning by utilizing wavelet transform of dynamic cutting forces Journal Article
In: Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, vol. 231, no. 14, pp. 2479 – 2494, 2017, (Cited by: 11).
@article{Tangjitsitcharoen20172479,
title = {Monitoring of chip breaking and surface roughness in computer numerical control turning by utilizing wavelet transform of dynamic cutting forces},
author = {Somkiat Tangjitsitcharoen and Kanyakarn Samanmit},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85034734832&doi=10.1177%2f0954405415601804&partnerID=40&md5=6f5dd4fb23a24252ebded89b922e504d},
doi = {10.1177/0954405415601804},
year = {2017},
date = {2017-01-01},
journal = {Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture},
volume = {231},
number = {14},
pages = {2479 – 2494},
publisher = {SAGE Publications Ltd},
abstract = {The aim of this research is to monitor and classify the broken chip signals from the dynamic cutting forces, in order to predict the surface roughness during the computer numerical control turning process utilizing the Meyer wavelet transform to decompose the dynamic cutting forces. The dynamic cutting forces of the broken chips and the surface roughness can be decomposed into the different levels. The levels of decomposed cutting forces can aid to explain the broken chip formation and the surface roughness profile in both time and frequency domains. The experimentally obtained results showed that the surface roughness frequency occurs at the higher level of decomposed cutting forces, especially at the fifth level, although the cutting conditions are changed. However, the chip breaking frequency appears at the lower level, which depends on the cutting conditions and the chip length. The ratio of the fifth level of decomposed feed forces to that of main forces is proposed to predict the surface roughness during the in-process cutting. It is understood that the broken chip formation can be separated clearly and the surface roughness can be predicted well during the cutting, regardless of the cutting conditions. © 2016, © IMechE 2016.},
note = {Cited by: 11},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The aim of this research is to monitor and classify the broken chip signals from the dynamic cutting forces, in order to predict the surface roughness during the computer numerical control turning process utilizing the Meyer wavelet transform to decompose the dynamic cutting forces. The dynamic cutting forces of the broken chips and the surface roughness can be decomposed into the different levels. The levels of decomposed cutting forces can aid to explain the broken chip formation and the surface roughness profile in both time and frequency domains. The experimentally obtained results showed that the surface roughness frequency occurs at the higher level of decomposed cutting forces, especially at the fifth level, although the cutting conditions are changed. However, the chip breaking frequency appears at the lower level, which depends on the cutting conditions and the chip length. The ratio of the fifth level of decomposed feed forces to that of main forces is proposed to predict the surface roughness during the in-process cutting. It is understood that the broken chip formation can be separated clearly and the surface roughness can be predicted well during the cutting, regardless of the cutting conditions. © 2016, © IMechE 2016.
Sudlop Ratanakuakangwan, Somkiat Tangjitsitcharoen
Comparison of metallurgical coke and lignite coke for power generation in Thailand Conference
vol. 191, no. 1, Institute of Physics Publishing, 2017, (Cited by: 1; All Open Access, Gold Open Access).
@conference{Ratanakuakangwan2017,
title = {Comparison of metallurgical coke and lignite coke for power generation in Thailand},
author = {Sudlop Ratanakuakangwan and Somkiat Tangjitsitcharoen},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020040301&doi=10.1088%2f1757-899X%2f191%2f1%2f012048&partnerID=40&md5=27cdea00135e2191799fc62a6377fb47},
doi = {10.1088/1757-899X/191/1/012048},
year = {2017},
date = {2017-01-01},
journal = {IOP Conference Series: Materials Science and Engineering},
volume = {191},
number = {1},
publisher = {Institute of Physics Publishing},
abstract = {This paper presents and compares two alternatives of cokes in power generation which are the metallurgical coke with coke oven gas and the coke from lignite under the consideration of the energy and the environment. These alternatives not only consume less fuel due to their higher heat content than conventional coal but also has less SO2 emission. The metallurgical coke and its by-product which is coke oven gas can be obtained from the carbonization process of coking coal. According to high grade coking coal, the result in the energy attitude is not profitable but its sulfur content that directly affects the emission of SO2 is considered to be very low. On the other hand, the coke produced from lignite is known as it is the lowest grade from coal and it causes the high pollution. Regarding to energy profitability, the lignite coke is considered to be much more beneficial than the metallurgical coke in contrast to the environmental concerns. However, the metallurgical coke has the highest heating value. Therefore, a decision making between those choices must be referred to the surrounding circumstances based on energy and environment as well as economic consideration in the further research. © Published under licence by IOP Publishing Ltd.},
note = {Cited by: 1; All Open Access, Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
This paper presents and compares two alternatives of cokes in power generation which are the metallurgical coke with coke oven gas and the coke from lignite under the consideration of the energy and the environment. These alternatives not only consume less fuel due to their higher heat content than conventional coal but also has less SO2 emission. The metallurgical coke and its by-product which is coke oven gas can be obtained from the carbonization process of coking coal. According to high grade coking coal, the result in the energy attitude is not profitable but its sulfur content that directly affects the emission of SO2 is considered to be very low. On the other hand, the coke produced from lignite is known as it is the lowest grade from coal and it causes the high pollution. Regarding to energy profitability, the lignite coke is considered to be much more beneficial than the metallurgical coke in contrast to the environmental concerns. However, the metallurgical coke has the highest heating value. Therefore, a decision making between those choices must be referred to the surrounding circumstances based on energy and environment as well as economic consideration in the further research. © Published under licence by IOP Publishing Ltd.
