Flow shop scheduling with low carbon emission and variable machining parameters

Lin, Wenwen; Tian, Guangdong; Li, Zhiwu; Zhang, Yuejun; Zhang, Chaoyong

doi:10.1177/0954405418782290

Cited by 13 publications

(16 citation statements)

References 22 publications

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“…The best values of the responses were determined at the end of the convergent run. 23,24 Finally, the TOPSIS was used to determine the best design point. 25,26 Basically, this method identifies the best compromised solution, which satisfies the requirements of the objective functions according to the objective weights.…”

Section: Methodsmentioning

confidence: 99%

Optimization of roller burnishing process using Kriging model to improve surface properties

Nguyen

2019

Proceedings of the Institution of Mechanical Engineers, Part B:

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The objective of this work is to investigate the influences of three machining factors (burnishing speed V, feed rate f, and depth of penetration a) on the improved rate of arithmetic average roughness Δ Ra, improved rate of maximum height roughness Δ Ry, and improved rates of surface hardness Δ SH. The internal roller burnishing experiments were conducted with the aid of the computer numerical control machining center and Box–Behnken experimental design. The Kriging models were used to render the highly nonlinear relationships between inputs and outputs. An integrative approach combining a Non-dominated Sorting Genetic Algorithm II and Technique for Order Preference by Similarity to Ideal Solution was adopted to generate a set of feasible optimal solutions and determine the best machining conditions. The scanning electron microscopy images were depicted to investigate the surface morphology at the different conditions. The X-ray diffraction was applied to measure the compressive stresses at the external surface. The results showed that the predicted values of the objectives have good agreement with the experimental ones. High surface quality is characterized by an improved average roughness of 95.80%, an enhancement in the maximum roughness of 91.98%, and an improvement in surface hardness of 45.44%, compared to pre-machined surfaces. The selection of optimum process parameters could help the burnishing operators to save the machining costs and time. The combination of Kriging model, Non-dominated Sorting Genetic Algorithm II, and Technique for Order Preference by Similarity to Ideal Solution is considered as an intelligent approach for modeling and optimization of burnishing processes.

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Section: Methodsmentioning

confidence: 99%

Optimization of roller burnishing process using Kriging model to improve surface properties

Nguyen

2019

Proceedings of the Institution of Mechanical Engineers, Part B:

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“…Wang et al 21 proposed a fuzzy nonlinear programming approach for planning energy-efficient wafer fabrication factories, thereinto, the total power consumption is obtained by summing the power consumptions of all the products in wafer fab. Lin et al 22 investigated a flow shop scheduling problem with low carbon emission into consideration. For specific scheduling problems, Li et al 23 studied a multi-objective energy-saving scheduling in a permutation flow line shop.…”

Section: Introductionmentioning

confidence: 99%

A multi-objective flexible job-shop cell scheduling problem with sequence-dependent family setup times and intercellular transportation by improved NSGA-II

Han

Chen

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part B:

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With the development of Industry 4.0 and requirement of smart factory, cellular manufacturing system (CMS) has been widely concerned in recent years, which may leads to reducing production cost and wip inventory due to its flexibility production with groups. Intercellular transportation consumption, sequence-dependent setup times, and batch issue in CMS are taken into consideration simultaneously in this paper. Afterwards, a multi-objective flexible job-shop cell scheduling problem (FJSCP) optimization model is established to minimize makespan, total energy consumption, and total costs. Additionally, an improved non-dominated sorting genetic algorithm is adopted to solve the problem. Meanwhile, for improving local search ability, hybrid variable neighborhood (HVNS) is adopted in selection, crossover, and mutation operations to further improve algorithm performance. Finally, the validity of proposed algorithm is demonstrated by datasets of benchmark scheduling instances from literature. The statistical result illustrates that improved method has a better or an equivalent performance when compared with some heuristic algorithms with similar types of instances. Besides, it is also compared with one type scalarization method, the proposed algorithm exhibits better performance based on hypervolume analysis under different instances.

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“…Morillo et al 23 provide a new model and meta-heuristic approach for the resource-constrained scheduling problem. Lin et al 24 use a mathematical model and a novel multi-objective heuristic algorithm to deal with scheduling problems considering variable machining parameters. Liu et al 25 use MIP model and GA in ultra-flexible jobshop (uFJS) to improve the energy efficiency.…”

Section: Introductionmentioning

confidence: 99%

A Tabu-GA-based parallel machine scheduling with restrained tool resources

Wang

Zou

Wang

2020

Proceedings of the Institution of Mechanical Engineers, Part B:

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In flexible manufacturing systems, disordered parallel machine scheduling may cause interruptions in the production line; thus, a reasonable scheduling plan beneﬁts proﬁts of manufacturing. In the literature, the operation sequence, the operation assignment, the tool scheduling, and the tool switching problems have been studied with unlimited resources. However, in practical manufacturing process, a scheduling problem along with these problems with restrained resources should be studied to make scheduling solutions more performable. There are a number of operations processed on a group of parallel machines, and each operation requires a set of tools where the tool copy number and tool service life are limited. The objective of this problem is to minimize the make-span with restrained resources. This article studies a parallel machine scheduling problem combining operation scheduling, tool scheduling and restrained resources, which benefit the real industry. A Tabu-Genetic Algorithm is proposed to find the optimal solution. In small size problem, the proposed method can achieve similar results whereas the mixed integer programming approach can obtain the exact solution. However, in large size problem, the latter cannot obtain the solutions within acceptable times, whereas the proposed method can ﬁnd solutions within reasonable times. This algorithm performs better when compared to Tabu search algorithm and genetic algorithm in selecting local and global optima.

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Flow shop scheduling with low carbon emission and variable machining parameters

Cited by 13 publications

References 22 publications

Optimization of roller burnishing process using Kriging model to improve surface properties

Optimization of roller burnishing process using Kriging model to improve surface properties

A multi-objective flexible job-shop cell scheduling problem with sequence-dependent family setup times and intercellular transportation by improved NSGA-II

A Tabu-GA-based parallel machine scheduling with restrained tool resources

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