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Journal articles on the topic 'Design automation'

To see the other types of publications on this topic, follow the link: Design automation.

Author: Grafiati

Published: 4 June 2021

Last updated: 14 March 2023

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1

Shah, Ankit P., Prof Kalpesh N. Shah, and Prof Harsh B. Joshi. "Design Automation of Shell." Indian Journal of Applied Research 4, no. 4 (October 1, 2011): 214–16. http://dx.doi.org/10.15373/2249555x/apr2014/65.

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2

Cook, B. M. "Design automation." Computer-Aided Design 21, no. 8 (October 1989): 535. http://dx.doi.org/10.1016/0010-4485(89)90064-x.

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3

Farrell, Bradley. "The role of the human in an age of automation." APPEA Journal 58, no. 2 (2018): 545. http://dx.doi.org/10.1071/aj17188.

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The liquefied natural gas (LNG) industry in Australia has a very large installed asset base that is highly automated. This paper explores established, emerging and experimental automations that could materially impact human work in existing LNG facilities. The focus is on automations that assist with physical interventions on the built asset. Riley’s method for assessing the level of automation is used on current and emerging automations in the industry. Use cases demonstrate that as automation increases, the primary focus of the human becomes one of system design, monitoring and intervention. The changing role of the human in this age of automaton has important implications for the development of human work skills for the future: with increasing automation, the nature of work will change. In the future (1) field workers need to supervise and maintain robots, (2) functional specialists need to define and debug robot instruction sets, and (3) system designers need to master the opportunities and challenges in an exciting new field: the robot-human-interface.

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4

Dahiyat, Bassil I., and Stephen L. Mayo. "Protein design automation." Protein Science 5, no. 5 (May 1996): 895–903. http://dx.doi.org/10.1002/pro.5560050511.

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5

Scattini, Noel, and Stanislaw Paul MAJ. "Aquaponics Automation – Design Techniques." Modern Applied Science 11, no. 11 (October 21, 2017): 28. http://dx.doi.org/10.5539/mas.v11n11p28.

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Aquaponics operators that have transitioned from hobby to commercial operators have commonly failed to meet commercial expectations. One of the reasons for failures is the occurrence of severe technical errors. Unexpected events can often have drastic financial consequences on new operators, which could be initially operating within tight margins. Standard techniques like Hazard and Operability studies (HAZOP) are conducted by process and chemical industries to do systematic analysis on a process and its sub-systems. Many aquaponics operators are not familiar with these design processes and find design inadequacies after an event, which normally has financial consequences. This design process is able to identify disturbances that could lead to product deviation and identify hazards that could affect the environment. Identifying process issues and designing engineering controls to prevent or mitigate issues can be carried out in multiple forms or design tools. Failure Mode Effect Analysis (FMEA) is one such tool in a designer’s toolbox and is recognized as an international standard (IEC 60812), which describes techniques to analyze processes that can effect the reliability of a process plant or determine what possible hazards could be present. The use of FMEA has been utilized by industries to aid in carrying out HAZOP design processes, the use of these design processes can lead to inherently reliable processes. Piping and Instrumentation Diagrams also referred to as Process and Instrumentation Diagram (P&ID) are used in the process industry to show an overview of the process plant. The P&ID also identifies instruments that could be required for measurement and any associated alarms that are present to warn operators and mitigate failures in the process. The use of these design tools have identified and mitigated the risks within the initial design concept to prevent these technical errors with engineering controls designed into the process.

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6

Konstantinov, Gennadiy, and Sardor Akhmedov. "Automation of turbogenerator design." Proceedings of Irkutsk State Technical University 23, no. 6 (December 2019): 1126–35. http://dx.doi.org/10.21285/1814-3520-2019-6-1126-1135.

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7

Wharton, D. "Handbook of design automation." Proceedings of the IEEE 74, no. 1 (1986): 236–37. http://dx.doi.org/10.1109/proc.1986.13451.

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8

Nielsen, A. A. K., B. S. Der, J. Shin, P. Vaidyanathan, V. Paralanov, E. A. Strychalski, D. Ross, D. Densmore, and C. A. Voigt. "Genetic circuit design automation." Science 352, no. 6281 (March 31, 2016): aac7341. http://dx.doi.org/10.1126/science.aac7341.

