Optimization of Food Industry Production Using the Monte Carlo Simulation Method: A Case Study of a Meat Processing Plant

Koroteev, Mikhail; Romanova, Ekaterina; Korovin, Dmitriy; Shevtsov, Vasiliy; Feklin, Vadim; Никитин, П. В.; Makrushin, Sergey; Bublikov, K. V.

doi:10.3390/informatics9010005

Cited by 5 publications

(4 citation statements)

References 32 publications

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“…The reason is its modification to current conditions and the usability of modern software tools, which leads to its wide applicability in various scientific disciplines. The Monte Carlo method is currently used in the field of physics and electrical engineering [26][27][28][29], chemistry [30,31], safety assessment [32], industry [33,34], public sector [35], economy [36][37][38][39], and others. We most often encounter the Monte Carlo method in simulations in economics, e.g., in option pricing, financial decisionmaking, etc.…”

Section: Modern Methods In Financial Managementmentioning

confidence: 99%

Model for Sustainable Financial Planning and Investment Financing Using Monte Carlo Method

2022

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The article deals with current issues of finance and investment planning with a selective focus on financial decision-making processes using sophisticated software tools. The article has a special significance in this period when it is necessary to re-evaluate and consider ways of appropriate and effective investment and financial policy in view of the restrictions in enterprises in Slovakia, which brings with it the global pandemic COVID-19 or another crisis in enterprises. The aim of the article is to propose a methodology as a tool for streamlining the investment activities of companies. The proposed methodology combines the usability of traditional and modern economic methods, making it an important tool for the sustainability and competitiveness of enterprises. Three variants of investment decisions in the enterprise were simulated using simulation in terms of two approaches. The first approach focuses on mathematical–economic calculations of deterministic modeling through traditional software tools. The second stochastic modeling uses the simulation of financial risks using a modern software tool using the Monte Carlo method. The output is the creation of a graphical management model in the form of an algorithm.

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Section: Modern Methods In Financial Managementmentioning

confidence: 99%

Model for Sustainable Financial Planning and Investment Financing Using Monte Carlo Method

2022

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“…This simulation technique is widely used within the food industry for quality assurance and productivity levels, but financial and operational efficiency remains challenging for food supply chains. The DES technique is used in practical aspects within food supply chains to determine the process performance and improve the standard of quality in food production [21].…”

Section: Introductionmentioning

confidence: 99%

The Adoption of Robotic Process Automation Considering Financial Aspects in Beef Supply Chains: An Approach towards Sustainability

et al. 2023

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Sustainable beef production is a global challenge in present times. This research paper aims to investigate the financial risks and barriers in the adoption of robotic process automation (RPA), which has emerged as a strategic catalyst for achieving sustainability in the beef sector. Beef manufacturers constantly strive to achieve sustainability and a competitive advantage in order to gain enhanced beef productivity at low operational costs. There is a gap in the research, as there is a lack of knowledge about the financial aspects, barriers, and challenges influencing the RPA adoption process in the beef supply chain. To bridge this gap, secondary research is used to extract statistical data and information relevant to the RPA adoption process in beef supply chains, considering financial aspects. This study utilises a simulation method adopting a process model created in previous research and analyses different scenarios based on financial parameters using values or variables in Simul8 software. The scenario analysis allows for the identification of financial risks in the adoption of RPA and evaluates the simulation results from a sustainability perspective. The scenario analysis highlights the financial risks and barriers in the adoption of RPA in beef supply chains through process simulation, using financial parameters as a basis. KPI values, income statements, and carbon emission reports are generated to evaluate the main bottlenecks at various beef supply chain stages, thus allowing business users to conduct a thorough cost analysis. Successful adoption of RPA can lead to reduced supply chain complexity, thus improving financial and operational efficiency, which results in increased beef productivity, quality, and shelf life. This study is extremely important as it assesses scenarios from a sustainability perspective and contributes to academic knowledge and professional practice. It provides a process model to support the financial and ethical decision-making of managers or stakeholders, while helping the beef sector adopt RPA with greater ease. The process model can be adopted or modified according to the financial circumstances and individual requirements of business users. Furthermore, it provides decision-makers with the knowledge to eliminate or prevent financial barriers, thus advancing and accelerating the adoption of RPA. Robust adoption of RPA assists beef supply chains in gaining higher productivity at reduced costs, thus creating sustainable value.

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“…Through economic analysis in [20], a working framework was proposed to generate a complex procedure for optimizing investment decisions in oil field development. The problem evaluated in [21] is related to optimizing an industrial enterprise budget using simulations of the production process. The authors of [22] advanced a methodology for optimizing intertemporal investment decisions through a consensusoriented process.…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Methodology for Investment Project Assessment Based on Monte Carlo Simulation

et al. 2023

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This article presents a methodology for assessing investment projects representing the sequence of steps necessary for a comprehensive assessment and optimization of an investment project. The assessment process starts with the quantitative forecasting of stochastic input factors, with the selection of risk factors and the definition of their uncertainty. That is followed by the design of a mathematical model for calculating the criterion of economic efficiency of investment, its calculation mathematically, and forecasting by Monte Carlo simulation. The simulation output is assessed from the point of view of risk, and in case of an unacceptable result, the possibilities for project optimization are proposed. Finally, the proposed methodology was applied to an investment project model, where individual principles are practically demonstrated.

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Optimization of Food Industry Production Using the Monte Carlo Simulation Method: A Case Study of a Meat Processing Plant

Cited by 5 publications

References 32 publications

Model for Sustainable Financial Planning and Investment Financing Using Monte Carlo Method

Model for Sustainable Financial Planning and Investment Financing Using Monte Carlo Method

The Adoption of Robotic Process Automation Considering Financial Aspects in Beef Supply Chains: An Approach towards Sustainability

A Comprehensive Methodology for Investment Project Assessment Based on Monte Carlo Simulation

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