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Relevant bibliographies by topics / Process control / Journal articles

Journal articles on the topic 'Process control'

To see the other types of publications on this topic, follow the link: Process control.

Author: Grafiati

Published: 4 June 2021

Last updated: 29 July 2024

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1

Abd EL-hamid, Ahmed S., Ahmed E. hussian, and Aly M. Radwan. "Generic Model Control of Biomethanation Process." International Journal of Engineering Research 4, no. 6 (June 1, 2015): 282–85. http://dx.doi.org/10.17950/ijer/v4s6/602.

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2

Kabdullinov, A. M., B. R. Nussupbekov, A. K. Khassennov, M. Stoev, and M. B. Karagaeva. "Automated control system for casting process." Bulletin of the Karaganda University. "Physics" Series 87, no. 3 (September 29, 2017): 65–70. http://dx.doi.org/10.31489/2017phys3/65-70.

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3

Jogi, Bhushan S., Lekrajsing R. Gour, and Nikhil Turkar. "Process Improvement Using Statistical Process Control in a Small Scale Industry." International Journal of Trend in Scientific Research and Development Volume-2, Issue-5 (August 31, 2018): 1885–92. http://dx.doi.org/10.31142/ijtsrd17144.

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4

Rivera, Diego Y. "Designing Soft Controls for Process Control." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 44, no. 1 (July 2000): 120–23. http://dx.doi.org/10.1177/154193120004400132.

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5

Honma, Chuichi. "Process control." JAPAN TAPPI JOURNAL 41, no. 10 (1987): 958–69. http://dx.doi.org/10.2524/jtappij.41.958.

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6

Lorraine, Hilary, and N. Domenico Bruzzone. "Process control." Technological Forecasting and Social Change 41, no. 1 (February 1992): 57–69. http://dx.doi.org/10.1016/0040-1625(92)90016-m.

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7

Montgomery, Douglas C., J. Bert Keats, George C. Runger, and William S. Messina. "Integrating Statistical Process Control and Engineering Process Control." Journal of Quality Technology 26, no. 2 (April 1994): 79–87. http://dx.doi.org/10.1080/00224065.1994.11979508.

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8

Hussain, Mohamed Abdullah, Mumtaz Mohamed Ali El-Mukhtar, and Wrya Mohamed Ali. "Secure Client- Server Based Remote Process Control." Journal of Zankoy Sulaimani - Part A 11, no. 1 (August 12, 2007): 67–80. http://dx.doi.org/10.17656/jzs.10182.

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9

Machado, I. C., A. C. de Araujo, and A. E. C. Peres. "Optimizing advanced process control systems: Process and control audits." Mining, Metallurgy & Exploration 20, no. 3 (August 2003): 135–39. http://dx.doi.org/10.1007/bf03403145.

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10

Aliyev, A. M., A. R. Safarov, I. V. Balayev, I. I. Osmanova, and A. M. Guseynova. "CONTROL OF PROPANE PYROLYSIS PROCESS IN NONSTATIONARY CONDITIONS." Azerbaijan Chemical Journal, no. 1 (March 12, 2020): 6–10. http://dx.doi.org/10.32737/0005-2531-2020-1-6-10.

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11

Ziegel, Eric R., and C. Mamzic. "Statistical Process Control." Technometrics 38, no. 4 (November 1996): 410. http://dx.doi.org/10.2307/1271327.

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12

Vukovinsky, Kim, and Leonard A. Doty. "Statistical Process Control." Technometrics 40, no. 1 (February 1998): 73. http://dx.doi.org/10.2307/1271395.

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13

., Ved Parkash. "STATISTICAL PROCESS CONTROL." International Journal of Research in Engineering and Technology 02, no. 08 (August 25, 2013): 70–72. http://dx.doi.org/10.15623/ijret.2013.0208010.

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14

Avakh Darestani, Soroush, and Mina Nasiri. "Statistical process control." International Journal of Quality & Reliability Management 33, no. 1 (December 31, 2015): 2–24. http://dx.doi.org/10.1108/ijqrm-08-2013-0130.

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Purpose – In this context, process capability indices (PCI) reveal the process zones base on specification limits (SLs). Most of the research on control charts assumed certain data. However, to measure quality characteristic, practitioners sometimes face with uncertain and linguistic variables. Fuzzy theory is one of the most applicable tools which academia has employed to deal with uncertainty. The paper aims to discuss these issues. Design/methodology/approach – In this investigation, first, fuzzy and S control chart has been developed and second, the fuzzy formulation of the PCIs such as C pm ,C pmu ,C pml , C pmk , P p , P pl , P pu , P pk are constructed when SLs and measurements are at both triangular fuzzy numbers (TFNs) and trapezoidal fuzzy numbers (TrFNs) stages. Findings – The results show that using fuzzy make more flexibility and sense on recognition of out-of-control warnings. Research limitations/implications – For further research, the PCIs for non-normal data can be conducted based on TFN and TrFN. Practical implications – The application case is related to a piston company in Konya’s industry area. Originality/value – In the previous researches, for calculating C p , C pk , C pm and C pmk indices, the base approach was calculate standard deviation for a short term variation. For calculating these indices, the variation between subgroups are being ignored. Therefore, P p and P pk indices solved this fault by mentioning long term and short term variations. Therefore these two indices calculate the actual process capability.

