Optimal Safety Stock Policy for a Hybrid Manufacturing System: A Simulation Study

Horng, Horng-Chyi

doi:10.1007/978-3-319-00557-7_24

Cited by 2 publications

(2 citation statements)

References 17 publications

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“…The different methods were evaluated using DES in Python. A real factory working with mixed MTO, MTS and ATO strategies was considered in the study by Horng (2013). The author developed a simulation model for the combined manufacturing system, to assess different safety stock policies and performance.…”

Section: Simulation In Combined Production Strategiesmentioning

confidence: 99%

Hybrid modelling of MTO/ETO manufacturing environments for performance assessment

Barbosa

Azevedo

2018

International Journal of Production Research

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Performance assessment is critical in today's competitive environments, where companies need to establish trade-offs between key competitive dimensions. The complexity of these environments calls for new approaches to performance assessment. Thus, in this work, we propose a novel conceptual framework for performance assessment in manufacturing environments combining different production strategies. Focus is laid on MTO/ETO combined environments and a threestage problem analysis is considered. Firstly, a hybrid SD-DES-ABS model approach addresses the needs of a system that handles different types of orders, processes and workforce allocation requirements; secondly, the model results for different demand scenarios are assessed using a one-way ANOVA analysis followed by a Tukey-Kramer's test, with pairwise comparisons for assessment of significant performance variations under different system operating policies. A full factorial Design of Experiments (DOE) analysis follows, for determining the relevant process parameters influencing the system performance. As an example of application of the proposed framework, we consider the case of an advanced manufacturing company, whose manufacturing environment encompasses combined MTO/ETO production strategies.

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Section: Simulation In Combined Production Strategiesmentioning

confidence: 99%

Hybrid modelling of MTO/ETO manufacturing environments for performance assessment

Barbosa

Azevedo

2018

International Journal of Production Research

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“…They concluded that each approach has its own strengths under particular conditions, and they recommended developing a dynamic approach for calculating SSs. Additionally, under stationary demand, Horng (2013) developed a simulation model to optimize safety stock levels for a hybrid manufacturing system by adopting both make-to-order and make-to-stock strategies. The main finding of their work was that strong links exist between the review and release rules of orders, the performance of the system and the needed SSs.…”

Section: Introductionmentioning

confidence: 99%

Determination of dynamic safety stocks for cyclic production schedules

Bahroun

Belgacem

2019

Oper Manag Res

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Safety stocks are necessary to accommodate supply or demand uncertainties. Typically, safety stocks are held constant throughout the management horizon. In this paper, we study the determination of dynamic safety stock levels under cyclic production schedules. Currently, companies often operate according to contract orders with fixed and cyclic delivery dates and varying quantities. In this context, companies have attempted to implement cyclic production modes for their cyclic delivery requirements. Indeed, cyclic production scheduling has many benefits, such as respecting just-in-time principles by synchronising production with demand and improving shop floor control. The objectives of this paper are twofold: (1) to propose a new dynamic approach for determining safety stock levels that is adapted to cyclic production and (2) to demonstrate the limitations of traditional approaches under nonstationary demands. Our dynamic approach is based on modelling a repetitive production sequence comprising many manufacturing orders. Our model estimates the dynamic safety stock levels necessary to accommodate cyclic manufacturing orders with uncertain quantities and start dates using a Monte Carlo simulation approach. For the case in which all demands follow normal probability distributions, we validated the results of our simulation model by comparing them to numerically approximated theoretical results. We then compared the proposed dynamic simulation approach with the traditional approach. The results demonstrate that the dynamic approach is more efficient in terms of simultaneously minimizing the required safety stocks and improving the service level by decreasing the probability of stock outs. Finally, we applied our simulation approach to a case in which all demands follow uniform probability distributions.

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Optimal Safety Stock Policy for a Hybrid Manufacturing System: A Simulation Study

Cited by 2 publications

References 17 publications

Hybrid modelling of MTO/ETO manufacturing environments for performance assessment

Hybrid modelling of MTO/ETO manufacturing environments for performance assessment

Determination of dynamic safety stocks for cyclic production schedules

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