| 1. |
- Benetti, Daniele, et al.
(author)
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Hole-extraction and photostability enhancement in highly efficient inverted perovskite solar cells through carbon dot-based hybrid material
- 2019
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In: Nano Energy. - : Elsevier. - 2211-2855 .- 2211-3282. ; 62, s. 781-790
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Journal article (peer-reviewed)abstract
- We report the effect of the integration of carbon dots (Cdots) in high-performance inverted planar-heterojunction (PHJ) perovskite solar cells (PSCs). We used Cdots to modify the hole-transport layer in planar PSC devices. By introducing Cdots on graphene oxide (GO) as hole-transporting layer, the efficiency of the PSC improved significantly from 14.7% in the case of bare GO to 16.2% of the best device with optimized Cdots content. When applying Cdots with an engineered absorption in the UV range as downshifting layer, the device performance was further improved, attaining a maximum PCE of 16.8% (+14%); the stability of the device was also enhanced of more than 20%. Kelvin probe force microscopy (KPFM) and cyclic voltammetry (CV) were employed to analyze the electronic band alignment at the interface between GO/Cdots and the perovskite film. Holes were extracted and transferred to the conductive substrate more efficiently in the presence of Cdots, thus delaying charge recombination. Photoluminescence (PL), transient PL decays and transient photovoltage (TPV) decays investigated the charge-transfer kinetics and proved the retardation of charge recombination. This work reveals an effective enhancement of the performance of planar PSCs by using Cdots/GO as hole transport material.
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| 2. |
- Fathi, Masood, et al.
(author)
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An improved genetic algorithm with variable neighborhood search to solve the assembly line balancing problem
- 2020
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In: Engineering computations. - : Emerald Group Publishing Limited. - 0264-4401 .- 1758-7077. ; 37:2, s. 501-521
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Journal article (peer-reviewed)abstract
- Purpose – This study aims to propose an efficient optimization algorithm to solve the assembly line balancing problem (ALBP). The ALBP arises in high-volume, lean production systems when decision makers aim to design an efficient assembly line while satisfying a set of constraints.Design/methodology/approach – An improved genetic algorithm (IGA) is proposed in this study to deal with ALBP in order to optimize the number of stations and the workload smoothness.Findings – To evaluate the performance of the IGA, it is used to solve a set of well-known benchmark problems and a real-life problem faced by an automobile manufacturer. The solutions obtained are compared against two existing algorithms in the literature and the basic genetic algorithm. The comparisons show the high efficiency and effectiveness of the IGA in dealing with ALBPs.Originality/value – The proposed IGA benefits from a novel generation transfer mechanism that improves the diversification capability of the algorithm by allowing population transfer between different generations. In addition, an effective variable neighborhood search is employed in the IGA to enhance its local search capability.
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| 3. |
- Fathi, Masood, et al.
(author)
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An optimization model for balancing assembly lines with stochastic task times and zoning constraints
- 2019
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In: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 7, s. 32537-32550
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Journal article (peer-reviewed)abstract
- This study aims to bridge the gap between theory and practice by addressing a real-world assembly line balancing problem (ALBP) where task times are stochastic and there are zoning constraints in addition to the commonly known ALBP constraints. A mixed integer programming (MIP) model is proposed for each of the straight and U-shaped assembly line configurations. The primary objective in both cases is to minimize the number of stations; minimizing the maximum of stations’ mean time and the stations’ time variance are considered secondary objectives. Four different scenarios are discussed for each model, with differences in the objective function. The models are validated by solving a real case taken from an automobile manufacturing company and some standard test problems available in the literature. The results indicate that both models are able to provide optimum solutions for problems of different sizes. The technique for order preference by similarity to ideal solution (TOPSIS) is used to create reliable comparisons of the different scenarios and valid analysis of the results. Finally, some insights regarding the selection of straight and U-shaped layouts are provided.
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| 4. |
- Fathi, Masood, et al.
(author)
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Assembly Line Balancing Type-E with Technological Requirement : A Mathematical Model
- 2018
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In: Advances in Manufacturing Technology XXXII. - Amsterdam : IOS Press. - 9781614999010 - 9781614999027 ; , s. 183-188
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Conference paper (peer-reviewed)abstract
- This study is motivated by a real-world assembly line in an automotive manufacturing company and it addresses the simple assembly line balancing problem type-E (SALBPE). The SALBPE aims to maximize the balance efficiency (BE) through determining the best combinations of cycle time and station number. To cope with the problem, a mixed integer nonlinear programming (MINLP) model is proposed. The MINLP model differs from the existing ALBPE models as it includes the technological requirements of assembly tasks and optimizes the variation of workload beside the BE. The validity of the proposed model is tested by solving the real-world case study and a set of benchmark problems.
