A Maclaurin-series expansion approach to coupled queues with phase-type distributed service times

International audienc

Coupled queues with customer impatience

Motivated by assembly processes, we consider a Markovian queueing system with multiple coupled queues and customer impatience. Coupling means that departures from all constituent queues are synchronised and that service is interrupted whenever any of the queues is empty and only resumes when all queues are non-empty again. Even under Markovian assumptions, the state space grows exponentially with the number of queues involved. To cope with this inherent state space explosion problem, we investigate performance by means of two numerical approximation techniques based on series expansions, as well as by deriving the fluid limit. In addition, we provide closed-form expressions for the first terms in the series expansion of the mean queue content for the symmetric coupled queueing system. By an extensive set of numerical experiments, we show that the approximation methods complement each other, each one being accurate in a particular subset of the parameter space. (C) 2017 Elsevier B.V. All rights reserved

Stochastic modelling of energy harvesting for low power sensor nodes

Battery lifetime is a key impediment to long-lasting low power sensor nodes. Energy or power harvesting mitigates the ependency on battery power, by converting ambient energy into electrical energy. This energy can then be used by the device for data collection and transmission. This paper proposes and analyses a queueing model to assess performance of such an energy harvesting sensor node. Accounting for energy harvesting, data collection and data transmission opportunities, the sensor node is modelled as a paired queueing system. The system has two queues, one representing accumulated energy and the other being the data queue. By means of some numerical examples, we investigate the energy-information trade-off

Strength and water absorption rate of concrete made from palm oil fuel ash

Concrete is one of the most important materials for construction industry. The material in the mixture of concrete includes cement, sand and coarse aggregate. Production of cement causes the air pollution from the emission of carbon dioxide to the air. This research studies the replacement of cement with palm oil fuel ash (POFA) in the concrete mixture. The objective of this research is to investigate the compressive strength of concrete and water absorption rate of concrete made from POFA and to compare the strength and absorption rate between conventional concrete and concrete made from POFA. This is to indicate whether the compressive strength and absorption rate are equivalent to the strength of conventional concrete. The methodology used in this research is experimental method and the palm oil fuel ash was taken from palm oil mill in Cha’ah, Johor, Malaysia. The results of this research are the specimens which contain 20% POFA has a compressive strength and water absorption rate comparable to conventional concrete

Simulation study on electrical resistance tomography using metal wall for bubble detection

Industrial process pipelines are mostly known to be constructed from metal which is a conducting material. Bubbles or gas detection are crucial in facilitating the bubble columns performance. By employing the Electrical Resistance Tomography (ERT) technique, a simulation study using COMSOL has been conducted to investigate the effect of excitation strategy, bubble sizes and locations towards the metal wall system. As for the current excitation strategy, conducting boundary protocol has to be applied when it comes to metallic vessel to overcome the grounding effect. Bubbles with a greater size than 2 mm and especially the one that is located near the wall boundary are much easier to detect. Further potential improvements to the current design and image reconstruction of the ERT system are desirable to improve the detection of small and centred bubble

Strength and water absorption rate of concrete made from palm oil fuel ash

Concrete is one of the most important materials for construction industry. The material in the mixture of concrete includes cement, sand and coarse aggregate. Production of cement causes the air pollution from the emission of carbon dioxide to the air. This research studies the replacement of cement with palm oil fuel ash (POFA) in the concrete mixture. The objective of this research is to investigate the compressive strength of concrete and water absorption rate of concrete made from POFA and to compare the strength and absorption rate between conventional concrete and concrete made from POFA. This is to indicate whether the compressive strength and absorption rate are equivalent to the strength of conventional concrete. The methodology used in this research is experimental method and the palm oil fuel ash was taken from palm oil mill in Cha’ah, Johor, Malaysia. The results of this research are the specimens which contain 20% POFA has a compressive strength and water absorption rate comparable to conventional concrete

Production planning in different stages of a manufacturing supply chain under multiple uncertainties

This thesis focuses on designing stochastic programming models for production planning at different stages in a manufacturing supply chain under multiple sources of uncertainties. Various decision makers along the manufacturing supply chain often have to make planning decisions with embedded risks and uncertainties. In an effort to reduce risks and to ensure that the customer demand is met in the most efficient and cost effective way, the production plans at each stage need to be strategically planned. To assist production planning decisions, a two-stage stochastic programming model is developed with the objective of minimizing the total cost including production, inventory, and backorder costs. The proposed framework is validated with case studies in an automobile part manufacturer with real data based on literature. The results demonstrate the robustness of the stochastic model compared with various deterministic models. Sensitivity analysis is performed for the production capacity parameter to derive managerial insights regarding lot-sizing and scheduling decisions under different scenarios