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Journal articles on the topic 'Chemical process control'

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Published: 4 June 2021
Last updated: 31 July 2024

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1

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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2

Norton, J. P. "Chemical process control-CPCIII." Chemical Engineering Science 43, no. 3 (1988): 735. http://dx.doi.org/10.1016/0009-2509(88)87034-9.

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3

Torng, Chau Chen, Chikong Huang, and Hsien Ming Chang. "Process control for aerospace chemical milling process." International Journal of Manufacturing Technology and Management 18, no. 3 (2009): 308. http://dx.doi.org/10.1504/ijmtm.2009.026390.

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4

Sekher, Malik, Mohammed M'Saad, Mondher Farza, and O. Gehan. "Chemical process sliding mode control." International Journal of Modelling, Identification and Control 5, no. 4 (2008): 260. http://dx.doi.org/10.1504/ijmic.2008.023510.

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5

Morari, M., and T. J. McAvoy. "Chemical process control-CPC III." Analytica Chimica Acta 199 (1987): 281. http://dx.doi.org/10.1016/s0003-2670(00)82845-7.

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6

Asbjørnsen, Odd A., Takeichiro Takamatsu, George Stephanopoulos, Jim S. Anderson, Jens G. Balchen, and David M. Prett. "7.1 — Chemical Process Control Education." IFAC Proceedings Volumes 20, no. 5 (July 1987): 97–99. http://dx.doi.org/10.1016/s1474-6670(17)55542-1.

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7

Wurst, M. "Chemical process control—CPC III." Chemical Engineering and Processing: Process Intensification 22, no. 3 (November 1987): 181. http://dx.doi.org/10.1016/0255-2701(87)80045-4.

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8

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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9

Kotus, M., E. Jankajová, and M. Petrík. "Quality control of aluminium melt in production process." Research in Agricultural Engineering 61, Special Issue (June 2, 2016): S43—S47. http://dx.doi.org/10.17221/28/2015-rae.

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The quality of aluminium alloy in the production process on the chemical composition basis was evaluated. The quality of casting alloy depends on the chemical composition of melt and on the technological process of production process. The basic elements such as Si, Cu, Fe, Mg and Al in melting were evaluated. The obtained data were compared with the guide data referred to in the standard for aluminium alloy.
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10

KUESPERT, D. R., and T. J. MCAVOY. "KNOWLEDGE EXTRACTION IN CHEMICAL PROCESS CONTROL." Chemical Engineering Communications 130, no. 1 (January 1994): 251–64. http://dx.doi.org/10.1080/00986449408936279.

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11

Tippett, Michael J., and Jie Bao. "Distributed control of chemical process networks." International Journal of Automation and Computing 12, no. 4 (July 1, 2015): 368–81. http://dx.doi.org/10.1007/s11633-015-0895-9.

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12

McAvoy, Thomas J. "Contemplative stance for chemical process control." Automatica 28, no. 2 (March 1992): 441–42. http://dx.doi.org/10.1016/0005-1098(92)90134-2.

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13

Both, Roxana, Eva-Henrietta Dulf, and Ana-Maria Cormos. "ADVANCED CONTROL OF A COMPLEX CHEMICAL PROCESS." Brazilian Journal of Chemical Engineering 33, no. 1 (March 2016): 155–68. http://dx.doi.org/10.1590/0104-6632.20160331s00001267.

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14

Sugiarta, Agus, Houtman P. Siregar, and Dedy Loebis. "Automation of Process Control in Chemical Plant." ACMIT Proceedings 2, no. 1 (March 15, 2015): 6–12. http://dx.doi.org/10.33555/acmit.v2i1.3.

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Automation of process control in chemical plant is an inspiring application field of mechatronicengineering. In order to understand the complexity of the automation and its application requireknowledges of chemical engineering, mechatronic and other numerous interconnected studies.The background of this paper is an inherent problem of overheating due to lack of level controlsystem. The objective of this research is to control the dynamic process of desired level more tightlywhich is able to stabilize raw material supply into the chemical plant system.The chemical plant is operated within a wide range of feed compositions and flow rates whichmake the process control become difficult. This research uses modelling for efficiency reason andanalyzes the model by PID control algorithm along with its simulations by using Matlab.
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15

Chu, Jian, Masahiro Ohshima, Iori Hashimoto, Takeichiro Tanamatsu, and JiCheng Wang. "A robustness study for chemical process control." JOURNAL OF CHEMICAL ENGINEERING OF JAPAN 22, no. 1 (1989): 30–34. http://dx.doi.org/10.1252/jcej.22.30.

