INFORMATION SYSTEM FOR OPTIMAL CONTROL OF THE BAKING PROCESS OF BAKERY PRODUCTS

Introduction. General-purpose MES systems are not adapted to bakery production: they do not provide flexible adjustment of baking parameters and do not account for the influence of process conditions on product quality. Their integration is time-consuming and requires extensive configuration or refinement, which highlights the need for applied, industry-specific solutions.

Aim. To develop and test an optimal control information system for the baking process of bakery products while maintaining required quality standards.

Methods. The study presents an information system for optimal control of the baking process based on an optimization model constructed through correlation-regression analysis and gradient descent. The empirical basis was formed from expert surveys of technologists and technological documentation. Testing was carried out in a model-based emulation environment.

Results. The study offers an information system for optimal control of the baking process implemented as a software module suitable for integration into a MES environment. The scientific contribution lies in the formulation of the optimization problem and the mathematical model of baking process control. Unlike existing research focused on line-loading planning or quality assessment without integration into automated control loops, the proposed model provides simultaneous optimization of formulation and baking parameters. Testing in an emulated environment showed a reduction in average quality deviations by fifteen percent and a decrease in raw-material consumption by up to seven percent (R² from 0.48 to 0.79; MSE from 0.0009 to 7.89 for the regression models).

Conclusions. The developed system can be integrated into a MES environment as a specialized module for optimal baking-process control. The presented approach formalizes control and optimization procedures in bakery production and can be scaled to other sectors of the food industry.

1. Babor, M., Pedersen, L., Kidmose, U., Paquet‑Durand, O., & Hitzmann, B. (2022). Application of Non‑Dominated Sorting Genetic Algorithm (NSGA‑II) to Increase the Efficiency of Bakery Production: A Case Study. Processes, 10(8), 1623. https://doi.org/10.3390/pr10081623

2. Babor, M., Paquet‑Durand, O., Kohlus, R., & Hitzmann, B. (2023). Modeling and Optimization of Bakery Production Scheduling to Minimize Makespan and Oven Idle Time. Scientific Reports, 13, 235. https://doi.org/10.1038/s41598-022-26866-9

3. Hadiyanto, H., Noomhorm, A., & Hadipernata, M. (2009). Multi‑Objective Optimization of the Bread Production Process Using Response Surface Methodology and Desirability Function. Journal of Food Process Engineering, 32(3), 382–400. https://doi.org/10.1111/j.1745-4530.2008.00240.x

4. Limanska, N. V., Hrybkov, S. V., & Kostikov, M. P. (2022). An Intelligent Production Planning Support System Between Bakery Enterprises. Herald of Kherson National Technical University, (2)(81), 69–78. http://dx.doi.org/10.35546/kntu2078-4481.2022.2.8

5. Serpa, N. P., Silva, D. J. C. da, Wegner, R. D. S., & Stertz, E. D. S. (2022). Quality and Sustainability in the Production Process: A Study of Bakeries Using an Integrated Multi‑Criteria Method Based on Fuzzy AHP and Fuzzy TOPSIS. Environmental Quality Management, 1(1), 1–12. https://doi.org/10.1002/tqem.21906

6. Abramov, G. I. (2020). On the Use of Information‑Analytical Systems in the Context of Modern ICT Development. StudNet, 3(4), 632–637.

7. Adamadziev, K. R., & Akutaev, S. G. (2017). Information Systems for Automation of Analysis and Planning in Food‑Industry Enterprises (Case of the Republic of Dagestan). Regional Economy: Theory and Practice, 15(2(437)), 303–314.

8. Alekseenko, A. A. (2020). Theoretical Foundations for the Study of Critical Control Points Monitoring Systems in the Bread Production Process. Science Without Borders, (3)(43), 46–52.

9. Aslanova, I. V. (2017). MES as a Basis for Developing Enterprise Production‑Process Control Systems. Russian Entrepreneurship, 18(11), 1651–1658.

10. Ashmarova, O. V., & Fedulova, E. A. (2016). Application Potential of Automated Management Information Systems in Food‑Industry Enterprises. Technology and Techniques of Food Production, 41(2), 170–176.

11. Egushova, E. A., & Pozdnyakova, O. G. (2018). Technological Aspects of Producing Functional Bread Products. Achievements of Science and Technology of the Agro‑Industrial Complex, 32(12), 90–93. http://dx.doi.org/10.24411/0235-2451-2018-11225

12. Efremova, E. N. (2016). Quality Assessment of Bakery Products. Agrarian Bulletin of the North Caucasus, (3)(23), 20–24.

13. Zinovyeva, M. A., & Novitsky, V. O. (2024). Automated System for Optimizing Control of Rye‑Wheat Bread Baking Regimes. Information‑Analytical and Intelligent Systems for Production and the Social Sphere, Collection of Articles (March 28, 2024), 11–18.

14. Koneva, D. A. (2019). Modern ERP Systems in the Russian Market: A Comparative Review. Academy, (4)(43), 43–46.

15. Kotandzhyan, A. V., & Bindzyar, D. A. (2023). Analysis of Modern Information‑Analytical Systems. Student. Science. Region, (1), 65–69. http://dx.doi.org/10.24412/cl-37131-2023-1-65-69

16. Novitsky, V. O. (2011). Methodology of System‑Wide Design of Automated Systems [in Russian]. Moscow: Moscow State University of Printing Arts Publishing, 120 pp.

17. Pavelev, V. P., & Paveleva, E. V. (2013). Application of Factor Analysis to Evaluate Enterprise Management Efficiency. Bulletin of Moscow State Technical University MAMI, 1(4(18)), 242–248.

18. Prakhov, A. D. (2015). Accounting Process and Methods for Automating Flour Dosing within a Bakery Production Cycle. Science Time, (5)(17), 365–370.

19. Ryazantseva, E. A. (2023). Application of Correlation‑Regression Tools to Analyze Socially Significant Factors. EFO: Economics. Finance. Society, (1)(5), 65–74. http://dx.doi.org/10.24412/2782-4845-2023-5-65-74

20. Tasvayeva, A. N. (2012). Data Flow Diagrams and Use‑Case Diagrams as Tools for Designing Information Systems. Models, Systems, Networks in Economics, Engineering, Nature and Society, (2)(3), 143–146.

21. Tashmatova, Sh. S. (2024). Algorithms Optimized for Efficient Neural Network Design. Science and Innovation, 3(Special Issue 33), 531–535. http://dx.doi.org/10.5281/zenodo.11192924

22. Tsarukyan, L. A., Berezovskaya, A. A., & Perova, M. V. (2015). Practice of ERP Systems Implementation in Russian Enterprises. Innovation Management: Theory, Methodology, Practice, (13), 117–122.