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| 5. |
- Fathi, Masood, et al.
(author)
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Production Sustainability via Supermarket Location Optimization in Assembly Lines
- 2020
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In: Sustainability. - : MDPI. - 2071-1050. ; 12:11, s. 1-16
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Journal article (peer-reviewed)abstract
- Manufacturers worldwide are nowadays in pursuit of sustainability. In the Industry 4.0 era, it is a common practice to implement decentralized logistics areas, known as supermarkets, to achieve production sustainability via Just-in-Time material delivery at assembly lines. In this environment, manufacturers are commonly struggling with the Supermarket Location Problem (SLP), striving to efficiently decide on the number and location of supermarkets to minimize the logistics cost. To address this prevalent issue, this paper proposed a Simulated Annealing (SA) algorithm for minimizing the supermarket cost, via optimally locating supermarkets in assembly lines. The efficiency of the SA algorithm was tested by solving a set of test problems. In doing so, a holistic performance index, namely the total cost of supermarkets, was developed that included both shipment cost and the installation cost across the assembly line. The effect of workload balancing on the supermarket cost was also investigated in this study. For this purpose, the SLP was solved both before and after balancing the workload. The results of the comparison revealed that workload balancing could significantly reduce the total supermarket cost and contribute to the overall production and economic sustainability. It was also observed that the optimization of material shipment cost across the assembly line is the most influencing factor in reducing the total supermarket cost.
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| 6. |
- Fiddaman, Steven R., et al.
(author)
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Ancient chicken remains reveal the origins of virulence in Marek's disease virus
- 2023
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In: Science (New York, N.Y.). - 1095-9203. ; 382:6676, s. 1276-1281
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Journal article (peer-reviewed)abstract
- The pronounced growth in livestock populations since the 1950s has altered the epidemiological and evolutionary trajectory of their associated pathogens. For example, Marek's disease virus (MDV), which causes lymphoid tumors in chickens, has experienced a marked increase in virulence over the past century. Today, MDV infections kill >90% of unvaccinated birds, and controlling it costs more than US$1 billion annually. By sequencing MDV genomes derived from archeological chickens, we demonstrate that it has been circulating for at least 1000 years. We functionally tested the Meq oncogene, one of 49 viral genes positively selected in modern strains, demonstrating that ancient MDV was likely incapable of driving tumor formation. Our results demonstrate the power of ancient DNA approaches to trace the molecular basis of virulence in economically relevant pathogens.
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| 7. |
- Nourmohammadi, Amir, et al.
(author)
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A Genetic Algorithm for Bi-Objective Assembly Line Balancing Problem
- 2019
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In: Advances in Manufacturing Technology XXXIII. - Amsterdam : IOS Press. - 9781643680088 - 9781643680095 ; , s. 519-524
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Conference paper (peer-reviewed)abstract
- Assembly line designs in manufacturing commonly face the key problem of dividing the assembly tasks among the working stations so that the efficiency of the line is optimized. This problem is known as the assembly line balancing problem which is known to be NP-hard. This study, proposes a bi-objective genetic algorithm to cope with the assembly line balancing problem where the considered objectives are the utilization of the assembly line and the workload smoothness measured as the line efficiency and the variation of workload, respectively. The performance of the proposed genetic algorithm is tested through solving a set of standard problems existing in the literature. The computational results show that the genetic algorithm is promising in providing good solutions to the assembly line balancing problem.
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| 8. |
- Nourmohammadi, Amir, et al.
(author)
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A genetic algorithm for heterogenous human-robot collaboration assembly line balancing problems
- 2022
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In: Procedia CIRP. - : Elsevier. - 2212-8271. ; 107, s. 1444-1448
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Journal article (peer-reviewed)abstract
- Originated by a real-world case study from the automotive industry, this paper attempts to address the assembly lines balancing problem with human-robot collaboration and heterogeneous operators while optimizing the cycle time. A genetic algorithm (GA) with customized parameters and features is proposed while considering the characteristics of the problem. The computational results show that the developed GA can provide the decision-makers with efficient solutions with heterogeneous humans and robots. Furthermore, the results reveal that the cycle time is highly influenced by order of the operators’ skills, particularly when a fewer number of humans and robots exist at the stations.
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| 9. |
- Nourmohammadi, Amir, et al.
