Multi-Objective Optimization Method of Industrial Workshop Layout from the Perspective of Low Carbon

Li, Rui; Chen, Yali; Song, Jinzhao; Li, Ming; Yu, Yu

doi:10.3390/su151612275

Cited by 4 publications

(2 citation statements)

References 29 publications

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“…The first theme reviews studies that have outlined the importance of data-driven decisions in determining recovery options in closed-loop systems, and their impact on sustainability outcomes. Recent key publications in this area include [30,31], where simulation models were constructed to analyze diverse product recovery strategies and routing optimization and time window scheduling. These studies assess diverse reverse logistics scenarios, integrating algorithms to optimize vehicle routing and scheduling, thus promoting sustainability.…”

Section: Xin Et Al (2022) [26]mentioning

confidence: 99%

An Integrated Methodology for Enhancing Reverse Logistics Flows and Networks in Industry 5.0

Dabo,

Hosseinian-Far

2023

Logistics

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Background: This paper explores the potential of Industry 5.0 in driving societal transition to a circular economy. We focus on the strategic role of reverse logistics in this context, underlining its significance in optimizing resource use, reducing waste, and enhancing sustainable production and consumption patterns. Adopting sustainable industrial practices is critical to addressing global environmental challenges. Industry 5.0 offers opportunities for achieving these goals, particularly through the enhancement of reverse logistics processes. Methods: We propose an integrated methodology that combines binary logistic regression and decision trees to predict and optimize reverse logistics flows and networks within the Industry 5.0 framework. Results: The methodology demonstrates effective quantitative modeling of influential predictors in reverse logistics and provides a structured framework for understanding their interrelations. It yields actionable insights that enhance decision-making processes in supply chain management. Conclusions: The methodology supports the integration of advanced technologies and human-centered approaches into industrial reverse logistics, thereby improving resource sustainability, systemic innovation, and contributing to the broader goals of a circular economy. Future research should explore the scalability of this methodology across different industrial sectors and its integration with other Industry 5.0 technologies. Continuous refinement and adaptation of the methodology will be necessary to keep pace with the evolving landscape of industrial sustainability.

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Section: Xin Et Al (2022) [26]mentioning

confidence: 99%

An Integrated Methodology for Enhancing Reverse Logistics Flows and Networks in Industry 5.0

Dabo,

Hosseinian-Far

2023

Logistics

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“…With the acceleration of the industrial process, the application of large equipment and complex devices has become more extensive. For the study of complex systems, the optimization of multiple variables has also become more meaningful [27][28][29]. Therefore, the multi-rate optimization problem has attracted more and more researchers' attention.…”

Section: Introductionmentioning

confidence: 99%

Online Dynamic Optimization of Multi-Rate Processes with the Case of a Fluid Catalytic Cracking Unit

Zhang,

Lin,

et al. 2023

Processes

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Due to operational limitations in the industrial field, the operating variables of fluid catalytic cracking units (FCCU) are of multiple operating frequencies, which are CO combustion promoter amount, recycle slurry flow rate, combustion air flow rate, heat escape, and reaction temperature, from low frequency to high frequency. There are usually two schemes for operation optimization of FCCU. The former is called single-rate, single-window optimization, whose operating variables are optimized only once in the whole operation cycle, which is easy to achieve, but the optimization effect is poor. The latter is called single-rate multi-window optimization, whose operating variables are optimized repeatedly and whose operation cycle is discretized into multiple optimization periods with the same frequency, which costs a heavy calculation burden and cannot adapt to the optimization variables with multiple operating frequencies. So, a multi-rate, variable-window online dynamic optimization method is proposed. In an operation cycle, the high-frequency operating variable is optimized in a short optimization period, and the low-frequency operating variable is optimized in a long optimization period; each optimization period has integer multiples to the minimum optimization period. Each optimized result for each optimization period is put into use online immediately. The optimization model involves the time domain differential equations, integral cost objective function, and measured disturbances. The experimental results show that compared with the single-rate, single-window optimization method and single-rate multi-window optimization method, the optimization effect of multi-rate, variable-window online dynamic optimization is better than single-rate, single-window optimization but worse than single-rate multi-window optimization. However, the optimization results are consistent with the operation frequency of each optimization variable, which can be implemented in complex chemical processes and increase certain economic benefits.

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Enhanced Decision Support for Multi-Objective Factory Layout Optimization: Integrating Human Well-Being and System Performance Analysis

Lind,

Elango,

Bandaru

et al. 2024

Applied Sciences

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This paper presents a decision support approach to enable decision-makers to identify no-preference solutions in multi-objective optimization for factory layout planning. Using a set of trade-off solutions for a battery production assembly station, a decision support method is introduced to select three solutions that balance all conflicting objectives, namely, the solution closest to the ideal point, the solution furthest from the nadir point, and the one that is best performing along the ideal nadir vector. To further support decision-making, additional analyses of system performance and worker well-being metrics are integrated. This approach emphasizes balancing operational efficiency with human-centric design, aligning with human factors and ergonomics (HFE) principles and Industry 4.0–5.0. The findings demonstrate that objective decision support based on Pareto front analysis can effectively guide stakeholders in selecting optimal solutions that enhance both system performance and worker well-being. Future work could explore applying this framework with alternative multi-objective optimization algorithms.

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Multi-Objective Optimization Method of Industrial Workshop Layout from the Perspective of Low Carbon

Cited by 4 publications

References 29 publications

An Integrated Methodology for Enhancing Reverse Logistics Flows and Networks in Industry 5.0

An Integrated Methodology for Enhancing Reverse Logistics Flows and Networks in Industry 5.0

Online Dynamic Optimization of Multi-Rate Processes with the Case of a Fluid Catalytic Cracking Unit

Enhanced Decision Support for Multi-Objective Factory Layout Optimization: Integrating Human Well-Being and System Performance Analysis

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