The order and volume fill rates in inventory control systems

Larsen, Christian; Thorstenson, Anders

doi:10.1016/j.ijpe.2012.07.021

Cited by 32 publications

(16 citation statements)

References 17 publications

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“…Based on the same demand distribution, Larsen and Thorstenson [23] consider a continuous review base stock policy and demonstrate the use of a computer program to obtain the base stock level needed to achieve the specified order fill rate (OFR) and volume fill rate (VFR), respectively. Moreover, the respective performances of the OFR and VFR Mathematical Problems in Engineering 3 for different inventory control systems are compared (Larsen and Thorstenson [24]). With demand arrivals following the Erlang distribution, in conjunction with a Gamma distribution for demand size, Saidane et al [25,26] propose an algorithm to determine the optimal base stock level under a costoriented continuous review inventory system and conduct numerical investigations to compare the performance of this model in cost reduction with that of the compound Poisson distribution and the classic Newsvendor model, respectively.…”

Section: Research Backgroundmentioning

confidence: 99%

Determining the Optimal Order Quantity with Compound Erlang Demand under (T,Q) Policy

Jiang

Tam

Bao

et al. 2018

Mathematical Problems in Engineering

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Management of electric equipment has a direct impact on companies' performance and profitability. Considering the critical role that electric power materials play in supporting maintenance operations and preventing equipment failure, it is essential to maintain an inventory to a reasonable level. However, a majority of these electric power materials exhibit an intermittent demand pattern characterized by random arrivals interspersed with time periods with no demand at all. These characteristics cause additional difficulty for companies in managing these electric power material inventories. In response to the above problem, this paper, based on the electric power material demand data of Shanghai Electric Power Company, develops a new method to determine the optimal order quantity * in a cost-oriented periodic review ( , ) system, whereby unsatisfied demands are backordered and demand follows a compound Erlang distribution.* corresponds to the value of that gives the minimum expected total inventory holding and backordering cost. Subsequently, an empirical investigation is conducted to compare this method with the Newsvendor model. Results verify its superiority in cost savings. Ultimately, considering the complicated calculation and low efficiency of that algorithm, this paper proposes an approximation and a heuristic algorithm which have a higher level of utility in a real industrial context. The approximation algorithm simplifies the calculation process by reducing iterative times while the heuristic algorithm achieves it by generalizing the relationship between the optimal order quantity * and mean demand interarrival rate .

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Section: Research Backgroundmentioning

confidence: 99%

Determining the Optimal Order Quantity with Compound Erlang Demand under (T,Q) Policy

Jiang

Tam

Bao

et al. 2018

Mathematical Problems in Engineering

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“…Para este entendimento, várias pesquisas têm sido desenvolvidas com a construção de modelos que elucidam quantidades econômicas, estoques de segurança (ver BRAGLIA;GABBRIELLI;ZAMMORI, 2013;ESMAEILIKIA et al, 2014), efeitos da variabilidade, (ver WANG;DISNEY, 2016;YANG;ZHANG, 2015), taxas de desempenhos e custos relacionados (ver BIJVANK;VIS, 2011;CARDOSO et al, 2014;LARSEN;THORSTENSON, 2014), efeitos da obsolescência dos estoques (ver PINÇE; DEKKER, 2011), entre outras diversas pesquisas.…”

Section: Gerenciamento De Estoquesunclassified

“…Outras pesquisas visam minimizar os efeitos de variabilidade provocada pela instabilidade da demanda e das entregas (WANG;DISNEY, 2016;YANG;ZHANG, 2015). Outras linhas demonstram as taxas de desempenho dos estoques e a relação entre os custos gerados pela falta de produto e os custos decorrentes para garantir a disponibilidade de produto (BIJVANK;VIS, 2011;CARDOSO et al, 2014;LARSEN;THORSTENSON, 2014), sendo que o gerenciamento inadequado das taxas de desempenho pode motivar a obsolescência de produtos e o aumento dos custos operacionais (PINÇE;DEKKER, 2011). Ainda, é possível constatar um grande esforço dos pesquisadores na busca de mecanismos que possam minimizar os custos envolvidos com estoques e facilitar a tomada de decisão, por exemplo, os estudos de (FLEISCHHACKER;FOK, 2015;LEE;CHO;PAIK, 2016;PICK;DIESEL;SELLITTO, 2011;PONTES;PALMA;PORTO, 2008).…”

Section: Introductionunclassified

Análise integrada para a tomada de decisão: os efeitos da modelagem no gerenciamento de estoques e o impacto sobre o indicador de rentabilidade ROI