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16

Chen, Chyi-Tsong. "Direct Adaptive Control of Chemical Process Systems." Industrial & Engineering Chemistry Research 40, no. 19 (September 2001): 4121–40. http://dx.doi.org/10.1021/ie990668q.

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17

Gisin, M., and C. Thommen. "Contemporary wet-chemical flow analyzersfor process control." TrAC Trends in Analytical Chemistry 8, no. 2 (February 1989): 62–66. http://dx.doi.org/10.1016/0165-9936(89)87020-7.

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18

Caulcutt, Roland, and John Coates. "Statistical process control with chemical batch processes." Total Quality Management 2, no. 2 (January 1991): 191–200. http://dx.doi.org/10.1080/09544129100000020.

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19

Cao, Xiaofeng, Shuhui Zou, and Dandan Wang. "Process Control Analysis of Modern Chemical Instruments and Chemical Automation." IOP Conference Series: Earth and Environmental Science 358 (December 13, 2019): 032056. http://dx.doi.org/10.1088/1755-1315/358/3/032056.

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20

Bay Jørgensen, S., L. Goldschmidt, and L. Hallager. "Sparse Process Modelling for Robust Multivariable Adaptive Chemical Process Control." IFAC Proceedings Volumes 18, no. 5 (July 1985): 391–96. http://dx.doi.org/10.1016/s1474-6670(17)60591-3.

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21

Morris, Julian. "New Horizons for Process Control in Chemical and Process Engineering." Chemical Engineering Research and Design 81, no. 2 (February 2003): 199–200. http://dx.doi.org/10.1205/026387603762878656.

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22

Morud, Tordis E. "Multivariate statistical process control; example from the chemical process industry." Journal of Chemometrics 10, no. 5-6 (September 1996): 669–75. http://dx.doi.org/10.1002/(sici)1099-128x(199609)10:5/6<669::aid-cem467>3.0.co;2-q.

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23

Kashkoush, Ismail, Rich Novak, and Eric Brause. "In-Situ Chemical Concentration Control for Wafer Wet Cleaning." Journal of the IEST 41, no. 3 (May 14, 1998): 24–30. http://dx.doi.org/10.17764/jiet.41.3.f573u112344t8pr5.

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This paper demonstrates the use of conductivity sensors to monitor and control the concentration of RCA cleaning and hydrofluoric acid (HF) etching solutions. Commercially available electrodeless conductivity sensors were used to monitor and control the concentration of these process solutions. A linear relationship between the conductivity of the solution and the chemical concentration was obtained within the range studied. A chemical injection scheme was developed to maintain the chemical concentration within specified limits. Different concentrations of RCA-based cleaning solutions and HF solutions were investigated. Results show that these techniques are suitable for monitoring and controlling the concentration of chemicals in the process tanks for better process control. These techniques provide low cost of ownership of the process by using dilute chemicals and longer bath life (i.e., a more environmentally sound process).
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24

Simkoff, Jodie M., Fernando Lejarza, Morgan T. Kelley, Calvin Tsay, and Michael Baldea. "Process Control and Energy Efficiency." Annual Review of Chemical and Biomolecular Engineering 11, no. 1 (June 7, 2020): 423–45. http://dx.doi.org/10.1146/annurev-chembioeng-092319-083227.

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We review the impact of control systems and strategies on the energy efficiency of chemical processes. We show that, in many ways, good control performance is a necessary but not sufficient condition for energy efficiency. The direct effect of process control on energy efficiency is manyfold: Reducing output variability allows for operating chemical plants closer to their limits, where the energy/economic optima typically lie. Further, good control enables novel, transient operating strategies, such as conversion smoothing and demand response. Indirectly, control systems are key to the implementation and operation of more energy-efficient plant designs, as dictated by the process integration and intensification paradigms. These conclusions are supported with references to numerous examples from the literature.
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25

KANO, Manabu, Hiromu OHNO, Shinji HASEBE, and Iori HASHIMOTO. "Application of Novel Statistical Process Control Methods to a Chemical Process." Transactions of the Society of Instrument and Control Engineers 37, no. 2 (2001): 160–67. http://dx.doi.org/10.9746/sicetr1965.37.160.

