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Operational decision support for a dairy manufacturing industry using simulation modelling

Minardi-Kwiatkowska, Barbara (2018) Operational decision support for a dairy manufacturing industry using simulation modelling. Master of Engineering thesis, Dublin City University.

Abstract
The Dairy Industry has to deal with complexities compared to other sectors such as perishability and seasonality. The opportunity to properly process milk during the peak season is the most important issue for any dairy company otherwise not only tangible values such as sales are lost but also intangible values such as the credibility can be damaged. The purpose of this research is to describe the use of a milk industry model and to study the best scenario for the demand on manufacturing performance of Irish dairy co-operative society. The model, developed in ExtendSim®, dynamic simulation software, is a framework that provides a what-if analysis considering changes in different scenarios in order to illustrate potential benefits to managers for a successful demand planning. The discrete-rate simulation model was built according to an SME Company and the operational decisions are made after the customer's orders. An analysis correlating the bottleneck and profitability of dairy ingredients such as Casein/ Caseinate evaluating the impact on the factory capacity. Considering that both products currently are competing for the utilization of a common piece of equipment, a planned sequencing process must be followed, thus this will guarantee that there will be no delay in the production and the specific demand is achieved. The key features of the proposed approach are combined of the shutdowns, breakdowns and capacities in the actual flow behaviour, collect the results of adjustments from future demands profile and identify the opportunities of value-adding activities to the enterprise via simulation. Moreover, this research also proposes a different approach to Caseinate production comparing the current process to the proposed solution to increase the output.
Metadata
Item Type:Thesis (Master of Engineering)
Date of Award:November 2018
Refereed:No
Supervisor(s):Geraghty, John
Subjects:Engineering > Production engineering
Mathematics > Stochastic analysis
Computer Science > Computer simulation
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Mechanical and Manufacturing Engineering
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 3.0 License. View License
Funders:Enterprise Ireland
ID Code:22449
Deposited On:22 Nov 2018 12:13 by John Geraghty . Last Modified 29 Jun 2022 03:30
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