Energy-efficient buffer allocation problem in unreliable production lines

Alaouchiche, Yasmine; Ouazène, Yassine; Yalaoui, Farouk

doi:10.1007/s00170-021-06971-1

Cited by 13 publications

(6 citation statements)

References 32 publications

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“…By adjusting the interarrival time of orders and the input buffer size to the capacity of the bottleneck, the production system is well balanced, and the throughput of the production system is maximized. The opposite strategy is to add work-in-flow buffers between machines in a production system to maximize throughput and to protect machines from the consequences of failures and blocking [51,52]. According to the Theory of Constraints, the throughput of a production lines is equal to the capacity of the bottleneck.…”

Section: Comparative Discussion On Energy-saving Methodsmentioning

confidence: 99%

“…The analyzed literature ignores the impact of work-in-process buffers on the energy consumption. The advantage of methods for finding the best buffer allocation and optimizing both the throughput and energy consumption for serial production lines is the assumption that the machines are unreliable [51,52]. In particular, bottleneck downtime is crucial to the performance of production systems, upstream and downstream machine run times are shorter than cycle times, and work-in-process buffers may not be necessary.…”

Section: Comparative Discussion On Energy-saving Methodsmentioning

confidence: 99%

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A Discrete-Time Queueing Model of a Bottleneck with an Energy-Saving Mechanism Based on Setup and Shutdown Times

Kempa,

Paprocka

2024

Symmetry

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Producers are encouraged to reduce their energy consumption of manufacturing systems by applying less-energy-intensive modern technologies and advanced machine tools and operating methods at the system level. In the paper, organizational and analytical solutions are combined to model the sustainable production system. Managers can study the behavior of a production system organized using energy-saving rules by changing key parameters of the input model (arrival intensity, bottleneck service rate, buffer size, setup and shutdown time) to analyze the queue size of the production system and therefore performance. A discrete-time queueing model of a single-bottleneck production line with a finite input buffer capacity is proposed. Jobs occur according to a binomial process and are processed individually, one by one, according to the natural FIFO service discipline, with a general discrete-type cumulative distribution function. The total number of jobs present in the system is bounded by a non-random fixed value N. Every time the system becomes empty, an energy-saving mechanism is started: the processing machine (server) is turned off during a geometrically distributed shutdown time. Similarly, the first job arriving into the empty system initializes a geometrically distributed setup time. Identifying renewal moments in the evolution of the model, a system of difference equations is built for the transient queue-size distribution conditioned by the state of the system at the opening. The solution is obtained explicitly in terms of probability-generating functions. In addition, the Drum-Buffer-Rope concept is proposed to reduce the energy consumption of the production line. The throughput of the production system is maximized by adjusting the time between the order arrivals and the size of the input buffer to the capacity of the bottleneck. Turning off a machine under certain conditions and slowing down non-critical machines are strategies to reduce energy consumption. A detailed illustrating numerical and simulation study of the considered model is attached as well, in which the sensitivity of the queue-size behavior to changes of the key input model parameters is investigated.

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Section: Comparative Discussion On Energy-saving Methodsmentioning

confidence: 99%

Section: Comparative Discussion On Energy-saving Methodsmentioning

confidence: 99%

A Discrete-Time Queueing Model of a Bottleneck with an Energy-Saving Mechanism Based on Setup and Shutdown Times

Kempa,

Paprocka

2024

Symmetry

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“…It is necessary to find optimal combinations for the efficient management of scarce resources, which is why optimization methods are useful and have been applied in a number of fields among which include Manufacturing [2,3], Engineering [4,5] and Education [6,7].…”

Section: Related Workmentioning

confidence: 99%

A Meta-Heuristic Search Algorithm based on Infrasonic Mating Displays in Peafowls

Kenekayoro

2021

JAMCS

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Meta-heuristic techniques are important as they are used to find solutions to computationally intractable problems. Simplistic methods such as exhaustive search become computationally expensive and unreliable as the solution space for search algorithms increase. As no method is guaranteed to perform better than all others in all classes of optimization search problems, there is a need to constantly find new and/or adapt old search algorithms. This research proposes an Infrasonic Search Algorithm, inspired from the Gravitational Search Algorithm and the mating behaviour in peafowls. The Infrasonic Search Algorithm identified competitive solutions to 23 benchmark unimodal and multimodal test functions compared to the Genetic Algorithm, Particle Swarm Optimization Algorithm and the Gravitational Search Algorithm.

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“…Because buffers can decrease the blocking phenomenon and keep machines working smoothly, it is vital to allocate buffers reasonably to improve the system performance and optimize the system energy consumption. 1,2 The MBAP can be solved by integrating evaluative algorithms with optimization algorithms. 3,4 Optimization algorithms search for candidate solutions, whereas evaluative algorithms select optimal solutions among candidate solutions.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A data-driven ensemble algorithm of black widow optimizer and simulated annealing algorithms for multi-objective buffer allocation in production lines

Gao

Liu

2023

Proceedings of the Institution of Mechanical Engineers, Part B:

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The multi-objective buffer allocation problem of production lines is a non-deterministic-polynomial-hard problem. Many metaheuristic algorithms have been proposed to solve this problem. However, further investigation of new algorithms is still required because metaheuristic algorithms highly depend on the problem types. Furthermore, the balance between the solution quality and computational efficiency requires further improvement. Therefore, a data-driven algorithm consisting of the black widow optimizer and simulated annealing algorithm is proposed to maximize throughput and minimize energy consumption in production lines. Numerical examples demonstrate that the proposed algorithm achieves better solution quality than other state-of-the-art algorithms without losing computational efficiency. This study contributes to multi-objective optimization of resource scheduling in production lines.

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Energy-efficient buffer allocation problem in unreliable production lines

Cited by 13 publications

References 32 publications

A Discrete-Time Queueing Model of a Bottleneck with an Energy-Saving Mechanism Based on Setup and Shutdown Times

A Discrete-Time Queueing Model of a Bottleneck with an Energy-Saving Mechanism Based on Setup and Shutdown Times

A Meta-Heuristic Search Algorithm based on Infrasonic Mating Displays in Peafowls

A data-driven ensemble algorithm of black widow optimizer and simulated annealing algorithms for multi-objective buffer allocation in production lines

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