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9

Waxman, Ronald. "Design Automation Standards Development." IEEE Transactions on Reliability R-36, no. 5 (December 1987): 507–13. http://dx.doi.org/10.1109/tr.1987.5222458.

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10

Kusiak, Andrew, and Mehmet Aktan. "Automation in Engineering Design." IFAC Proceedings Volumes 31, no. 15 (June 1998): 217–22. http://dx.doi.org/10.1016/s1474-6670(17)40556-8.

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11

Benel, R. A., R. D. Dancey, J. D. Dehn, J. C. Gutmann, and D. M. Smith. "Advanced Automation Systems design." Proceedings of the IEEE 77, no. 11 (1989): 1653–60. http://dx.doi.org/10.1109/5.47728.

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12

Murphy, E. E. "Technology '89: design automation." IEEE Spectrum 26, no. 1 (January 1989): 34–37. http://dx.doi.org/10.1109/6.16374.

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13

Murphy, E. E., and K. I. Werner. "Technology '88: design automation." IEEE Spectrum 25, no. 1 (January 1988): 35–37. http://dx.doi.org/10.1109/6.4480.

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14

Wilson, John. "Automation and work design." Applied Ergonomics 17, no. 1 (March 1986): 67–68. http://dx.doi.org/10.1016/0003-6870(86)90200-0.

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15

Shull, Emily M., John G. Gaspar, Daniel V. McGehee, and Rose Schmitt. "Using Human–Machine Interfaces to Convey Feedback in Automated Driving." Journal of Cognitive Engineering and Decision Making 16, no. 1 (March 2022): 29–42. http://dx.doi.org/10.1177/15553434221076827.

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The next decade will see a rapid increase in the prevalence of partial vehicle automation, specifically conditional automation (i.e., SAE level 3; SAE, 2018 ). In conditional automation, the expectation is that the user is still receptive to takeover and can disengage while the automation is active, but as the automation approaches its operational limits, or the end of its operational design domain, it issues a request to intervene and the user is expected to retake control. A human–machine interface (HMI) that can safely and effectively transition control is therefore very important. This simulator study investigated how features of the HMI design, specifically feedback about the confidence (i.e., current capability) of the automation influenced transition of control. Participants were assigned to one of three conditions, which received varying amounts of visual and auditory feedback regarding the automation’s confidence. Findings suggest 3-stage auditory-visual feedback about the automation’s confidence may improve subsequent takeover performance compared to 3-stage visual and a control group without feedback. This research demonstrates the potential value of providing more insight into automated feature performance in conditional automation.

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16

Hashem, Nicholas, Mitchell Pryor, Derek Haas, and James Hunter. "Design of a Computed Tomography Automation Architecture." Applied Sciences 11, no. 6 (March 23, 2021): 2858. http://dx.doi.org/10.3390/app11062858.

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This paper presents a literature review on techniques related to the computed tomography procedure that incorporate automation elements in their research investigations or industrial applications. Computed tomography (CT) is a non-destructive testing (NDT) technique in that the imaging and inspection are performed without damaging the sample, allowing for additional or repeated analysis if necessary. The reviewed literature is organized based on the steps associated with a general NDT task in order to define an end-to-end computed tomography automation architecture. The process steps include activities prior to image collection, during the scan, and after the data are collected. It further reviews efforts related to repeating this process based on a previous scan result. By analyzing the multiple existing but disparate efforts found in the literature, we present a framework for fully automating NDT procedures and discuss the remaining technical gaps in the developed framework.

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17

Do, Sung-Hee, and Gyung-Jin Park. "Application of Design Axioms for Glass Bulb Design and Software Development for Design Automation." Journal of Mechanical Design 123, no. 3 (January 1, 2001): 322–29. http://dx.doi.org/10.1115/1.1372705.

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The automation concept is being applied to many areas as the automation system in the manufacturing field works more efficiently. Automation of the design process is also very important for the reduction of the entire engineering cost, and can be achieved by an excellent design process and software development. Design axioms have been announced as a general theoretical framework for all design fields. Application of the design axioms is investigated, and automation is obtained by computer programs. The design process can be analyzed and newly defined to satisfy the axioms. A software system can be designed according to the newly defined design process. In this research, a conventional design process for a TV glass design has been improved by an axiomatic approach, and a software system is designed for the automation of the design process. It is found that the conventional process is coupled, and the coupling causes inefficiencies. A new process is established by the application of axioms. A software design is conducted based on the new process and software development is carried out according to the software design. The developed software is exploited well in the real design.