(author)
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A mathematical model for supermarket location problem with stochastic station demands
- 2018
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In: Procedia CIRP. - : Elsevier. - 2212-8271 .- 2212-8271. ; 72, s. 444-449
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Journal article (peer-reviewed)abstract
- This paper aims to investigate the effect of station demands variations on supermarket location problem (SLP). This problem arises in the real-world assembly line part feeding (PF) context where supermarkets are used as the intermediate storage areas for stations. To this purpose a stochastic SLP model is developed to optimize the total cost of PF in terms of shipment, inventory and installation costs. The computational results over a real case as well as different test instances verify that the station demands variation has an effect on the SLP solutions.
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| 10. |
- Nourmohammadi, Amir, et al.
(author)
-
A water-flow like algorithm for solving U-shaped assembly line balancing problems
- 2019
-
In: IEEE Access. - : Institute of Electrical and Electronics Engineers. - 2169-3536. ; 7, s. 129824-129833
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Journal article (peer-reviewed)abstract
- The problem of assigning assembly tasks to the stations arranged along a material handling device is known as assembly line balancing. This paper aims to address the U-shaped assembly line balancing problem (UALBP) which arises when a U-shaped assembly line has to be configured. It is widely known that this problem is NP-hard. Accordingly, different meta-heuristics based on a single solution (such as Simulated Annealing) or a population of solutions (such as Genetic Algorithms) have been proposed in the literature. Meanwhile, it has been argued that either of these meta-heuristics with a fixed number of solutions cannot maintain efficient search progress and thus can lead to premature convergence. Thus, this study aims at adopting a novel meta-heuristic algorithm with dynamic population sizes, namely Water Flow-like Algorithm (WFA), inspired by the behaviour of water flows in nature, to address the UALBP. The line efficiency and variation of workload are considered as the primary and the secondary objective, to be optimized, respectively. To verify the efficiency and robustness of the proposed WFA, a real case study taken from an automobile manufacturer as well as a set of standard problems are solved and the results compared with the existing approaches in the literature. The computational results demonstrate the superiority of the WFA, particularly in addressing medium to large-sized problems.
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| 11. |
- Nourmohammadi, Amir, et al.
(author)
-
An integrated model for cost-oriented assembly line balancing and parts feeding with supermarkets
- 2018
-
In: Procedia CIRP. - : Elsevier. - 2212-8271 .- 2212-8271. ; 72, s. 381-385
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Journal article (peer-reviewed)abstract
- This paper aims to deal with assembly line design from both line balancing and parts feeding (PF) aspects as two-interrelated decision problems while supermarkets are used. These problems arise in the real-world assembly lines (ALs) where decision makers are planning to simultaneously determine the optimal number of stations and the optimal number of supermarkets so that the total installation costs of ALs including line balancing and PF costs are minimized. To this purpose an integrated mathematical model is proposed and its performance is tested through solving a number of benchmark problems and a real case taken from industry.
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| 12. |
- Nourmohammadi, Amir, et al.
(author)
-
Balancing and scheduling assembly lines with human-robot collaboration tasks
- 2022
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In: Computers & Operations Research. - : Elsevier. - 0305-0548 .- 1873-765X. ; 140, s. 1-18
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Journal article (peer-reviewed)abstract
- In light of the Industry 5.0 trend towards human-centric and resilient industries, human-robot collaboration (HRC) assembly lines can be used to enhance productivity and workers’ well-being, provided that the optimal allocation of tasks and available resources can be determined. This study investigates the assembly line balancing problem (ALBP), considering HRC. This problem, abbreviated ALBP-HRC, arises in advanced manufacturing systems, where humans and collaborative robots share the same workplace and can simultaneously perform tasks in parallel or in collaboration. Driven by the need to solve the more complex assembly line-balancing problems found in the automotive industry, this study aims to address the ALBP-HRC with the cycle time and the number of operators (humans and robots) as the primary and secondary objective, respectively. In addition to the traditional ALBP constraints, the human and robot characteristics, in terms of task times, allowing multiple humans and robots at stations, and their joint/collaborative tasks are formulated into a new mixed-integer linear programming (MILP) model. A neighborhood-search simulated annealing (SA) is proposed with customized solution representation and neighborhood search operators designed to fit into the problem characteristics. Furthermore, the proposed SA features an adaptive neighborhood selection mechanism that enables the SA to utilize its exploration history to dynamically choose appropriate neighborhood operators as the search evolves. The proposed MILP and SA are implemented on real cases taken from the automotive industry where stations are designed for HRC. The computational results over different problems show that the adaptive SA produces promising solutions compared to the MILP and other swarm intelligence algorithms, namely genetic algorithm, particle swarm optimization, and artificial bee colony. The comparisons of human/robot versus HRC settings in the case study indicate significant improvement in the productivity of the assembly line when multiple humans and robots with collaborative tasks are permissible at stations.
