Abstract

Introduction. Statistical methods of data processing and IT technologies make it possible to introduce new modern methods of hazard and risk analysis in food industry. The research objective was to develop new software that would link together various risk-related production data.
Study objects and methods. The research featured food production company LLC Yug (Biysk, Russia) that specializes in functional products and various ready-made software automation solutions. The study also involved statistical methods, methods of observation, collection of primary information, sequential top-down development of algorithms, and the Java programming language.
Results and discussion. Food producers have a registration procedure for inconsistencies and violations of permissible limits at critical control points. The authors developed a new software program that allows production line operators to enter data on downtime and other violations of the production process. The program makes it possible for managers to receive up-to-date reports on various criteria, identify violations, and select appropriate corrective actions. This ready-made solution automates the process of accounting and hazard analysis. The program was tested at LLC Yug with the focus on the time that operators and managers needed to register the problem, analyze the data, develop corrective or preventive measures, and apply them.
Conclusion. The new software proved to be less time-consuming than standard procedures applied in food industry and made it possible to save the time that operators and managers spent on decision making and reporting.

Keywords

Information technology, program, monitoring, algorithm, quality, safety, operator, manager, data processing, data visualization, risk management

REFERENCES

1. Liu F, Rhim H, Park K, Xu J, Lo CKY. HACCP certification in food industry: Trade-offs in product safety and firm performance. International Journal of Production Economics. 2021;231. https://doi.org/10.1016/j.ijpe.2020.107838.
2. Chen H, Liu S, Chen Y, Chen C, Yang H, Chen Y. Food safety management systems based on ISO 22000:2018 methodology of hazard analysis compared to ISO 22000:2005. Accreditation and Quality Assurance. 2019;25(1):23–37. https://doi.org/10.1007/s00769-019-01409-4.
3. Vukman D, Viličnik P, Vahčić N, Lasić D, Niseteo T, Panjkota Krbavčić I, et al. Design and evaluation of an HACCP gluten-free protocol in a children's hospital. Food Control. 2021;120. https://doi.org/10.1016/j.foodcont.2020.107527.
4. Escanciano C, Santos-Vijande ML. Reasons and constraints to implementing an ISO 22000 food safety management system: Evidence from Spain. Food Control. 2014;40(1):50–57. https://doi.org/10.1016/j.foodcont.2013.11.032.
5. Psomas EL, Kafetzopoulos DP. HACCP effectiveness between ISO 22000 certified and non-certified dairy companies. Food Control. 2015;53:134–139. https://doi.org/10.1016/j.foodcont.2015.01.023.
6. Feng H, Chen J, Zhou W, Rungsardthong V, Zhang X. Modeling and evaluation on WSN-enabled and knowledge-based HACCP quality control for frozen shellfish cold chain. Food Control. 2019;98:348–358. https://doi.org/10.1016/j.foodcont.2018.11.050.
7. Hasnan NZN, Mohd Ramli SH. Modernizing the preparation of the Malaysian mixed rice dish (MRD) with Cook-Chill Central Kitchen and implementation of HACCP. International Journal of Gastronomy and Food Science. 2020;19. https://doi.org/10.1016/j.ijgfs.2019.100193.
8. Chen H, Liou B-K, Dai F-J, Chuang P-T, Chen C-S. Study on the risks of metal detection in food solid seasoning powder and liquid sauce to meet the core concepts of ISO 22000:2018 based on the Taiwanese experience. Food Control. 2020;111. https://doi.org/10.1016/j.foodcont.2019.107071.
9. How remote monitoring can improve water treatment management [Internet]. [cited 2021 Aug 08]. Available from: https://www.foodqualityandsafety.com/article/water-treatment-remote-monitoring/.
10. da Cunha D. T. Improving food safety practices in the foodservice industry. Current Opinion in Food Science. 2021;42:127–133. https://doi.org/10.1016/j.cofs.2021.05.010.
11. Muda I, Erlina AA. Influence of human resources to the effect of system quality and information quality on the user satisfaction of accrual-based accounting system. Contaduría y Administración. 2018;64(2). https://doi.org/10.22201/fca.24488410e.2019.1667.