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18

Marwedel, P., and C. A. Lopez-Barrio. "Design, Design Automation, And Test In Europe." IEEE Design & Test of Computers 14, no. 2 (April 1997): 14–15. http://dx.doi.org/10.1109/mdt.1997.587735.

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19

Shahbazi, Sasha, Kerstin Johansen, and Erik Sundin. "Product Design for Automated Remanufacturing—A Case Study of Electric and Electronic Equipment in Sweden." Sustainability 13, no. 16 (August 12, 2021): 9039. http://dx.doi.org/10.3390/su13169039.

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Remanufacturing is one of the main practices toward a circular economy and industrial sustainability. Remanufacturing is highly dependent on how circular products are designed and developed. Remanufacturing can also benefit from automation for efficiency, accuracy and flexibility. This paper, via a multiple case study, connects the three areas of remanufacturing, product design and automation and investigates how circular product design can facilitate automation remanufacturing processes. First, circular product design guidelines are discussed with regard to remanufacturing. Second, potential areas for automation at three remanufacturers of electric and electronic equipment are pinpointed. Finally, design guidelines are connected to the identified potential automation areas in each remanufacturing process and discussed together. According to our results, the main incentives for automating remanufacturing processes are mainly related to the work environment, efficiency and quality. In addition, several design guidelines can facilitate automated remanufacturing processes; for instance, the standardization of components, fasteners and remanufacturing tools across different models and brands can also facilitate automated remanufacturing, where products can easily and nondestructively be disassembled by a robot or a machine.

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20

Kuamar, B. Shiva, B. Satya Satwik, and N. Anil Kumar A. V. Tarun Kumar. "Design and Implementation of Bluetooth Based Industrial Automation." International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (April 30, 2019): 1130–32. http://dx.doi.org/10.31142/ijtsrd23180.

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21

Godghate, Sushant, and Satoru Yamaguchi. "Rule Based Ship Design Automation." Journal of the Japan Society of Naval Architects and Ocean Engineers 18 (2013): 199–206. http://dx.doi.org/10.2534/jjasnaoe.18.199.

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22

Kikuchi, Shunji. "Design Automation Technology on SMT." HYBRIDS 7, no. 3 (1991): 2–7. http://dx.doi.org/10.5104/jiep1985.7.3_2.

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23

Chen, Deming, Jason Cong, and Peichen Pan. "FPGA Design Automation: A Survey." Foundations and Trends® in Electronic Design Automation 1, no. 3 (2006): 195–334. http://dx.doi.org/10.1561/1000000003.

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24

Camp, B. H. "Electronic Design Automation (EDA '84)." Electronics and Power 31, no. 4 (1985): 327. http://dx.doi.org/10.1049/ep.1985.0202.

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25

Willis, J., and J. Damore. "Design automation Technical Committee Newsletter." IEEE Design & Test of Computers 21, no. 4 (July 2004): 343. http://dx.doi.org/10.1109/mdt.2004.28.

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26

Appleton, Evan, Curtis Madsen, Nicholas Roehner, and Douglas Densmore. "Design Automation in Synthetic Biology." Cold Spring Harbor Perspectives in Biology 9, no. 4 (February 28, 2017): a023978. http://dx.doi.org/10.1101/cshperspect.a023978.

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27

Sudo, T. "Design automation systems in Japan." IEEE Design & Test of Computers 5, no. 6 (December 1988): 14–21. http://dx.doi.org/10.1109/54.9268.

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28

Tyson, Thomas R. "Effective Automation for Structural Design." Journal of Computing in Civil Engineering 5, no. 2 (April 1991): 132–40. http://dx.doi.org/10.1061/(asce)0887-3801(1991)5:2(132).

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29

Dyer, Hilary. "Workstation design for library automation." Program 26, no. 2 (February 1992): 97–110. http://dx.doi.org/10.1108/eb047108.

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30

Liu, Jianxia, and D. R. Strong. "SURVEY OF FIXTURE DESIGN AUTOMATION." Transactions of the Canadian Society for Mechanical Engineering 17, no. 4A (November 1993): 585–611. http://dx.doi.org/10.1139/tcsme-1993-0033.