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| 13. |
- Nourmohammadi, Amir, et al.
(author)
-
Balancing and scheduling human-robot collaborated assembly lines with layout and objective consideration
- 2024
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In: Computers & industrial engineering. - : Elsevier. - 0360-8352 .- 1879-0550. ; 187
-
Journal article (peer-reviewed)abstract
- The recent Industry 4.0 trend, followed by the technological advancement of collaborative robots, has urged many industries to shift towards new types of assembly lines with human-robot collaboration (HRC). This type of manufacturing line, in which human skill is supported by robot agility, demands an integrated balancing and scheduling of tasks and operators among the stations. This study attempts to deal with these joint problems in the straight and U-shaped assembly lines while considering different objectives, namely, the number of stations (Type-1), the cycle time (Type-2), and the cost of stations, operators, and robot energy consumption (Type-rw). The latter type often arises in the real world, where multiple types of humans and robots with different skills and energy levels can perform the assembly tasks collaboratively or in parallel at stations. Additionally, practical constraints, namely robot tool changes, zoning, and technological requirements, are considered in Type-rw. Accordingly, different mixed-integer linear programming (MILP) models for straight and U-shaped layouts are proposed with efficient lower and upper bounds for each objective. The computational results validate the efficiency of the proposed MILP model with bounded objectives while addressing an application case and different test problem sizes. In addition, the analysis of results shows that the U-shaped layout offers greater flexibility than the straight line, leading to more efficient solutions for JIT production, particularly in objective Type-2 followed by Type-rw and Type-1. Moreover, the U-shaped lines featuring a high HRC level can further enhance the achievement of desired objectives compared to the straight lines with no or limited HRC.
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| 14. |
- Nourmohammadi, Amir, et al.
(author)
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Choosing efficient meta-heuristics to solve the assembly line balancing problem : A landscape analysis approach
- 2019
-
In: Procedia CIRP. - : Elsevier. - 2212-8271 .- 2212-8271. ; 81, s. 1248-1253
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Journal article (peer-reviewed)abstract
- It is widely known that the assembly line balancing problem (ALBP) is an NP-hard optimization problem. Although different meta-heuristics have been proposed for solving this problem so far, there is no convincing support that what type of algorithms can perform more efficiently than the others. Thus, using some statistical measures, the landscape of the simple ALBP is studied for the first time in the literature. The results indicate a flat landscape for the problem where the local optima are uniformly scattered over the search space. Accordingly, the efficiency of population-based algorithms in addressing the considered problem is statistically validated.
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| 15. |
- Nourmohammadi, Amir, et al.
(author)
-
Design of stochastic assembly lines considering line balancing and part feeding with supermarkets
- 2019
-
In: Engineering optimization (Print). - : Taylor & Francis Group. - 0305-215X .- 1029-0273. ; 51:1, s. 63-83
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Journal article (peer-reviewed)abstract
- This article aims to address the assembly line balancing problem (ALBP) and supermarket location problem (SLP) as two long-term interrelated decision problems considering the stochastic nature of the task times and demands. These problems arise in real-world assembly lines during the strategic decision-making phase of configuring new assembly lines from both line balancing and part-feeding (PF) aspects. A hierarchical mathematical programming model is developed, in which the first level resolves the stochastic ALBP by minimizing the workstation numbers and the second level deals with the stochastic SLP while optimizing the PF shipment, inventory and installation costs. The results of case data from an automotive parts manufacturer and a set of standard test problems verified that the proposed model can optimize the configuration of assembly lines considering both ALBP and SLP performance measures. This study also validates the effect of the stochastic ALBP on the resulting SLP solutions.
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| 16. |
- Nourmohammadi, Amir, et al.
(author)
-
Integrated locating in-house logistics areas and transport vehicles selection problem in assembly lines
- 2021
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In: International Journal of Production Research. - : Taylor & Francis. - 0020-7543 .- 1366-588X. ; 59:2, s. 598-616
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Journal article (peer-reviewed)abstract
- Decentralised in-house logistics areas, known as supermarkets, are widely used in the manufacturing industry for parts feeding to assembly lines. In contrary to the literature and inspired by observation in a real case, this study relaxes the assumption of using identical transport vehicles when deciding on the supermarkets’ location by considering the availability of different vehicles. In this regard, this study deals with the integrated supermarket location and transport vehicles selection problems (SLTVSP). A mixed-integer programming (MIP) model of the problem is developed. Due to the complexity of the problem, a hybrid genetic algorithm (GA) with variable neighborhood search (GA-VNS) is also proposed to address large-sized problems. The performance of GA-VNS is compared against the MIP, the basic GA, and simulated annealing (SA) algorithm. The computational results from the real case and a set of generated test problems show that GA-VNS provides a very good approximation of the MIP solutions at a much shorter computational time while outperforming the other compared algorithms. The analysis of the results reveals that it is beneficial to apply different transport vehicles rather than identical vehicles for SLTVSP.
