Using Markov Chain to Analyze Production Lines Systems with Layout Constraints

There are some problems with estimating the time required for the manufacturing process of products, especially when there is a variable serving time, like control stage. These problems will cause overestimation of process time. Layout constraints, reworking constraints and inflexible product schedule in multi product lines need a precise planning to reduce volume in particular situation of line stock. In this article, a hybrid model has been presented by analyzing real queue systems with layout constraints as well as by using concepts and principles of Markov chain in queue theory. This model can serve as benchmark to assess queue systems with probable parameters of service. Here, the proposed model will be described drawing on the findings of a case study. Thus, production lines of a home application manufacturer will be analyzed

Approximate regenerative-block bootstrap for Markov chains

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Approximate regenerative-block bootstrap for Markov chains: some simulation studies

In [7], a novel methodology for bootstrapping general Harris Markov chains has been developed, the (approximate) regenerative block-bootstrap. It is built on the renewal properties of the chain (or of a Nummelin extension of the latter) and has theoretical properties that surpass other existing methods within the Markovian framework. This paper is devoted to discuss practical issues related to the implementation of this specific resampling method and to present various simulation studies for investigating its performance and comparing it to other bootstrap resampling schemes, standing as natural candidates in the Markov setting