Selective disassembly sequence planning under uncertainty using trapezoidal fuzzy numbers: A novel hybrid metaheuristic algorithm

Engineering Applications of Artificial Intelligence, Journal Year: 2023, Volume and Issue: 128, P. 107459 - 107459

Published: Nov. 22, 2023

Language: Английский

Dynamic grouping maintenance optimization by considering the probabilistic remaining useful life prediction of multiple equipment

Eksploatacja i Niezawodnosc - Maintenance and Reliability, Journal Year: 2024, Volume and Issue: 26(3)

Published: May 11, 2024

For multi-equipment maintenance of modern production equipment, the economic correlation and degradation uncertainty may lead to insufficient or excessive maintenance, increasing costs. This paper proposes a dynamic grouping method based on probabilistic remaining useful life (RUL) prediction for multiple equipment. Long short term memory (LSTM) is developed predict equipment probability RUL by Variational Auto-Encoder (VAE) resampling. Then, model constructed minimize cost rate under known information. The gazelle optimization algorithm (GOA) used determine optimal time each To better verify effectiveness proposed method, numerical case with six wind turbines introduced analyse performance GOA. Moreover, advantages verified comparing independent whose reduced 10.01%.

Language: Английский

Solving a Stochastic Multi-Objective Sequence Dependence Disassembly Sequence Planning Problem with an Innovative Bees Algorithm

Automation, Journal Year: 2024, Volume and Issue: 5(3), P. 432 - 449

Published: Aug. 23, 2024

As the number of end-of-life products multiplies, issue their efficient disassembly has become a critical problem that urgently needs addressing. The field sequence planning consequently attracted considerable attention. In actual process, complex structures can lead to significant delays due interference between different tasks. Overlooking this result in inefficiencies and waste resources. Therefore, it is particularly important study sequence-dependent problem. Additionally, activities are inherently fraught with uncertainties, neglecting these further impact effectiveness disassembly. This first analyze an uncertain environment. It utilizes stochastic programming approach address uncertainties. Furthermore, mixed-integer optimization model constructed minimize time energy consumption simultaneously. Recognizing complexity problem, introduces innovative bees algorithm, which proven its by showing superior performance compared other state-of-the-art algorithms various test cases. research offers solutions for holds implications advancing sustainable development recycling

Language: Английский