Design of practical optimum JIT systems by integration of computer simulation and analysis of variance

Azadeh, A.; Bidokhti, B.; Sakkaki, S. M. R.

doi:10.1016/j.cie.2005.03.005

Cited by 20 publications

(13 citation statements)

References 37 publications

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“…Since design and implementation of theoretical JIT philosophy may not be possible for most dynamic systems due to their unique limitations and constrains, a more applicable JIT design approach which is compatible with the limitations of the dynamic system is called practical JIT (Azadeh et al 2005). This paper extends the previous study by Azadeh et al (2005) and considers the practical JIT simulation developed in Azadeh et al (2005) as a case study. Therefore, the hybrid GA-simulation approach is the major significance of this study in particular and JIT modelling in general.…”

Section: Introductionmentioning

confidence: 92%

Section: The Practical Jit Designmentioning

confidence: 99%

“…The daily production plan is 234 front doors. The daily available time and down time are 44,000 and 8200 seconds, respectively (Azadeh et al 2005). At this stage, an ANOVA is conducted to evaluate the effects of the practical JIT system (Montgomery 1984, Yang et al 2007a, Farahani and Elahipanah 2008, Sandanayake et al 2008.…”

Section: The Practical Jit Designmentioning

confidence: 99%

“…Since this paper considers the practical JIT simulation developed in Azadeh et al (2005) as a case study, Section 2, is an overview of Azadeh et al (2005), which includes the framework of the practical JIT system for the production line which the proposed hybrid GA-simulation approach is applied to. In Section 3, the methodology of the implemented hybrid GA-simulation approach is explained.…”

Section: Introductionmentioning

confidence: 99%

“…The defects generated by the system could not be dismissed and a practical JIT design must consider this phenomenon. Random breakdowns are a part of the production line and it therefore should be a feature of the practical optimum JIT design (Azadeh et al 2005).…”

Section: Introductionmentioning

confidence: 99%

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A hybrid GA-simulation approach to improve JIT systems

Azadeh

Ebrahimipour

Bavar

2009

International Journal of Production Research

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This study presents a hybrid approach involving genetic algorithms (GAs) as an optimisation search technique and a simulation model, representing the dynamic behaviour of a system and its limitations, to improve an existing just-in-time (JIT) manufacturing system. To achieve the objective, first, the existing system is modelled and simulated (by considering the system's limitations and its dynamic behaviour). Second, the integrated simulation model is tested and validated by analysis of variance. Third, the hybrid GA-simulation approach is used in an interactive manner to determine the optimal/near-optimal number of kanban cards in different stations of the existing JIT system. The presented hybrid approach is tested and applied to an auto industry production line. Furthermore, it is compared with the practical JIT through analysis of variance (ANOVA) and the results show improvements in the average daily production rate, the average resource utilisation and the average cycle time but some deterioration in the average queue length and in-process inventory is inevitable.

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Section: Introductionmentioning

confidence: 92%

Section: The Practical Jit Designmentioning

confidence: 99%