Sasitorn Peantong, Somkiat Tangjitsitcharoen
A STUDY of USING HYDROGEN GAS for STEAM BOILER in CHOLOR- ALKALI MANUFACTURING Conference
vol. 215, no. 1, Institute of Physics Publishing, 2017, (Cited by: 6; All Open Access, Gold Open Access).
@conference{Peantong2017,
title = {A STUDY of USING HYDROGEN GAS for STEAM BOILER in CHOLOR- ALKALI MANUFACTURING},
author = {Sasitorn Peantong and Somkiat Tangjitsitcharoen},
editor = {Ding J. and Gaol F.L. and Webb J.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028329140&doi=10.1088%2f1757-899X%2f215%2f1%2f012018&partnerID=40&md5=19e241e7183b80b7fdd689c5f7f20a33},
doi = {10.1088/1757-899X/215/1/012018},
year = {2017},
date = {2017-01-01},
journal = {IOP Conference Series: Materials Science and Engineering},
volume = {215},
number = {1},
publisher = {Institute of Physics Publishing},
abstract = {Main products of manufacturing of Cholor - Alkali, which commonly known as industrial chemical, are chlorine gas (Cl2), Sodium Hydroxide (NaOH) and hydrogen gas (H2). Chorine gas and sodium hydroxide are two main products for commercial profit; where hydrogen gas is by product. Most industries release hydrogen gas to atmosphere as it is non-profitable and less commercial scale. This study aims to make the most use of hydrogen as a substitute energy of natural gas for steam boiler to save energy cost. The second target of this study is to reduce level of CO2 release to air as a consequence of boiler combustion. This study suggests to install boiler that bases on hydrogen as main power with a high turndown ratio of at least 1:6. However, this case study uses boiler with two mode such as natural gas (NG) mode and mixed mode as they need to be flexible for production. Never the less, the best boiler selection is to use single mode energy of hydrogen. The most concerned issue about hydrogen gas is explosion during combustion stage. Stabilization measures at emergency stop is introduced to control H2 pressure to protect the explosion. This study varies ratio of natural gas to hydrogen gas to find the optimal level of two energy sources for boiler and measure total consumption through costing model; where CO2 level is measured at the boiler stack. The result of this study shows that hydrogen gas can be a substitute energy with natural gas and can reduce cost. Natural gas cost saving is 248,846 baht per month and reduce level of NOx is 80 ppm 7% O2 and 2 % of CO2 release to air as a consequence of boiler combustion. © Published under licence by IOP Publishing Ltd.},
note = {Cited by: 6; All Open Access, Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Main products of manufacturing of Cholor – Alkali, which commonly known as industrial chemical, are chlorine gas (Cl2), Sodium Hydroxide (NaOH) and hydrogen gas (H2). Chorine gas and sodium hydroxide are two main products for commercial profit; where hydrogen gas is by product. Most industries release hydrogen gas to atmosphere as it is non-profitable and less commercial scale. This study aims to make the most use of hydrogen as a substitute energy of natural gas for steam boiler to save energy cost. The second target of this study is to reduce level of CO2 release to air as a consequence of boiler combustion. This study suggests to install boiler that bases on hydrogen as main power with a high turndown ratio of at least 1:6. However, this case study uses boiler with two mode such as natural gas (NG) mode and mixed mode as they need to be flexible for production. Never the less, the best boiler selection is to use single mode energy of hydrogen. The most concerned issue about hydrogen gas is explosion during combustion stage. Stabilization measures at emergency stop is introduced to control H2 pressure to protect the explosion. This study varies ratio of natural gas to hydrogen gas to find the optimal level of two energy sources for boiler and measure total consumption through costing model; where CO2 level is measured at the boiler stack. The result of this study shows that hydrogen gas can be a substitute energy with natural gas and can reduce cost. Natural gas cost saving is 248,846 baht per month and reduce level of NOx is 80 ppm 7% O2 and 2 % of CO2 release to air as a consequence of boiler combustion. © Published under licence by IOP Publishing Ltd.
