Analysis of multi-product manufacturing systems with arbitrary processing times

Kang, Ningxuan; Zheng, Liang; Li, Jingshan

doi:10.1080/00207543.2014.952363

Cited by 14 publications

(4 citation statements)

References 10 publications

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“…They also investigate the robustness of the policies and provide practical guidance for operation management. Paper [27] further extends the work to machines with arbitrary processing times.…”

Section: Literature Reviewmentioning

confidence: 99%

Scheduling policies in flexible Bernoulli lines with dedicated finite buffers

Park

Feng

2018

Journal of Manufacturing Systems

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This paper is devoted to studying scheduling policies in flexible serial lines with two Bernoulli machines and dedicated finite buffers. Priority, cyclic and work-in-process (WIP)-based scheduling policies are investigated. For small scale systems, exact solutions are derived using Markov chain models. For larger ones, a flexible line is decomposed into multiple interacting dedicated serial lines, and iteration procedures are introduced to approximate system production rate. Through extensive numerical experiments, it is shown that the approximation methods result in acceptable accuracy in throughput estimation. In addition, system-theoretic properties such as asymptotic behavior, reversibility, and monotonicity, as well as impact of buffer capacities are discussed, and comparisons of the scheduling policies are carried out.

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Section: Literature Reviewmentioning

confidence: 99%

Scheduling policies in flexible Bernoulli lines with dedicated finite buffers

Park

Feng

2018

Journal of Manufacturing Systems

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“…The generalized stochastic Petri net was applied to construct the model and the isomorphic Markov chain was used to make the quantitative analysis of the model proposed (Zhang et al, 2012). Kang et al (2015) constructed an embedded Markov chain model to evaluate the performance of multi-product systems with arbitrary processing times. To minimization the cost of printer cartridge industry, Francie et al (2015)using the nonhomogeneous Markov process to describe the dynamics of the overall production system.…”

Section: Literature Reviewmentioning

confidence: 99%

Reassembly classification selection method based on the Markov Chain

Liu

et al. 2018

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Purpose As the last link of product remanufacturing, reassembly process is of great importance in increasing the utilization of remanufactured parts as well as decreasing the production cost for remanufacturing enterprises. It is a common problem that a large amount of remanufactured part/reused part which past the dimension standard have been scrapped, which have increased the production cost of remanufacturing enterprises to a large extent. With the aim to improve the utilization of remanufacturing parts with qualified quality attributes but exceed dimension, the purpose of this paper is to put forward a reassembly classification selection method based on the Markov Chain. Design/methodology/approach To begin with, a classification standard of reassembly parts is proposed. With the thinking of traditional ABC analysis, a classification management method of reassembly parts for remanufactured engine is proposed. Then, a homogeneous Markov Chain of reassembly process is built after grading the matching dimension of reassembly parts with different variety. And the reassembly parts selection model is constructed based on the Markov Chain. Besides, the reassembly classification selection model and its flow chart are proposed by combining the researches above. Finally, the assembly process of remanufactured crankshaft is adopted as a representative example for illustrating the feasibility and the effectiveness of the method proposed. Findings The reassembly classification selection method based on the Markov Chain is an effective method in improving the utilization of remanufacturing parts/reused parts. The average utilization of remanufactured crankcase has increased from 35.7 to 80.1 per cent and the average utilization of reused crankcase has increased from 4.2 to 14 per cent as shown in the representative example. Originality/value The reassembly classification selection method based on the Markov Chain is of great importance in enhancing the economic benefit for remanufacturing enterprises by improving the utilization of remanufactured parts/reused parts.

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“…For short Markovian flow lines, both exact mathematical models [1,5,[27][28][29] and closed-form formulas [3,12,26,30,31] exist.…”

Section: Current Evaluative Models Of Flow Linesmentioning

confidence: 99%

“…However, the variable e TR needs to be obtained using simulations so the formula cannot be applied on its own for performance analysis. Recent work [3,30] presents an interesting Markov chain-based analytical model to obtain e TR for short service-based flow lines with non-exponential processing times.…”

Section: Current Evaluative Models Of Flow Linesmentioning

confidence: 99%