Adapting discrete-event simulation tools to support tactical forecasting in the automotive industry

Steinemann, Adrian; Taiber, Joachim; Fadel, Georges; Wegener, Konrad; Kunz, Andreas

doi:10.1080/15710882.2013.824484

Cited by 6 publications

(3 citation statements)

References 22 publications

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“…Durante a última década, a simulação de eventos discretos tornou-se a ferramenta de escolha para verificar as decisões estratégicas e medidas táticas no processo de produção. Sendo assim, Steinemanna et al (2013) baseado em um estudo de caso de uma linha de montagem na indústria automotiva, propuseram uma abordagem com base em simulações em ambientes de produção. O estudo teve como objetivo simplificar o uso de ferramentas de simulação a eventos discretos, fornecendo novas interfaces de visualização e interação para apoiar as decisões sobre as medidas táticas e, assim, estabeleceram iniciativas de fabricação enxuta, com monitoramento em tempo real.…”

Section: Proposta De Técnicas Quantitativasunclassified

Logística reversa e sustentabilidade; Modelo de gestão para logística reversa e sua aplicação em produtos eletronicos da linha branca

Nicolli¹,

Franceschini²

2020

Gestão Da Produção Em Foco - Volume 43

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Section: Proposta De Técnicas Quantitativasunclassified

Logística reversa e sustentabilidade; Modelo de gestão para logística reversa e sua aplicação em produtos eletronicos da linha branca

Nicolli¹,

Franceschini²

2020

Gestão Da Produção Em Foco - Volume 43

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“…equipment failure and queue capacity exceeding). DES has been used by multiple researchers regarding automotive industry decision-making assistance (Kendall et al , 1998; Patel and Ma, 2002; Bangsow, 2012; Steinemann et al , 2013; Rybicka et al , 2016; Barrera-Diaz et al , 2018). ABM is of assistance when identifying and modeling the different attributes or when inherent features of distinctive entities are essential to the problem.…”

Section: Introductionmentioning

confidence: 99%

Assessing the transition from mass production to lean manufacturing using a hybrid simulation model of a LEGO® automotive assembly line

Katsigiannis

Pantelidakis

Mykoniatis

2023

IJLSS

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Purpose With hybrid simulation techniques getting popular for systems improvement in multiple fields, this study aims to provide insight on the use of hybrid simulation to assess the effect of lean manufacturing (LM) techniques on manufacturing facilities and the transition of a mass production (MP) facility to incorporating LM techniques. Design/methodology/approach In this paper, the authors apply a hybrid simulation approach to improve an educational automotive assembly line and provide guidelines for implementing different LM techniques. Specifically, the authors describe the design, development, verification and validation of a hybrid discrete-event and agent-based simulation model of a LEGO® car assembly line to analyze, improve and assess the system’s performance. The simulation approach examines the base model (MP) and an alternative scenario (just-in-time [JIT] with Heijunka). Findings The hybrid simulation approach effectively models the facility. The alternative simulation scenario (implementing JIT and Heijunka LM techniques) improved all examined performance metrics. In more detail, the system’s lead time was reduced by 47.37%, the throughput increased by 5.99% and the work-in-progress for workstations decreased by up to 56.73%. Originality/value This novel hybrid simulation approach provides insight and can be potentially extrapolated to model other manufacturing facilities and evaluate transition scenarios from MP to LM.

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“…Based on a case of an assembly line in the automotive industry, Steinemann et al (2012) proposed an approach for running production environments that can benefit from simulation experiments. The goal was to extend and simplify the current discrete event simulation tool to be readily applicable right at the production lines on site, and to support simulation experiments within the improvement process.…”

Section: Introductionmentioning

confidence: 99%

A simulation analysis of the vehicle axle and spring assembly lines

Bae

Zheng

Imani

2015

2015 Winter Simulation Conference (WSC)

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A discrete event simulation model was developed to represent the current vehicle axle and spring assembly lines and understand their dynamics for an automotive company in need of production increase to accommodate expected demand growth. The aim of this study is to provide viable manufacturing plans to improve productivity, and we propose several alternative system component changes to reach the desired throughput level as well as determine the corresponding optimal system configurations. Sensitivity analyses were conducted to measure the effects of various factors such as arrival rate, batch size, and operator resource on throughput, and consequently to find the best scenario. The results of the proposed simulation model demonstrated potential impacts on production capacity increase by considering multiple operational factors while applying feasible improvement strategies. 1 978-1-4673-9743-8/15/$31.00 ©2015 IEEE

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Adapting discrete-event simulation tools to support tactical forecasting in the automotive industry

Abstract: ABSTRACT

Cited by 6 publications

References 22 publications

Logística reversa e sustentabilidade; Modelo de gestão para logística reversa e sua aplicação em produtos eletronicos da linha branca

Logística reversa e sustentabilidade; Modelo de gestão para logística reversa e sua aplicação em produtos eletronicos da linha branca

Assessing the transition from mass production to lean manufacturing using a hybrid simulation model of a LEGO® automotive assembly line

A simulation analysis of the vehicle axle and spring assembly lines

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