12. Fazullina OF, Smirnov SO. New safety management system for pasta production. Food Processing: Technique and Technology. 2020;50(4):736–748. (In Russ.). https://doi.org/10.21603/2074-9414-2020-4-736-748.
13. Trofimova NB, Ermolaeva EO, Trofimov IE. Development of a software product for the automation of hazard analysis and critical control points in food production. Food Processing: Techniques and Technology. 2020;50(1):167–175. (In Russ.). https://doi.org/10.21603/2074-9414-2020-1-167-175.
14. Prosekov AYu, Ivanova SA. Providing food security in the existing tendencies of population growth and political and economic instability in the world. Foods and Raw Materials. 2016;4(2):201–211. https://doi.org/10.21179/2308-4057-2016-2-201-211.
15. Surkov IV, Ermolaeva EO, Rossieva DV, Trofimova NB, Trofimov IE. Ehkspertnaya sistema opredeleniya opasnostey i kontrolʹnykh tochek proizvodstvennykh protsessov po printsipam KHASSP [Expert system for determining the hazards and control points of production processes according to the principles of HACCP]. Certificate of registration of the computer program RU 2018666105. 2018.
16. Surkov IV, Ermolaeva EO, Rossieva DV, Trofimova NB, Trofimov IE. Uchet i analiz nesootvetstviy vnutrennego audita integrirovannoy sistemy menedzhmenta (uchet i analiz nesootvetstviy vnutrennego audita ISM) [Accounting and analysis of inconsistencies in the internal audit of the integrated management system (accounting and analysis of inconsistencies in the internal audit of the IMS)]. Certificate of registration of the computer program RU 2017616985. 2017.
17. Prokhorov AA, Ermolaeva EO, Trofimova NB, Trofimov IE. Uchet opasnykh faktorov i nesootvetstviy protsessov proizvodstva pishchevoy produktsii [Hazards and inconsistencies in food production processes]. Certificate of registration of the computer program RU 2018665743. 2018.
18. Woźniak D, Gohardani B, Majchrzak E, Hoti E, Urikova O. Product lifecycle management service system. In: Barolli L, Nishino H, Miwa H, editors. Advances in intelligent networking and collaborative systems. Cham: Springer; 2019. pp. 525–533. https://doi.org/10.1007/978-3-030-29035-1_51.
19. Drozdov D, Atmojo UD, Pang C, Patil S, Ali MI, Tenhunen A, et al. Utilizing software design patterns in product-driven manufacturing system: A case study. In: Borangiu T, Trentesaux D, Leitão P, Boggino AG, Botti V, editors. Service oriented, holonic and multi-agent manufacturing systems for industry of the future. Cham: Springer; 2020. pp. 301–312. https://doi.org/10.1007/978-3-030-27477-1_23.
20. Rossieva DV, Ermolaeva EO, Trofimova NB, Trofimov IE. Development of software product to support the process of internal audit of a food company. Food Processing: Techniques and Technology. 2017;46(3):135–140. (In Russ.).
21. Angelopoulos C, Filios G, Nikoletseas S, Raptis TP. Keeping data at the edge of smart irrigation networks: A case study in strawberry greenhouses. Computer Networks. 2020;167. https://doi.org/10.1016/j.comnet.2019.107039.
22. Assunção WKG, Vergilio SR, Lopez-Herrejon RE. Automatic extraction of product line architecture and feature models from UML class diagram variants. Information and Software Technology. 2020;117. https://doi.org/10.1016/j.infsof.2019.106198.
23. Wang L, Liu C. Evolutionary game analysis on government supervision and dairy enterprise in the process of product recall in China. International Journal of Information Systems in the Service Sector. 2020;12(1):44–66. https://doi.org/10.4018/IJISSS.2020010104.
24. Sahni V, Srivastava S, Khan R. Modelling techniques to improve the quality of food using artificial intelligence. Journal of Food Quality. 2021;2021. https://doi.org/10.1155/2021/2140010.
25. Deǧerli M, Özbudak EK, Asli Aytaç A, Nur Çolakoǧlu F, Demirel OE. Project-level audits as part of an effective quality assurance process: Applied practices and relevant lessons learned. CEUR Workshop Proceedings. 2017;1980:391–402.
26. Lisitsyn AB, Chernukha IM, Nikitina MA. Russian methodology for designing multicomponent foods in retrospect. Foods and Raw Materials. 2020;8(1):2–11. https://doi.org/10.21603/2308-4057-2020-1-2-11.
27. Bychkova SM, Karelskaia SN, Abdalova EB, Zhidkova EA. Social responsibility as the dominant driver of the evolution of reporting from financial to non-financial: theory and methodology. Foods and Raw Materials. 2021;9(1):135–145. https://doi.org/10.21603/2308-4057-2021-1-135-145.