2020Journal of Discrete Mathematical Sciences and CryptographyRequires access

Designing a Simulink model for a mixed model stochastic assembly line : A case study using a water bottling plant

Rangith Baby Kuriakose, Herman Jacobus Vermaak

Open publisher page 17 citations

Abstract

As the world is moving into the 4th Industrial revolution, commonly referred to as Industry 4.0, mass production is giving way to mass customization. This shift necessitates a change in the design of the assembly line with flexibility and multi variant manufacturing taking precedence. These kind of assembly lines that can manufacture multiple models without a predetermined manufacturing time are referred to as mixed model stochastic assembly lines.This paper looks at how such a mixed model stochastic assembly line can be modelled. This is done by taking the case study of a water bottling plant that is being developed at the university where this research is conducted. The water bottling plant needs to produce 500 ml and 750 ml bottles of clean drinking water which can be used within the university or be sold externally.The primary aim of this paper is to develop a MATLAB model for the water bottling plant and study the results from the simulations. These results will shed light on how the model can be optimized thereby contribute to the niche area of Mixed Model Stochastic Assembly Line Balancing.

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What this paper is about

As the world is moving into the 4th Industrial revolution, commonly referred to as Industry 4.0, mass production is giving way to mass customization. This shift necessitates a change in the design of the assembly line with flexibility and multi variant manufacturing taking precedence. These kind of assembly lines that can manufacture multiple models without a predetermined manufacturing time are referred to as mixed model stochastic assembly lines.This paper looks at how such a mixed model stochastic assembly line can be modelled. This is done by taking the case study of a water bottling plant that is being developed at the university where this research is conducted. The water bottling plant needs to produce 500 ml and 750 ml bottles of clean drinking water which can be used within the university or be sold externally.The primary aim of this paper is to develop a MATLAB model for the water bottling plant and study the results from the simulations. These results will shed light on how the model can be optimized thereby contribute to the niche area of Mixed Model Stochastic Assembly Line Balancing.

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OpenAlex reports 17 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

As the world is moving into the 4th Industrial revolution, commonly referred to as Industry 4.0, mass production is giving way to mass customization. This shift necessitates a change in the design of the assembly line with flexibility and multi variant manufacturing taking precedence. These kind of assembly lines that can manufacture multiple models without a predetermined manufacturing time are referred to as mixed model stochastic assembly lines.This paper looks at how such a mixed model stochastic assembly line can be modelled. This is done by taking the case study of a water bottling plant that is being developed at the university where this research is conducted. The water bottling plant needs to produce 500 ml and 750 ml bottles of clean drinking water which can be used within the university or be sold externally.The primary aim of this paper is to develop a MATLAB model for the water bottling plant and study the results from the simulations. These results will shed light on how the model can be optimized thereby contribute to the niche area of Mixed Model Stochastic Assembly Line Balancing.

Key concepts: Bottling line, Mass customization, Flexibility (engineering), Computer science, Line (geometry), Stochastic modelling, Industrial engineering, Production line

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Designing a Simulink model for a mixed model stochastic assembly line : A case study using a water bottling plant — Research Paper | ScholarLens