Implementation and Analysis of Pizza Production Process Using Fuzzy Logic Based on Multi-Factors Criteria

Authors

  • Pankaj Kumar Research Scholar, Department of Computer Science and Engineering, Om Sterling Global University, Hisar, Haryana-125001
  • Rajinder Singh Sodhi Associate Professor, Department of Computer Science and Engineering, Om Sterling Global University, Hisar, Haryana-125001

Keywords:

Artificial intelligence, Fuzzy logic and set, Fuzzy inference system, food industry

Abstract

In contemporary food companies, whether it's a quick food supplier or a fixed restaurant, the waiting time significantly influences customer satisfaction. Extensive empirical evidence supports the notion that businesses in the food industries must compete primarily based on the speed of their food service. Within the food industry community, it is widely recognized that customers highly value promptness and accord it substantial importance in selecting their preferred food service provider. In this study I am introducing a scheduling system for the food industry, employing a fuzzy-based mechanism system. It specifically focuses on determining the necessary number of devices used in industry like ovens and workers for various tasks within the food manufacturing process, with a special emphasis on pizza production. The research considers factors such as reducing finances, enhancing the satisfaction of the customers, and elevating service quality. Implementation of the system was carried out using Matlab software, involving the development of code to achieve the desired outcomes.

Downloads

Download data is not yet available.

References

Allon, Gad, Awi Federgruen, and Margaret Pierson. "How Much Is a Reduction of Your Customers' Wait Worth? An Empirical Study of the Fast-Food Drive-Thru Industry Based on Structural Estimation Methods." Manufacturing and Service Operations Management 13.4 (2011): 489-507.

Bernstein, Sharon. “Fast-food industry is quietly defeating Happy Meal bans.” Los Angeles Times. May 18, 2011.

Cheng, Ching Chan, Shao-I Chiu, Hsiu-Yuan Hu, and Ya-Yuan Chang. "A Study on Exploring the Relationship between Customer Satisfaction and Loyalty in the Fast Food Industry: With Relationship Inertia as a Mediator." African Journal of Business Management 5.13 (2011): 5118-126. R. Nicole, “Title of paper with only first word capitalized,” J. Name Stand. Abbrev., in press.

Hwang, Johye, Long Gao, and Wooseung Jang. "Joint Demand and Capacity Management in a Restaurant System." European Journal of Operations Research 207 (2010): 465-72..

Kahraman, Cengiz, Ufuk Cebeci, and DaRuan. "Multi-attribute Comparison of Catering Service Companies Using Fuzzy AHP: The Case of Turkey." Int. J. Production Economics 87 (2004): 171-84

Jiping Niu 1,John Dartell2 Application Of Fuzzy Mrp-ii In Fast Moving Consumer Goods Manufacturing Industry... Faculty of Engineering, University of Technology, Sydney 15 Broadway, Ultimo, NSW, 2007, AUSTRALIA

Sanjoy Petrovic1 And Carole Fayad2 A Genetic Algorithm For Job Shop Scheduling With Load Balancing.

Ripon Kumar Chakraborety1 And Md. Aktar Hassen2. Solving An Aggregate Production Planning Problem By Using Basal Genetic Algorithm Approach. International Journal of Fuzzy Logic Systems (IJFLS) Vol.3, No1, January 2013

Manish Agrawal1. Fuzzy Logic Control of Washing Machine.

Pramot srinoi prof.Ebrahimshayan1, Dr.Fatemehghot2 Scheduling Of Flexible Manufacturing Systems Using Fuzzy Logic., School Of Mathematical Sciences.2004

Zaiul Hassan Serneabat1, Nabila Chowdhury2 And Dr. A.K.M. Mausud3Simulation Of Flexible Manufacturing Using Fuzzy Logic

Dusan Teodornic1. Fuzzy Logic System Transportation. 11 may 1998.

L. A. Zadeh, Fuzzy Sets, Information and Control, 8(1965) 338-353.

Yager, R.R. and Zadeh, L.A. (1992) An Introduction to Fuzzy Logic Applications in Intelligent Systems. Kluwer Academic Publishers, Boston.

Harold W. Lewis, 1997, The foundations of fuzzy control: IFSR international series on systems science and engineering, New York:Plenum Press

Elmohamed, M.A. Saleh; Fox, Geoffrey; and Coddington, Paul, "A Comparison of Annealing Techniques for Academic Course Scheduling", Northeast Parallel Architecture Center. 1997, Paper 8.

J., George, Ute H., and BoYuan. Fuzzy set theory: foundations and applications. Prentice Hall PTR, 1997.

Shin-Yun Wang & Cheng Few Lee “Application of Fuzzy Set Theory to Finance Research: Method and Application” Handbook of Quantitative Finance & Risk Management pp 1183-1199

Downloads

Published

25.12.2023

How to Cite

Kumar, P. ., & Sodhi, R. S. . (2023). Implementation and Analysis of Pizza Production Process Using Fuzzy Logic Based on Multi-Factors Criteria. International Journal of Intelligent Systems and Applications in Engineering, 12(2), 112–118. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4226

Issue

Section

Research Article