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| 17. |
- Nourmohammadi, Amir, et al.
(author)
-
Multi-objective optimization of cycle time and robot energy expenditure in human-robot collaborated assembly lines
- 2024
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In: Procedia Computer Science. - : Elsevier. - 1877-0509. ; 232, s. 1279-1288
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Journal article (peer-reviewed)abstract
- The recent Industry 4.0 trend, followed by the technological advancement of collaborative robots, has convinced many industries to shift towards semi-automated assembly lines with human-robot collaboration (HRC). In the HRC environment, robot agility can support human skill upon efficiently balancing tasks among the stations and operators. On the other hand, the robot energy consumption in today's energy crisis area demands that tasks be performed with as little energy utilization as possible by robots. In this context, the cycle time (CT) and total energy cost (TEC) of robots are among two conflicting objectives. Thus, this study balances HRC lines where a trade-off between CT and TEC of robots is sought. A mixed-integer linear programming model is proposed to formulate the problem. In addition, a multi-objective optimization approach based on ε-constraint is developed to address a case study from the automotive industry and a set of generated test problems. The computational results show that promising Pareto solutions in terms of CT and TEC can be obtained using the proposed approach.
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| 18. |
- Nourmohammadi, Amir, et al.
(author)
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Multi-objective optimization of mixed-model assembly lines incorporating musculoskeletal risks assessment using digital human modeling
- 2023
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In: CIRP - Journal of Manufacturing Science and Technology. - : Elsevier. - 1755-5817 .- 1878-0016. ; 47, s. 71-85
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Journal article (peer-reviewed)abstract
- In line with Industry 5.0, ergonomic factors have recently received more attention in balancing assembly lines to enhance the human-centric aspect. Meanwhile, today’s mass-customized trend yields manufacturers to offset the assembly lines for different product variants. Thus, this study addresses the mixed-model assembly line balancing problem (MMALBP) by considering worker posture. Digital human modeling and posture assessment technologies are utilized to assess the risks of work-related musculoskeletal disorders using a method known as rapid entire body analysis (REBA). The resulting MMALBP is formulated as a mixed-integer linear programming (MILP) model while considering three objectives: cycle time, maximum ergonomic risk of workstations, and total ergonomic risks. An enhanced non-dominated sorting genetic algorithm (E-NSGA-II) is developed by incorporating a local search procedure that generates neighborhood solutions and a multi-criteria decision-making mechanism that ensures the selection of promising solutions. The E-NSGA-II is benchmarked against Epsilon-constraint, MOGA, and NSGA-II while solving a case study and also test problems taken from the literature. The computational results show that E-NSGA-II can find promising Pareto front solutions while dominating the considered methods in terms of performance metrics. The robustness of E-NSGA-II results is evaluated through one-way ANOVA statistical tests. The analysis of results shows that a smooth distribution of time and ergonomic loads among the workstations can be achieved when all three objectives are simultaneously considered.
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| 19. |
- Slama, Ilhem, et al.
(author)
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Assembly Line Balancing with Collaborative Robots Under Uncertainty of Human Processing Times
- 2023
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In: 2023 9th International Conference on Control, Decision and Information Technologies (CoDIT). - : IEEE. - 9798350311419 - 9798350311402 - 9798350311396 ; , s. 2649-2653
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Conference paper (peer-reviewed)abstract
- This paper studies the assembly line balancing problem with collaborative robots in light of recent efforts to implement collaborative robots in industrial production systems under random processing time. A stochastic version with uncertain human processing time is considered for the first time. The issue is defined by the potential for simultaneous human and robot task execution at the same workpiece, either in parallel or in collaboration. We provide stochastic mixed-integer programming based on Monte Carlo sampling approach for the balancing and scheduling of collaborative robot assembly lines for this novel issue type. In order to minimise the line cost including fixed workstation operating costs and resource costs caused by exceeding cycle time, the model determines both the placement of collaborative robots at stations and the distribution of work among humans and robots.
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