Optimal allocation of resources in a job shop environment

Seshadri, Sridhar; Pinedo, Michael

doi:10.1080/07408179908969820

Cited by 6 publications

(4 citation statements)

References 25 publications

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“…The queueing network studied in Seshadri and Pinedo [28] captures the effects of productivity loss through service rate reductions and downtime by allowing the work per unit time to depend on an efficiency factor. The queueing models most closely related to ours are those of Koyanagi and Kawai [17] and Yao, in Chapter 3 of [42].…”

Section: Traditional Maintenance Control Models Include What Vanmentioning

confidence: 99%

Machine maintenance with workload considerations

Kaufman

Lewis

2007

Naval Research Logistics

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Abstract:Machine maintenance is modeled in the setting of a single-server queue. Machine deterioration corresponds to slower service rates and failure. This leads to higher congestion and an increase in customer holding costs. The decision-maker decides when to perform maintenance, which may be done pre-emptively; before catastrophic failures. Similar to classic maintenance control models, the information available to the decision-maker includes the state of the server. Unlike classic models, the information also includes the number of customers in queue. Considered are both a repair model and a replacement model. In the repair model, with random replacement times, fixed costs are assumed to be constant in the server state. In the replacement model, both constant and variable fixed costs are considered. It is shown in general that the optimal maintenance policies have switching curve structure that is monotone in the server state. However, the switching curve policies for the repair model are not always monotone in the number of customers in the queue. Numerical examples and two heuristics are also presented.

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Section: Traditional Maintenance Control Models Include What Vanmentioning

confidence: 99%

Machine maintenance with workload considerations

Kaufman

Lewis

2007

Naval Research Logistics

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“…For a general open queueing network, Giloni, 2001 [12] derives conditions under which the problem is reduced to solving a concave or convex problem. Additionally, Seshadri & Pinedo, 1999 [27] exploit an approach where a heuristic is used to minimize the WIP level. Lastly, Yoneda et al, 1992 [39] apply simulated annealing to optimize their system.…”

Section: Introductionmentioning

confidence: 99%

Staff optimization for time-dependent acute patient flow

Andersen

Nielsen

Reinhardt

et al. 2019

European Journal of Operational Research

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“…Estes problemas já foram objeto de diversos estudos anteriores em sistemas job-shops, por exemplo, em Bitran & Tirupati (1989), Boxma et al (1990), Van Vliet & Rinnooy Kan (1991), Bitran & Sarkar (1994a), Bitran & Morabito (1995, 1996 e Silva & Morabito (2007). Outros estudos relacionados aparecem em Calabrese (1992), Frenk et al (1994), Sundarraj et al (1994), Bretthauer (1996), Seshadri & Pinedo (1999), Shanthikumar & Xu (2000), …”

Section: Introductionunclassified

Análise de problemas de partição de instalações em sistemas job-shops por meio de modelos de redes de filas

Silva

Morábito

2007

Pesqui. Oper.

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ResumoEste artigo estuda o problema de projeto de fábrica focalizada envolvendo a partição da instalação (planta) em subplantas e a alocação de capacidade em cada estação de trabalho das subplantas. O sistema de manufatura job-shop é representado por meio de uma rede de filas aberta genérica, e aproximações b aseadas em métodos de decomposição são utilizadas para avaliar e otimizar o desempenho do sistema. O objetivo é reduzir a complexidade do sistema do ponto de vista da gestão do produto ou da gestão da estação, por exemplo, limitando-se a variância dos leadtimes dos produtos na rede. Apresenta-se um modelo de programação não-linear inteira para o problema e um algoritmo heurístico para resolvê-lo. Aplicando-se o algoritmo em alguns problemas testes, mostra-se que a partição da instalação em subplantas pode reduzir a variância dos leadtimes dos produtos na rede, sem necessidade de investimentos adicionais em capacidade. Além disso, algumas vezes é possível manter (ou até melhorar) o desempenho da rede, particionando-a em subplantas que necessitam de menos capacidade do que a configuração original da rede como uma planta única.Palavras-chave: partição da instalação; fábrica focalizada; projeto de job-shops; redes de filas abertas; alocação de capacidade; métodos de avaliação de desempenho. AbstractThis paper studies the focused factory design involving the partition of the facility (plant) into sub-plants and the allocation of capacity in each workstation of the sub-plants. The job-shop system is represented by a generic open queuing network and approximations based on decomposition methods are used to evaluate and optimize the performance of the system. The aim is to reduce the system complexity from the point of view of the product or workstation management, for example, limiting the variance of the product leadtimes in the network. An integer non-linear programming model and a heuristic algorithm are presented. Applying the algorithm to some testing problems, it is shown that the partition of the facility into sub-plants can reduce the variance of the product leadtimes without requiring additional investments of capacity. Moreover, sometimes it is possible to maintain (or even improve) the network performance by partitioning the plant into sub-plants which need less capacity than the original plant.

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Optimal allocation of resources in a job shop environment

Cited by 6 publications

References 25 publications

Machine maintenance with workload considerations

Machine maintenance with workload considerations

Staff optimization for time-dependent acute patient flow

Análise de problemas de partição de instalações em sistemas job-shops por meio de modelos de redes de filas

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