Phitchaya Phanomwan Na Ayudhya, Somkiat Tangjitsitcharoen
REDUCTION of DEFECTS in JEWELRY MANUFACTURING Conference
vol. 215, no. 1, Institute of Physics Publishing, 2017, (Cited by: 1; All Open Access, Gold Open Access).
@conference{Ayudhya2017,
title = {REDUCTION of DEFECTS in JEWELRY MANUFACTURING},
author = {Phitchaya Phanomwan Na Ayudhya and Somkiat Tangjitsitcharoen},
editor = {Ding J. and Gaol F.L. and Webb J.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028361260&doi=10.1088%2f1757-899X%2f215%2f1%2f012016&partnerID=40&md5=9857878a01904c0537dcd5d90ff38e27},
doi = {10.1088/1757-899X/215/1/012016},
year = {2017},
date = {2017-01-01},
journal = {IOP Conference Series: Materials Science and Engineering},
volume = {215},
number = {1},
publisher = {Institute of Physics Publishing},
abstract = {The aim of this research was to reduce the defects of gem bracelet found during manufacturing process at a jewelry company. It was found that gem bracelet product has the highest rejects compared to the rejects found in ring, earring, and pendant products. Types of defect were classified by using Pareto Diagram consisting of gem falling, seam, unclean casting, impinge, and deformation. The causes of defect were analyzed by Cause and Effect Diagram and applied Failure Mode and Effects Analysis (FMEA) was applied during manufacturing processes. This research found that the improvement of manufacturing process could reduce the Risk Priority Number (RPN) and total of all defects by 48.70% and 48.89%, respectively. © Published under licence by IOP Publishing Ltd.},
note = {Cited by: 1; All Open Access, Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
The aim of this research was to reduce the defects of gem bracelet found during manufacturing process at a jewelry company. It was found that gem bracelet product has the highest rejects compared to the rejects found in ring, earring, and pendant products. Types of defect were classified by using Pareto Diagram consisting of gem falling, seam, unclean casting, impinge, and deformation. The causes of defect were analyzed by Cause and Effect Diagram and applied Failure Mode and Effects Analysis (FMEA) was applied during manufacturing processes. This research found that the improvement of manufacturing process could reduce the Risk Priority Number (RPN) and total of all defects by 48.70% and 48.89%, respectively. © Published under licence by IOP Publishing Ltd.
Somkiat Tangjitsitcharoen, Prae Thesniyom, Suthas Ratanakuakangwan
A wavelet approach to predict surface roughness in ball-end milling Journal Article
In: Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, vol. 231, no. 14, pp. 2468 – 2478, 2017, (Cited by: 13).
@article{Tangjitsitcharoen20172468,
title = {A wavelet approach to predict surface roughness in ball-end milling},
author = {Somkiat Tangjitsitcharoen and Prae Thesniyom and Suthas Ratanakuakangwan},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85034767138&doi=10.1177%2f0954405415605951&partnerID=40&md5=a03cbda8ee3a8ac9a2d6025c8bea11f9},
doi = {10.1177/0954405415605951},
year = {2017},
date = {2017-01-01},
journal = {Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture},
volume = {231},
number = {14},
pages = {2468 – 2478},
publisher = {SAGE Publications Ltd},
abstract = {This research proposed an advance in the prediction of the in-process surface roughness during the ball-end milling process by utilizing the wavelet transform to monitor and decompose the dynamic cutting forces. The chatter detection system has been adopted from the previous research of the author to avoid the chatter first, and hence, the dynamic cutting force ratio is introduced to predict the in-process surface roughness during the normal cutting by taking the ratio of the decomposed dynamic cutting force in X axis to that in Z axis. The Daubechies wavelet transform is employed in this research to analyze the in-process surface roughness. The experimentally obtained results showed that the surface roughness frequency occurred at the same level of the decomposed dynamic cutting forces although the cutting conditions are changed. It is understood that the in-process surface roughness can be predicted effectively under various cutting conditions referring to the proposed monitoring system. © 2015, © IMechE 2015.},
note = {Cited by: 13},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This research proposed an advance in the prediction of the in-process surface roughness during the ball-end milling process by utilizing the wavelet transform to monitor and decompose the dynamic cutting forces. The chatter detection system has been adopted from the previous research of the author to avoid the chatter first, and hence, the dynamic cutting force ratio is introduced to predict the in-process surface roughness during the normal cutting by taking the ratio of the decomposed dynamic cutting force in X axis to that in Z axis. The Daubechies wavelet transform is employed in this research to analyze the in-process surface roughness. The experimentally obtained results showed that the surface roughness frequency occurred at the same level of the decomposed dynamic cutting forces although the cutting conditions are changed. It is understood that the in-process surface roughness can be predicted effectively under various cutting conditions referring to the proposed monitoring system. © 2015, © IMechE 2015.