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31

Hu, X. Sharon. "The 55th Design Automation Conference." IEEE Design & Test 35, no. 5 (October 2018): 75–77. http://dx.doi.org/10.1109/mdat.2018.2862894.

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32

Aitken, Robert. "56th Design Automation Conference Report." IEEE Design & Test 36, no. 6 (December 2019): 80–81. http://dx.doi.org/10.1109/mdat.2019.2942327.

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33

KAKOLLU, MOUNIKA, GIRISH VARMA VEGESNA, Vijaya Nagarjana Devi Duvvuri, SOWJANYA SWATHI NAMBHATLA, and RAVI VEMAGIRI. "Smart Design for Automation System." International Journal of Forensic Software Engineering 1, no. 1 (2019): 1. http://dx.doi.org/10.1504/ijfse.2019.10023806.

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34

Kim, Chol. "Trend of LSI Design Automation." Journal of the Society of Mechanical Engineers 95, no. 884 (1992): 590–93. http://dx.doi.org/10.1299/jsmemag.95.884_590.

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35

Sonnleitner, Bernhard. "Bioprocess automation and bioprocess design." Journal of Biotechnology 52, no. 3 (January 1997): 175–79. http://dx.doi.org/10.1016/s0168-1656(96)01642-2.

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36

Coates, T., A. Smith, M. Emanuel, and B. Peterson. "Automation of optimal laminate design." Australian Journal of Mechanical Engineering 6, no. 2 (January 2008): 119–26. http://dx.doi.org/10.1080/14484846.2008.11464566.

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37

Novoselov, Yu A. "Automation of cutting-tool design." Russian Engineering Research 28, no. 12 (December 2008): 1234–40. http://dx.doi.org/10.3103/s1068798x08120174.

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38

Murphy, E. E. "Reconciling conflicting design-automation standards." IEEE Spectrum 27, no. 3 (March 1990): 44–45. http://dx.doi.org/10.1109/6.48850.

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39

Rahmatian, Sasan. "Automation design: Its human problems." Systems Practice 3, no. 1 (February 1990): 67–80. http://dx.doi.org/10.1007/bf01062822.

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40

Fingrut, Adam, and Darwin Lau. "Construction Automation and Design Research." Technology|Architecture + Design 6, no. 2 (July 3, 2022): 159–61. http://dx.doi.org/10.1080/24751448.2022.2116229.

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41

Bindra, Ashok, and Alan Mantooth. "Modern Tool Limitations in Design Automation: Advancing Automation in Design Tools is Gathering Momentum." IEEE Power Electronics Magazine 6, no. 1 (March 2019): 28–33. http://dx.doi.org/10.1109/mpel.2018.2888653.

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42

Geiselman, Eric E., Christopher M. Johnson, and David R. Buck. "Flight Deck Automation." Ergonomics in Design: The Quarterly of Human Factors Applications 21, no. 3 (July 2013): 22–26. http://dx.doi.org/10.1177/1064804613491268.

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We respond to claims that airline pilots may be losing their ability to manually control aircraft because overreliance on automation is eroding basic manual flying skills. We propose that better training is only a partial solution and that automation can be designed to better support human performance. We do not simply advocate more automation; rather, we envision a more context-aware automation design philosophy that promotes a more communicative and collaborative human-machine interface. Examples are used to illustrate the benefits of this approach. A companion piece to this article, which includes proposed mitigation interface designs, will be available in a subsequent issue of Ergonomics in Design.

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43

Meshram, Kashish, Kshitij Meshram, Ratnesh Mekhe, Yashashri Meshram, Aashay Meshram, and Yogita Narule. "Home Automation Using Arduino." International Journal for Research in Applied Science and Engineering Technology 10, no. 12 (December 31, 2022): 948–51. http://dx.doi.org/10.22214/ijraset.2022.47912.