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26

Barrows, Elina, Katherine Martin, and Thérèse Smith. "Markup language for chemical process control and simulation." Computers & Chemical Engineering 160 (April 2022): 107702. http://dx.doi.org/10.1016/j.compchemeng.2022.107702.

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27

Ramirez-Beltran, Nazario D. "Transfer function models to control a chemical process." Computers & Industrial Engineering 33, no. 1-2 (October 1997): 417–20. http://dx.doi.org/10.1016/s0360-8352(97)00126-5.

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28

Ramirez-Beltran, Nazario D., and Henry Jackson. "Application of neural networks to chemical process control." Computers & Industrial Engineering 37, no. 1-2 (October 1999): 387–90. http://dx.doi.org/10.1016/s0360-8352(99)00100-x.

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29

Szczurko, Peter, Kai Finke, and Dorothee Hoberg. "Quality Management in Chemical Process Control Expert Systems." IFAC Proceedings Volumes 29, no. 1 (June 1996): 7177–82. http://dx.doi.org/10.1016/s1474-6670(17)58839-4.

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30

Gill, F. S. "Health hazard control in the chemical process industry." Chemical Engineering Science 43, no. 10 (1988): 2911–12. http://dx.doi.org/10.1016/0009-2509(88)80039-3.

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31

Lees, F. P. "Health hazard control in the chemical process industry." Chemical Engineering Journal 39, no. 1 (September 1988): 68. http://dx.doi.org/10.1016/0300-9467(88)80093-5.

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32

McAvoy, Thomas. "Model Predictive Statistical Process Control of Chemical Plants." Industrial & Engineering Chemistry Research 41, no. 25 (December 2002): 6337–44. http://dx.doi.org/10.1021/ie020067q.

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33

Szczurko, Peter, Kai Finke, and Dorothee Hoberg. "Quality Management in Chemical Process Control Expert Systems." IFAC Proceedings Volumes 28, no. 21 (September 1995): 181–86. http://dx.doi.org/10.1016/s1474-6670(17)46722-x.

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34

Pilz, V. "Health hazard control in the chemical process industry." Chemical Engineering and Processing: Process Intensification 25, no. 1 (February 1989): 57. http://dx.doi.org/10.1016/0255-2701(89)85012-3.

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35

Boisde, G. "Chemical measurements with optical fibers for process control." Talanta 35, no. 2 (February 1988): 75–82. http://dx.doi.org/10.1016/0039-9140(88)80042-0.

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36

Et.al, T. Anitha. "Design of Advanced Process Control Strategy for Industrial Pressure Process." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 6 (April 10, 2021): 38–49. http://dx.doi.org/10.17762/turcomat.v12i6.1259.

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In the process industry, pressure process control is important. Pressure process control systems have been refined and used in numerous implementations of in several process industries, pressure process plants are used, including chemical process industries, pharmaceuticals, wastewater treatment, and power plants. Pressure process management is essential in the process industry. Pressure process control systems have been refined and applied to a wide range of pressure process plant applications in a number of industries, including chemical manufacturing, pharmaceuticals, wastewater treatment, and power plants. The execution of such mechanism may result in remote and then the parameters can change over time.
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37

Wheelis, M. "Biotechnology and chemical weapons control." Pure and Applied Chemistry 74, no. 12 (January 1, 2002): 2247–51. http://dx.doi.org/10.1351/pac200274122247.

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Biotechnology is revolutionizing the way new drugs are discovered, from a substantially empirical art to a rational, predictive process in which targets of drugs are selected on the basis of known physiology, then ligands that can bind to these targets are designed. The same process could be used to identify promising new chemical weapons (CW) agents, which would be synthesized from unscheduled precursors. Biotechnology thus has the potential of fueling CW proliferation. It can also aid the development of novel nonlethal chemical agents, the development of which could have a number of negative consequences for CW control.
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38

Cooper, D. J., and A. M. Lalonde. "Process behavior diagnostics and adaptive process control." Computers & Chemical Engineering 14, no. 4-5 (May 1990): 541–49. http://dx.doi.org/10.1016/0098-1354(90)87025-k.

