Predictive Reliability Assessment and Profit Optimization of an Ice Cream Plant Using an Artificial Neural Network Technique

Authors

Akash Tewatia, Department of Mathematics, Amity Institute of Applied Sciences, Amity University, Noida, IndiaFollow
Surbhi Gupta, Department of Mathematics, Amity Institute of Applied Sciences, Amity University, Noida, IndiaFollow
Manju Kashyap, Department of Applied Sciences and Humanities, Galgotias College of Engineering and Technology Greater Noida, IndiaFollow
Archana Chauhan, Department of Mathematics, Sharda School of Basic Sciences and Research, Sharda University, Greater Noida, UP, IndiaFollow

Abstract

This study presents a reliability analysis of an ice cream manufacturing facility based on operational failure data. The research develops a ten-component system model that captures plant dynamics and organizes it into three subsystems to reduce computational complexity. The study derives key reliability parameters and constructs a state transition diagram to represent system behavior across multiple operating states. The analysis applies an Artificial Neural Network (ANN) to address the limitations of conventional analytical methods in modeling complex nonlinear systems. The ANN provides strong predictive performance and manages uncertainty within the operational environment. The proposed framework estimates system reliability with high precision and supports maintenance planning and cost optimization. Numerical simulations validate the effectiveness of the ANN-based model. The results demonstrate improved prediction accuracy and greater computational efficiency compared to traditional approaches. State probability deviations are evaluated over a 24-hour period. The up-state probability increases from 95% to 96.02% during the useful life period and from 95% to 96.03% during the wear-out period. The findings confirm that the proposed method enhances reliability prediction, improves maintenance scheduling, and supports cost control and equipment design optimization in ice cream production systems.

Keywords

Artificial neural network, Ice cream plant, Mean time to failure (M.T.T.F), Reliability, State transition

Subject Area

Mathematics

Article Type

Original Study

First Page

1008

Last Page

1019

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite this Article

Tewatia, Akash; Gupta, Surbhi; Kashyap, Manju; and Chauhan, Archana (2026) "Predictive Reliability Assessment and Profit Optimization of an Ice Cream Plant Using an Artificial Neural Network Technique," Baghdad Science Journal: Vol. 23: Iss. 3, Article 23.
DOI: https://doi.org/10.21123/2411-7986.5249