Vargas

Baccin

Sellitto

2017

Revista PO: R. Eletr. de Eng. de Produção e Correlatas

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Universidade do Vale do Rio dos Sinos (UNISINOS), São Leopoldo, RS.Resumo: O adequado gerenciamento de estoques pode auxiliar a minimizar os efeitos de variabilidade e custos operacionais, assim como melhorar os níveis de serviço e a rentabilidade das empresas. Neste sentido, o objetivo deste artigo é integrar a modelagem sobre gerenciamento de estoques e seu impacto sobre o indicador de rentabilidade ROI. Foram modelados quatro cenários e aplicados em um caso no gerenciamento de estoques de matéria-prima, aplicado em uma empresa metal mecânica no estado do Rio Grande do Sul. Os resultados modelados foram usados para comparar e analisar os impactos gerados sobre o indicador de rentabilidade da empresa. O método de pesquisa foi a modelagem quantitativa. Os resultados indicam possibilidade de redução do custo total de operação, redução dos volumes e valores em inventário e aumento do giro de estoques. Além disso, os impactos das modelagens demonstram a possibilidade de aumento no ROI em até 58,5% no curto prazo. A análise integrada pode auxiliar na compreensão da importância do gerenciamento adequado dos estoques.Palavras-chave: Gerenciamento de Estoques. Modelagem. Retorno sobre o investimento. Matéria-prima.Abstract: A suitable stock management can help minimize the effects of variability and operational costs, as well as improve service levels and profitability. In this sense, the purpose of this article is to integrate modeling on inventory management and its impact on the profitability indicator ROI. Four scenarios were modeled and applied in a case regarding the inventory management of raw material, applied in a metalworking company in the state of Rio Grande do Sul. The modeled results were used to identifying, comparing and analyzing impacts generated on the company's profitability indicator. The research method was the quantitative modeling. The results indicate the possibility of reducing the total cost of operation, reduction of the quantity and values in inventory and inventory turnover increase. In addition, the impacts of modeling demonstrated the possibility of increase ROI by up to 58.5% in the short term. The integrated analysis can assist in the understanding of the importance of suitable stocks management. O desenvolvimento de modelos pode auxiliar na compreensão do ambiente em estudo e seus problemas, visando a sistematização e formulação de estratégias que auxiliam na tomada de decisão (MIGUEL et al., 2012). Esta pesquisa utiliza do método de modelagem, aplicado em uma empresa metal mecânica no estado do Rio Grande do Sul. O melhor resultado modelado com possibilidade de aplicação a curto prazo (Modelagem 1), possibilita a redução no custo total de operação, volumes e valor em inventário de matéria-prima em 22,8%, 22% e 33,6%; aumento no giro dos estoques em 28,2% e um Fill Rate de 99,4%; gerando aumento do ROI em 58,5%.Isso representa a possibilidade de aumento da margem de lucro em 46,4% e turnover dos ativos em 8,3%. Estes valores de otimização no gerenciamento dos estoques correspondem dir...

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“…This is sometimes referred to as item fill rate, volume fill rate, unit fill rate, or the immediate fill rate (Guijarro Tarradellas, Cardós and Babiloni, 2012). It is different to the order fill rate, which applies to the proportion of fulfilled customer orders that may consist of multiple products (Larsen and Thorstenson, 2014). Schneider (1981), Johnson et al (1995), Silver and Bischak (2011) and Guijarro Tarradellas, Cardós and Babiloni (2012) provide literature reviews of the fill rate.…”

Section: Literature Reviewmentioning

confidence: 99%

Fill rate in a periodic review order-up-to policy under auto-correlated normally distributed, possibly negative, demand

Disney

Gaalman

Hedenstierna

et al. 2015

International Journal of Production Economics

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We investigate the inventory service metric known as the fill rate-the proportion of demand that is immediately fulfilled from inventory. The task of finding analytical solutions for general cases is complicated by a range of factors including; correlation in demand, double counting of backlogs, and proper treatment of negative demand. In the literature, two approximate approaches are often proposed. Our contribution is to present a new fill rate measure for normally distributed, autocorrelated, and possibly negative demand. We treat negative demand as returns. Our approach also accounts for accumulated backlogs. The problem reduces to identifying the minimum of correlated normally distributed bivariate random variables. There exists an exact solution, but it has no closed form. However, the solution is amenable to numerical techniques, and we present a custom Microsoft Excel function for practical use. Numerical investigations reveal that the new fill rate is more robust than previous measures. Existing fill rate measures are likely to cause excessive inventory investment, especially when fill rate targets are modest, a strongly positive or negative autocorrelation in demand is present, or negative demands exist. Our fill rate calculation ensures that the target fill rate is achieved without excessive inventory investments.

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The order and volume fill rates in inventory control systems

Cited by 32 publications

References 17 publications

Determining the Optimal Order Quantity with Compound Erlang Demand under (T,Q) Policy

Determining the Optimal Order Quantity with Compound Erlang Demand under (T,Q) Policy

Análise integrada para a tomada de decisão: os efeitos da modelagem no gerenciamento de estoques e o impacto sobre o indicador de rentabilidade ROI

Fill rate in a periodic review order-up-to policy under auto-correlated normally distributed, possibly negative, demand

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