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Abstract: Technology is a never-ending process. In this project we have developed a low cost but flexible and secure smartphonebased Home Automation System This project aim is to develop and design a home automation system using Arduino with Bluetoothmodule. The communication between the smartphone and the Arduino board is wireless. Password protectionis also used nowadays to allow authorized users from accessing the appliances at home. Home Automation system using the latest and new technology provides more convenience, security and safety. Nowadays, people have less time to handle any work so automationis simple way to handle any device automatically. Manyhome appliances like fan, bulb, automatic door locks arecontrolled by home automation system. The projectmainly focuses on the control of smart home by Smartphone and tries to provide a security based smart home, when the people are not present at home. The motive of this project is to control home appliances in smart home with user friendly design at low cost and simple installation by using Bluetooth technology.

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44

Maksimovskii, D. E. "Automation of process design by design-technological parameterization." Russian Engineering Research 31, no. 9 (September 2011): 870–72. http://dx.doi.org/10.3103/s1068798x1109019x.

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45

Marques Cardoso, Antonio J. "Power Electronics Design Methods and Automation in the Digital Era: Evolution of Design Automation Tools." IEEE Power Electronics Magazine 7, no. 2 (June 2020): 36–40. http://dx.doi.org/10.1109/mpel.2020.2988077.

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46

MIHOLA, MILAN, ZDENEK ZEMAN, ADAM BOLESLAVSKY, JAN BEM, ROBERT PASTOR, and DAVID FOJTIK. "AUTOMATION OF DESIGN OF ROBOTIC ARM." MM Science Journal 2022, no. 3 (September 27, 2022): 5876–82. http://dx.doi.org/10.17973/mmsj.2022_10_2022122.

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Robotic arms are complex mechatronic systems. Therefore, their design requires knowledge and experience from various technical fields, such as mechanics, electrical engineering, electronics or control. From the view of the requirements placed on developers, the design of robotic arms is one of the more complex tasks. Unfortunately, there is a lack of necessary specialists in this field of technology. Therefore, ways are sought to help existing specialists in their work and, simultaneously, reduce the time needed to design the required equipment. At the same time, there are also sought ways to open the way to this issue for developers who do not yet have enough experience. For this reason, algorithms and development tools have been developed to significantly simplify and reduce the time required to design robotic arms and simultaneously automate as much of this process as possible. The aim is to shorten the design time and achieve better results than in the case of designs according to classical procedures.

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47

Smith, Philip J. "Conceptual Frameworks to Guide Design." Journal of Cognitive Engineering and Decision Making 12, no. 1 (October 25, 2017): 50–52. http://dx.doi.org/10.1177/1555343417732239.

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This is a response providing some thoughts triggered by the paper “Issues in Human–Automation Interaction Modeling: Presumptive Aspects of Frameworks of Types and Levels of Automation,” by David Kaber. The key theme is that in order to debate the relative merits of different conceptual frameworks to guide human–automation interaction design efforts, we need a richer understanding of the psychology of design. We need to better understand how contributions by the field of cognitive engineering really affect the efforts of system designers.

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48

Mitchell, Christine M. "Operations Automation: A Concept and Design Methodology for Human-Centered Automation." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 47, no. 3 (October 2003): 320–24. http://dx.doi.org/10.1177/154193120304700315.

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49

Sroka, Michal, Roman Nagy, and Dominik Fisch. "Genetic Algorithms in Test Design Automation." Applied Mechanics and Materials 693 (December 2014): 153–58. http://dx.doi.org/10.4028/www.scientific.net/amm.693.153.

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Automation in the software testing process has significant impact on the overall software development in industry. Therefore, any automation in software testing has huge influence on overall development costs. The present article reviews the current state of the art of test case design automation via genetic algorithms. Three approaches applied in software testing are described with regards to their applicability in the testing of embedded software.

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50

Gui, Xue, Xiao Yan Zheng, Jian Wei Song, and Xia Peng. "Automation Bridge Design and Structural Optimization." Applied Mechanics and Materials 63-64 (June 2011): 457–60. http://dx.doi.org/10.4028/www.scientific.net/amm.63-64.457.

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This paper summarizes the structural optimization applications in civil engineering design and development of the situation based on the characteristics of the bridge structure design process is proposed for the bridge project to the genetic algorithm, neural network, expert system technology as the basis for combining automated design and optimization of structural design of the system; as basic idea, given the structure design of automation system design and optimization of the overall design framework, and prestressed beam design automation is simply an example of structural design and optimization of design automation. Finally, a brief summary of the development process of bridge design software, design automation and optimization that the inevitable trend of development.

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