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39

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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40

Y., Dharshan, Vivek S., Saranya S., Aarthi V.R., and Madhumathi T. "Gesture Control of Robotic Arm." IRA-International Journal of Technology & Engineering (ISSN 2455-4480) 7, no. 1 (May 10, 2017): 1. http://dx.doi.org/10.21013/jte.v7.n1.p1.

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<div><p><em>Robots have become a key technology in various fields. Robotic arms are mostly remote controlled by buttons or panels and sometimes in batch process they are autonomous. The usage of panel boards or control sticks includes a lot of hardwiring and subject to malfunction. It also induces some stress on the operators. Hence major chemical industries like cosmetic manufacturing, paint manufacturing and Biosynthesis laboratory etc., which deals with hazardous environment due to the chemicals and other bio substances, involve humans for the processing. The aim is to reduce the bulk of wiring in the robotic arms and reduce the effort and number of operators in controlling the robotic arm operations. To implement gestures into the process this would be a major breakthrough. This can also be used as pick &amp; place robot, a cleaning robot in chemical industries where a human does not need to directly involved in the process of cleaning the chemicals and also for coating underground tanks.</em></p></div>
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41

Yamabe, Mitsuharu, Satoru Adachi, Hideki Kayama, Yasutoshi Noda, and Yoshitaka Furukawa. "Process Control in Metalorganic Chemical Vapor Deposition of CdTe." Materials Transactions, JIM 35, no. 2 (1994): 130–35. http://dx.doi.org/10.2320/matertrans1989.35.130.

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42

Li, Shuyun, Gaurav Mirlekar, Gerardo Ruiz-Mercado, and Fernando Lima. "Development of Chemical Process Design and Control for Sustainability." Processes 4, no. 3 (July 25, 2016): 23. http://dx.doi.org/10.3390/pr4030023.

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43

Yoo, Sung-Jin, Chang-Jun Lee, and Jong-Min Lee. "Major Control Techniques for Chemical and Gas Process Industries." Journal of the Korean Institute of Gas 15, no. 1 (February 28, 2011): 1–8. http://dx.doi.org/10.7842/kigas.2011.15.1.001.

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44

YAMAUCHI, Norihiro, and Toshiyuki ASAKURA. "Development of Neuro Process Controller for Chemical Reaction Control." Proceedings of Conference of Hokuriku-Shinetsu Branch 2003.40 (2003): 235–36. http://dx.doi.org/10.1299/jsmehs.2003.40.235.

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45

Yamamoto, T., C. L. Yang, M. R. Beltran, and Z. Kravets. "Plasma-assisted chemical process for NO/sub x/ control." IEEE Transactions on Industry Applications 36, no. 3 (2000): 923–27. http://dx.doi.org/10.1109/28.845073.

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46

Duty, C., D. Jean, and W. J. Lackey. "Laser chemical vapour deposition: materials, modelling, and process control." International Materials Reviews 46, no. 6 (June 2001): 271–87. http://dx.doi.org/10.1179/095066001771048727.

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47

Noh, Kap Kyun, Dongil Shin, En Sup Yoon, and Jong Dae Lee. "Adaptive output feedback control of a nonlinear chemical process." IFAC Proceedings Volumes 34, no. 25 (June 2001): 691–97. http://dx.doi.org/10.1016/s1474-6670(17)33905-8.

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48

Zhao, Futao, Wei Du, and Guozhen Yu. "An improved generalized analytical predictor for chemical process control." Journal of Process Control 9, no. 2 (April 1999): 185–91. http://dx.doi.org/10.1016/s0959-1524(98)00028-6.

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49

Asbjornsen, Odd A. "Chemical process control: An introduction to theory and practice." Automatica 21, no. 4 (July 1985): 502–4. http://dx.doi.org/10.1016/0005-1098(85)90090-1.

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50

Song, Jeong Jun, and Sunwon Park. "A fuzzy dynamic learning controller for chemical process control." Fuzzy Sets and Systems 54, no. 2 (March 1993): 121–33. http://dx.doi.org/10.1016/0165-0114(93)90270-r.

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