Open Access Open Access  Restricted Access Subscription or Fee Access

A review on factory automation

Shubhaseesh Srivastava

Abstract


Automation, also known as automatic control, refers to the use of numerous control systems to operate machinery, factory operations, boilers, heat treatment ovens, telephone network switching, steering and stabilisation of ships and aircraft, and other equipment with little to no human involvement. Saving money on labour, energy, and materials, as well as enhancing the precision, accuracy, and quality of the final product, are among automation's key benefits. Connecting factory equipment to process control systems to increase their effectiveness and dependability is known as factory automation, also known as industrial automation. As a result, expenses are reduced, quality is raised, there is more flexibility, and the environment isn't as negatively affected. Create applications for factory automation that are intelligent, adaptable, and efficient to conserve energy and prolong system life. The use of systems and technology to regulate a production process is known as "factory automation," with the ultimate objective being to boost output and cut costs. The degree of automation can range from partial automation of a specific task to complete automation with no human interference. At any stage of the production process, from material quantity management to production and assembly, and lastly to packaging and shipping, factory automation can be used.

 


Keywords


automation, factory automation, Single automated machine, automated production lines, Minimal automation.

Full Text:

PDF

References


AI Maaazine, 1988 Spring, pp 27-45. Lauber, R.J: Forecasting Real-Time Behaviour During Software Design using a ASE Environ-Int. Conf. on System Science 1989, pp 645-653.

D. Agrawal, A. El Abbadi, F. Emekci and A. Metwally, 2009, Database Management as a Service: Challenges and Opportunities, Proceedings of the 2009 25th International Conference on Data Engineering, IEEE, pp. 1709-1716.

Blake, I.F., Kolesnikov, 2006, V. Conditional Encrypted Mapping and Comparing Encrypted Numbers. In: Di Crescenzo, G., Rubin, A. (eds.) FC 2006. Springer, Heidelberg, LNCS, vol. 4107, pp. 206–220.

D. X. Song, D. Wagner, and A. Perrig, “Practical techniques for searcheson encrypted data,” in SP ’00: Proceedings of the 2000 IEEE Symposiumon Security and Privacy, 2000, pp. 44–55.

C. Grigg et al., “The IEEE reliability test system-1996. A report prepared by the reliability test system task force of the application of probability methods subcommittee,”,” IEEE Trans. Power Syst., vol. 14, no.3, pp. 1010–1020, Aug. 1999.

R. Bhana, “A production simulation tool for systems with integrated photovoltaic energy resources,” M.S. thesis, Dept. Elect. & Comp. Eng., Univ. of Ilinois, Urbana-Champaign, IL, 2011.

R. Xu and D. C. Wunsch, “partitional clustering”, in Clustering, John Wiley & SonsInc., Hoboken, New Jersey, pp. 67-72, 2009.

R. Dominguez, et al., “Optimal offering strategy for a concentrating solar power plant,” Applied Energy, vol. 98, pp.316-325, 2012.

G. Gross, “Electricity Resource Planning”, class notes for ECE 588, Dept. Elect. & Comp. Eng., Univ. Ilinois, Urbana-Champaign, Fall 2012.

A. M. Patnode, “Simulation and Performance Evaluation of Parabolic Trough Solar Power Plants." Dept. Mech. Eng., Univ. Wisconsin, Madison, 2006.




DOI: https://doi.org/10.37628/ijra.v8i1.1441

Refbacks

  • There are currently no refbacks.