Automated Dairy Plant Production Using OATP Technique


  • V. Manochitra, A. Shaik Abdul Khadir


Rule Mining, Milk Wastage, Data Management, Dairy Plant, Data Mining


In modern day dairy products needs are on demand around the world on other side managing dairy plant in a smart way is also a challenging task. In dairy products manufacturing the milk wastage and easy to decay the milk based products .Most of the milk production plants are working using manual and semi-automated techniques.The potential to incorporate wastes in the production cycle or perform recycle for using it again is a vital solution for conserving resources. Due to the challenges associated with the attribute of sustainability in the dairy circular supply chain, there has been interest shown towards consistent preparation and supervision of quality commitment policies adopted in the circular supply chain network. In this work, OATP (Optimized Aggregated Tuple Process) based on supervised rule mining technique is proposed. The objective of proposed system is to help the managers in dairy plant to plan good logistics so that the quality is maintained and dairy wastes reduced. This proposed technique was done experiment with different set of attributes  like accuracy,milk wastage level and error rate that shown better results than the existing techniques.       


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FoodDrinkEurope, “Data & Trends of the European Food and Drink Industry”,2011.

Eurobarometersurvey,“SMEsareimportantforasmoothtransitiontoa greener economy”. MEMO/12/218, March2012.

European Commission, “Integrated Pollution Prevention and Control”, Reference Document on Best Available Techniques in the Food, Drink and Milk Industries,2006.

DG Environment – European Commission, “Water Scarcity and Droughts,In-DepthAssessment,SecondInterimReport”,June2007.

Sevenster, M. and de Jong, F., “A sustainable dairy sector: Global, regional and life cycle facts and figures on greenhouse-gasemissions”,

CE Delft, 2008

USDairyWaterUse,“Understandingthegeographicalhotspotsfordairy operations with regard to water use impacts”,2011.

CIAA,“ManagingEnvironmentalSustainabilityintheEuropeanFood& Drink Industries”,2001.

Bilgen, B., Dogan, K., “Multistage production planning in the dairy industry: A mixed-integer programming approach. Industrial & EngineeringChemistryResearch54(46),pp.11709-11719,2015.

Doganis, P., Sarimveis, H., “Optimal scheduling in a yogurt production line based on mixed integer linear programming”. Journal of Food Engineering 80 (2), pp. 445-453,2007

Grossmann,I.E.,Hooker,J.,Mendez,C.,Sand,G.,Wassick,J.,“Scope forindustrialapplicationsofproductionschedulingmodelsandsolution methods”.Computers&ChemicalEngineering62,pp161-193,2014

Hazaras, M. J., Swartz, C. L., Marlin, T. E., “Industrial application of a continuous-time scheduling framework for process analysis and improvement”.Industrial&EngineeringChemistryResearch53(1),259- 273,2013.

Kopanos,G.M.,Puigjaner,L.,Georgiadis,M.C.,“Resource-constrained production planning in semicontinuous food industries”, Computers & chemical engineering 35 (12), 2929-2944,2011

Mendez, C. A., Cerda, J., Grossmann, I. E., Harjunkoski, I., Fahl, M., “State-of-the-art review of optimization methods for short-term schedulingofbatchprocesses”.Computers&ChemicalEngineering30 (6), pp 913-946,2006

Okubo,H.,Miyamoto,T.,Yoshida,S.,Mori,K.,Kitamura,S.,Izui,Y., “Project scheduling under partially renewable resources and resource consumption during setup operations”. Computers & Industrial Engineering, 83, pp. 91-99,2015.




How to Cite

V. Manochitra. (2024). Automated Dairy Plant Production Using OATP Technique . International Journal of Intelligent Systems and Applications in Engineering, 12(21s), 2324–2327. Retrieved from



Research Article