Optimization of a Product Batch Quantity

Berlec, Tomaž; Kušar, Janez; Žerovnik, Janez; Starbek, Marko

doi:10.5545/sv-jme.2013.1009

Cited by 12 publications

(9 citation statements)

References 5 publications

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“…The Lean system has become even a reference model for optimizing production and general performance of larger companies as well as SMEs (Lyonnet et al, 2010;Powell at al., 2013;Belekoukias et al, 2014). Therefore some research works focus in simulation of production processes as well as in material flow and batch quantity optimization (Bozickovic et al 2012;Dordevic et al, 2013;Berlec et al, 2014). Any overproduction, as well as any excess stock is considered to be a source of waste (Ohno, 1988;Womack and Jones, 2003;Drew et al, 2004) and only producing what is really needed by the customer is one of the major principles of Lean Manufacturing.…”

Section: Introductionmentioning

confidence: 98%

Production line balancing with discrete event simulation: A case study

Zupan

Herakovič

2015

IFAC-PapersOnLine

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In this paper we present the case study for the optimization of the production line by using the balancing and discrete event simulation approach. First the basic theory and steps for the production line balancing are presented. For the real production process, consisting of two production lines and an assembly workplace the simulation model is built and the initial results obtained. After balancing of the production process and improvement of its performance some further steps of the process optimization by using the improved simulation model are performed. The results of the combination of the line balancing and further process optimization raise the production rate of the process enormously, which is obvious from the research results of this paper.

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Section: Introductionmentioning

confidence: 98%

Production line balancing with discrete event simulation: A case study

Zupan

Herakovič

2015

IFAC-PapersOnLine

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“…PBC approach to production planning is different from other planning approaches since it focuses more on time factor (period length) than on some other factor which influences manufacturing lead time, like the batch size for instance which is seen in [25]. Having in sight the PBC system, which is on the same level as the MRP system in the production planning and control hierarchy, it would be interesting to investigate the periodical planning of virtual manufacturing cells with the PBC principles and rules applied.…”

Section: Period Batch Controlmentioning

confidence: 99%

Period Batch Control - A Production Planning System Applied to Virtual Manufacturing Cells

Tešić¹,

Stevanov²,

Jovanović³

2016

Int. j. simul. model.

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Period Batch Control (PBC) system has been known for its implementation with the classical group technology (GT) cells, and it has been known for its simplicity. The main production planning decisions concern the choice of the period length and the stage number and contents. Also, in order to better integrate the production planning with the application of GT cells at the shop floor, the concept of virtual manufacturing cells has been applied. Since virtual cells configurations are changing periodically, a model for implementing the PBC system into virtual manufacturing cells environment is developed. The model enables alignment of the PBC principles and rules with virtual cell design goals. Model is tested on the case study of furniture production. With the use of scheduling software, different scheduling rules were simulated for four production weeks. The experimental results from these for production weeks show how the choice of PBC parameters impacts the virtual cells configurations, machine sharing and utilization.

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“…Berlec et al [21] study the calculation of optimal batch quantity using first the basic model, and then the extended model taking into account the tied-up capital in a production, in addition to the costs of changing the batch and storage costs. They implement the study for a case to find out when either of the two models should be used.…”

Section: Literature Reviewmentioning

confidence: 99%

Simulation Analysis of Shuttle Based Storage and Retrieval Systems

Lerher¹,

Ekren²,

Sari³

2015

Int. j. simul. model.

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In this paper, a simulation-based performance evaluation of shuttle-based storage and retrieval system (SBS/RS) is presented. In comparison with well-known automated storage and retrieval systems, SBS/RSs can substantially increase the throughput capacity of the system. The objective of this study is to exploit the benefits of SBS/RS system design for reducing the mean cycle time of transactions and consequently increasing the throughput capacity of the system. Performance comparison of the studied SBS/RS is contrasted with alternative storage rack configurations, velocity profiles of the shuttle carriers and velocity profiles of the elevators' lifting tables in the system. The results show that SBS/RSs are effective in reducing the mean cycle time and also show large improvement by increasing throughput capacity.

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Optimization of a Product Batch Quantity

Cited by 12 publications

References 5 publications

Production line balancing with discrete event simulation: A case study

Production line balancing with discrete event simulation: A case study

Period Batch Control - A Production Planning System Applied to Virtual Manufacturing Cells

Simulation Analysis of Shuttle Based Storage and Retrieval Systems

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