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15

Luis Duarte Ribeiro, José, Carla Schwengber ten Caten, and Celso Fritsch. "Integrated process control." International Journal of Quality & Reliability Management 18, no. 4 (June 2001): 444–64. http://dx.doi.org/10.1108/02656710110387049.

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16

Kawabata, S., K. Ito, and Masako Niwa. "Tailoring Process Control." Journal of the Textile Institute 83, no. 3 (January 1992): 361–74. http://dx.doi.org/10.1080/00405009208631209.

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17

Arnold, B. F., and E. von Col Iani. "Economic Process Control." Statistica Neerlandica 41, no. 2 (June 1987): 89–97. http://dx.doi.org/10.1111/j.1467-9574.1987.tb01175.x.

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18

Vetter, Thomas R., and Douglas Morrice. "Statistical Process Control." Anesthesia & Analgesia 128, no. 2 (February 2019): 374–82. http://dx.doi.org/10.1213/ane.0000000000003977.

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19

Perry, Robert L. "Statistical Process Control." Technometrics 30, no. 4 (November 1988): 454–55. http://dx.doi.org/10.1080/00401706.1988.10488444.

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20

Adams, Benjamin M. "Statistical Process Control." Technometrics 35, no. 1 (February 1993): 90–91. http://dx.doi.org/10.1080/00401706.1993.10485003.

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21

Vljkovinsky, Kim. "Statistical Process Control." Technometrics 40, no. 1 (February 1998): 73–74. http://dx.doi.org/10.1080/00401706.1998.10485484.

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22

Thoma, Manfred. "Process control engineering." Automatica 32, no. 4 (April 1996): 659–60. http://dx.doi.org/10.1016/s0005-1098(96)90013-8.

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23

Koštial, Imrich, Ján Terpák, Lubomír Dorčák, and Pavol Nemčovský. "Sintering Process Control." IFAC Proceedings Volumes 31, no. 23 (September 1998): 147–51. http://dx.doi.org/10.1016/s1474-6670(17)35870-6.

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24

Kaczorek, Tadeusz. "Nonlinear process control." Control Engineering Practice 5, no. 3 (March 1997): 441. http://dx.doi.org/10.1016/s0967-0661(97)87527-2.

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25

Walsh, Stephen. "Process control engineering." Journal of Process Control 6, no. 1 (February 1996): 67. http://dx.doi.org/10.1016/s0959-1524(96)90001-3.

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26

Dowd, John S. "Statistical Process Control." Journal of Quality Technology 20, no. 4 (October 1988): 276–78. http://dx.doi.org/10.1080/00224065.1988.11979123.

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27

Nelson, Peter R. "Process Quality Control." Journal of Quality Technology 23, no. 1 (January 1991): 71–73. http://dx.doi.org/10.1080/00224065.1991.11979288.

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28

Thane, Phil. "Industrial process control." Electronics Education 1996, no. 3 (1996): 26–28. http://dx.doi.org/10.1049/ee.1996.0076.

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29

Morse, Gary. "Statistical Process Control." Transactions of the IMF 71, no. 2 (January 1993): 80–82. http://dx.doi.org/10.1080/00202967.1993.11870994.

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30

Mort, N. "Multivariable Process Control." IFAC Proceedings Volumes 27, no. 9 (August 1994): 161–64. http://dx.doi.org/10.1016/s1474-6670(17)45920-9.

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31

Kashinov, V. V., and V. V. Voznesenskii. "Furnace process control." Refractories 30, no. 9-10 (September 1989): 579–81. http://dx.doi.org/10.1007/bf01280752.

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32

Braatz, Richard D., and Oscar D. Crisalle. "Chemical process control." International Journal of Robust and Nonlinear Control 17, no. 13 (2007): 1161–62. http://dx.doi.org/10.1002/rnc.1173.

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33

Virk, G. S. "Robust process control." Chemical Engineering Science 45, no. 4 (1990): 1149. http://dx.doi.org/10.1016/0009-2509(90)85041-b.

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34

Moshgbar, Mojgan, and Steve Hammond. "Advanced Process Control." Quality Assurance Journal 13, no. 3-4 (July 2010): 62–66. http://dx.doi.org/10.1002/qaj.472.

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35

Bruns, H. "Process Control Engineering." Chemie Ingenieur Technik 67, no. 9 (September 1995): 1213. http://dx.doi.org/10.1002/cite.3306709182.

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36

Saghrouchni, Hamza. "Advanced Process Control and Critical Dimension Control in Photolithography Process." International Journal of New Practices in Management and Engineering 11, no. 1S (January 20, 2022): 18–19. http://dx.doi.org/10.17762/ijnpme.v11i1s.139.