Somkiat Tangjitsitcharoen, Mumin Sassantiwong
vol. 241, no. 1, Institute of Physics Publishing, 2017, (Cited by: 2; All Open Access, Gold Open Access).
@conference{Tangjitsitcharoen2017,
title = {Concurrent Monitoring of Chip Formation and Prediction of Roundness in CNC Turning Using Wavelet Transform},
author = {Somkiat Tangjitsitcharoen and Mumin Sassantiwong},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85035079384&doi=10.1088%2f1757-899X%2f241%2f1%2f012028&partnerID=40&md5=69263519ca324ce8124dd2c894ef7cab},
doi = {10.1088/1757-899X/241/1/012028},
year = {2017},
date = {2017-01-01},
journal = {IOP Conference Series: Materials Science and Engineering},
volume = {241},
number = {1},
publisher = {Institute of Physics Publishing},
abstract = {The aim of this research is to investigate the chip formation, the roundness and the dynamic cutting forces in CNC turning process. The dynamic cutting forces are decomposed to classify the signals of the broken chip and the roundness. The Daubechies wavelet transform is utilized to identify those signals into different levels due to the different frequencies of itself. The experimentally obtained results showed that the decomposed cutting forces can be used to estimate the roundness under various cutting conditions. © Published under licence by IOP Publishing Ltd.},
note = {Cited by: 2; All Open Access, Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
The aim of this research is to investigate the chip formation, the roundness and the dynamic cutting forces in CNC turning process. The dynamic cutting forces are decomposed to classify the signals of the broken chip and the roundness. The Daubechies wavelet transform is utilized to identify those signals into different levels due to the different frequencies of itself. The experimentally obtained results showed that the decomposed cutting forces can be used to estimate the roundness under various cutting conditions. © Published under licence by IOP Publishing Ltd.
Oranuch Nooted, Somkiat Tangjitsitcharoen
DEFECTIVE REDUCTION in FROZEN PIE MANUFACTURING PROCESS Conference
vol. 215, no. 1, Institute of Physics Publishing, 2017, (Cited by: 3; All Open Access, Gold Open Access).
@conference{Nooted2017,
title = {DEFECTIVE REDUCTION in FROZEN PIE MANUFACTURING PROCESS},
author = {Oranuch Nooted and Somkiat Tangjitsitcharoen},
editor = {Ding J. and Gaol F.L. and Webb J.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028348459&doi=10.1088%2f1757-899X%2f215%2f1%2f012015&partnerID=40&md5=ac3dff48787b0996ecfd6fce20c79605},
doi = {10.1088/1757-899X/215/1/012015},
year = {2017},
date = {2017-01-01},
journal = {IOP Conference Series: Materials Science and Engineering},
volume = {215},
number = {1},
publisher = {Institute of Physics Publishing},
abstract = {The frozen pie production has a lot of defects resulting in high production cost. Failure mode and effect analysis (FMEA) technique has been applied to improve the frozen pie process. Pareto chart is also used to determine the major defects of frozen pie. There are 3 main processes that cause the defects which are the 1st freezing to glazing process, the forming process, and the folding process. The Risk Priority Number (RPN) obtained from FMEA is analyzed to reduce the defects. If RPN of each cause exceeds 45, the process will be considered to be improved and selected for the corrective and preventive actions. The results showed that RPN values decreased after the correction. Therefore, the implementation of FMEA technique can help to improve the performance of frozen pie process and reduce the defects approximately 51.9%. © Published under licence by IOP Publishing Ltd.},
note = {Cited by: 3; All Open Access, Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
The frozen pie production has a lot of defects resulting in high production cost. Failure mode and effect analysis (FMEA) technique has been applied to improve the frozen pie process. Pareto chart is also used to determine the major defects of frozen pie. There are 3 main processes that cause the defects which are the 1st freezing to glazing process, the forming process, and the folding process. The Risk Priority Number (RPN) obtained from FMEA is analyzed to reduce the defects. If RPN of each cause exceeds 45, the process will be considered to be improved and selected for the corrective and preventive actions. The results showed that RPN values decreased after the correction. Therefore, the implementation of FMEA technique can help to improve the performance of frozen pie process and reduce the defects approximately 51.9%. © Published under licence by IOP Publishing Ltd.