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High volume, practical, assembling of cutting edge' photolithography processes requires top to bottom comprehension of Process and Process-Tool connection to accomplish Advanced Process Control (APC). The process likewise requires a tight control to keep up an ideal entryway CD. The direct loom that is right now being used in most semiconductor offices depends on administrator experience and doesn't give good control on the CD variety. Usage of a programmed input control framework in the business has been troublesome in light of the fact that the CD can't be estimated progressively finished. In this magazine, a neural complex is utilized to anticipate CD dependent on the estimations of thickness, reflectivity, refractive record, and portion. The neural network is prepared utilizing recorded information that are gathered at an assembling office. A neural scheme-based converse model of the progression is created. The opposite model is knock down with the progression model to frame a feed-forward controller.

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37

Vining, Geoff. "Technical Advice: Statistical Process Control and Automatic/Engineering Process Control." Quality Engineering 22, no. 3 (June 7, 2010): 222–24. http://dx.doi.org/10.1080/08982111003800547.

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38

Box, George E. P., David E. Coleman, and Robert V. Baxley. "A Comparison of Statistical Process Control and Engineering Process Control." Journal of Quality Technology 29, no. 2 (April 1997): 128–30. http://dx.doi.org/10.1080/00224065.1997.11979740.

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39

Yang, Ling, and Shey-Huei Sheu. "Integrating multivariate engineering process control and multivariate statistical process control." International Journal of Advanced Manufacturing Technology 29, no. 1-2 (November 16, 2005): 129–36. http://dx.doi.org/10.1007/s00170-004-2494-8.

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40

Seethaler, R. J., and I. Yellowley. "Process control and dynamic process planning." International Journal of Machine Tools and Manufacture 40, no. 2 (January 2000): 239–57. http://dx.doi.org/10.1016/s0890-6955(99)00054-1.

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41

Whalley, R., and M. Ebrahimi. "Process control with minimum control effort." Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering 213, no. 4 (November 1999): 275–89. http://dx.doi.org/10.1243/0954408991529889.

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42

Lin, Bishan. "Crime Control by Statistical Process Control." Kybernetes 20, no. 7 (July 1991): 51–58. http://dx.doi.org/10.1108/eb005912.

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43

Henson, Michael A., Babatunde A. Ogunnaike, and James S. Schwaber. "Habituating control strategies for process control." AIChE Journal 41, no. 3 (March 1995): 604–18. http://dx.doi.org/10.1002/aic.690410318.

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44

Kuchuk-Yatsenko, S. I., P. M. Rudenko, V. S. Gavrish, A. V. Didkovsky, and E. V. Antipin. "Statistical control of process of flash-butt welding of rails. Two-level control system." Paton Welding Journal 2016, no. 6 (June 28, 2016): 13–16. http://dx.doi.org/10.15407/tpwj2016.06.02.

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45

Lant, Paul, and Marc Steffens. "Benchmarking for process control: “should i invest in improved process control?”." Water Science and Technology 37, no. 12 (June 1, 1998): 49–54. http://dx.doi.org/10.2166/wst.1998.0497.

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Benchmarking to achieve world class performance is becoming an increasingly popular technique in all business sectors. In this paper, we benchmark wastewater treatment process control practice against other process industry sectors in Australia, and provide an evaluation of the general level of process control in the wastewater treatment industry. The benchmarking is based on criteria developed by ICI Engineering. We also present a quantitative statistical tool which can be used for performing a benefits analysis.

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46

Koli, D. R., R. Wan Hsiang Liang, H. J. Kim, and R. Solan. "Advanced Process Control for Variability Control in Chemical Mechanical Polishing Process." ECS Transactions 72, no. 18 (October 11, 2016): 11–16. http://dx.doi.org/10.1149/07218.0011ecst.

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47

Jalote, P., and A. Saxena. "Optimum control limits for employing statistical process control in software process." IEEE Transactions on Software Engineering 28, no. 12 (December 2002): 1126–34. http://dx.doi.org/10.1109/tse.2002.1158286.

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48

Duffuaa *, S. O., S. N. Khursheed, and S. M. Noman. "Integrating statistical process control, engineering process control and Taguchi's quality engineering." International Journal of Production Research 42, no. 19 (October 2004): 4109–18. http://dx.doi.org/10.1080/00207540410001704069.

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49

D., Pamela. "Bio-inspired Hybrid Algorithm for Air Temperature Process Control." Journal of Advanced Research in Dynamical and Control Systems 12, SP4 (March 31, 2020): 1762–68. http://dx.doi.org/10.5373/jardcs/v12sp4/20201659.

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50

Sun, Weihong, Jingwen Ma, and Man Liang. "Research on Quality Control of Medical Device Production Process." International Journal of Materials, Mechanics and Manufacturing 7, no. 3 (June 2019): 133–37. http://dx.doi.org/10.18178/ijmmm.2019.7.3.446.

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