Task Planning Optimization in Assisting Multiple NC Machine Tools Using AMR DOI

Ken Kusashio,

Takahiro Yakoh, Yasuhiro Kakinuma

et al.

2022 IEEE International Conference on Industrial Technology (ICIT), Journal Year: 2024, Volume and Issue: 22, P. 1 - 6

Published: March 25, 2024

Although advanced manufacturing strategies such as Industry 4.0 are becoming popular, many small and medium-sized enterprises (SMEs) still facing challenges in factory automation. One of the reasons is that automation may require significant system updates. A retrofittable handle versatile tasks needed to facilitate easier integration industry. This paper proposes a can assist multiple numerical control (NC) machine tools using an autonomous mobile robots (AMR). The integrated chip removal inside NC tool's chuck, vibration analysis while tool processing charging AMR. AMR has perform these within production line's strict time constraints AMR's battery constraint. proposed produced feasible schedule tasks. Numerical simulation evaluated feasibility schedule. was verified by performing real world.

Language: Английский

Multi-objective Optimization for Green Delivery Routing Problems with Flexible Time Windows DOI Creative Commons
Burak Gülmez, Michael Emmerich, Yingjie Fan

et al.

Applied Artificial Intelligence, Journal Year: 2024, Volume and Issue: 38(1)

Published: March 27, 2024

This paper presents a model and heuristic solution algorithms for the Green Vehicle Routing Problem with Flexible Time Windows. A scenario of new vehicle routing is analyzed in which customers are asked to provide alternative time windows offer flexibility help route planners find more fuel-efficient routes ("green delivery"). Customers can rank their preferred as first, second, third. The optimization aims reduce tour costs, promote electromobility over fossil fuels, such diesel, meet customer preferences when possible affordable. study incorporates multi-objective three objectives, overall cost, use fuel, satisfaction. For problem, set realistic benchmark problems created four mainstream solvers applied Pareto front approximation: NSGA-II, NSGA-III, MOEA/D, SMS-EMOA. These compared terms effectiveness achieving objectives minimizing travel promoting electromobility, meeting preferences. uses five different single-vehicle planning. Two major findings that selection metaheuristic make big difference algorithm performance. resulting 3-D fronts reveal nature this class problems: Interestingly, flexible windows, most users still be delivered only small concessions other objectives. However, using one window per user lead an increasingly drastic cost fuel consumption.

Language: Английский

Citations

9

Optimizing Internal Logistics Using Automated Guided Vehicles: An Evaluation of Heuristic Approaches DOI
José A. Oliveira,

Bernardo Fernandes,

Marcelo Henriques

et al.

Communications in computer and information science, Journal Year: 2025, Volume and Issue: unknown, P. 42 - 55

Published: Jan. 1, 2025

Language: Английский

Citations

0

An Effective Hybrid Jellyfish Search Algorithm for Multi-AGVs Path Planning DOI
Xiaojie Chen, Qingtao Wu, Xuhui Zhao

et al.

Published: March 8, 2024

Language: Английский

Citations

2

Optimization strategy of mixed-integer linear planning in logistics distribution DOI Creative Commons
Yuhua Li

Applied Mathematics and Nonlinear Sciences, Journal Year: 2024, Volume and Issue: 9(1)

Published: Jan. 1, 2024

Abstract The evolution of the logistics and distribution industry, notably express delivery sector, has significantly increased its prevalence in everyday life. This escalation necessitates an ongoing innovation strategies enhancements service quality, positioning these elements at heart industry focus. study initially addresses vehicular route planning issue within distribution, selecting Company A as a case to examine inherent logistical challenges. Subsequently, it develops optimal model under time constraints. It is converted into mixed-integer linear programming through techniques such variable substitution segmented approximation. conversion facilitates rapid solutions by mathematical solvers. research contrasts performance before after optimization assess efficacy proposed strategies. Findings indicate that optimized achieves more equitable tasks, along with substantial improvements complexity transportation routes reduction travel distances. Specifically, results significant decrease penalty costs associated vehicles, cost for third vehicle involved reduced 66.40%. evidence supports implementation scientific scheduling firms, underscoring model’s practical implications.

Language: Английский

Citations

1

Consideration of Carbon Emissions in Multi-Trip Delivery Optimization of Unmanned Vehicles DOI Open Access
Xinhua Gao, Song Liu, Yan Wang

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(6), P. 2357 - 2357

Published: March 12, 2024

In order to achieve the goal of low-carbon, efficient delivery using unmanned vehicles, a multi-objective optimization model considering carbon emissions in problem optimizing multi-route for vehicles is proposed. An improved genetic algorithm (IGA) designed solving this problem. This study takes into account constraints such as maximum service duration delivery, number and approved loading capacity with objective minimizing startup cost, transportation fuel environmental cost terms dioxide vehicles. A combination encoding method based on integer trips, customers used. The inclusion simulated annealing an elite selection strategy design IGA enhances quality efficiency algorithm. international dataset Solomon RC 208 used verify effectiveness small-, medium-, large-scale cases by comparing them (GA) (SA). research results show that proposed applicable while emissions. Compared GA SA, demonstrates faster convergence speed higher efficiency. Additionally, problem’s scale increases, average total deviation rate changes significantly, better solutions are obtained IGA. Furthermore, routes primarily depends their costs distance, choice different vehicle types has impact duration, trips. considers shows 22.6% difference its compared does not consider algorithms provide achieving low-carbon aiming reduce costs. They also contribute development application technology field.

Language: Английский

Citations

0

Task Planning Optimization in Assisting Multiple NC Machine Tools Using AMR DOI

Ken Kusashio,

Takahiro Yakoh, Yasuhiro Kakinuma

et al.

2022 IEEE International Conference on Industrial Technology (ICIT), Journal Year: 2024, Volume and Issue: 22, P. 1 - 6

Published: March 25, 2024

Although advanced manufacturing strategies such as Industry 4.0 are becoming popular, many small and medium-sized enterprises (SMEs) still facing challenges in factory automation. One of the reasons is that automation may require significant system updates. A retrofittable handle versatile tasks needed to facilitate easier integration industry. This paper proposes a can assist multiple numerical control (NC) machine tools using an autonomous mobile robots (AMR). The integrated chip removal inside NC tool's chuck, vibration analysis while tool processing charging AMR. AMR has perform these within production line's strict time constraints AMR's battery constraint. proposed produced feasible schedule tasks. Numerical simulation evaluated feasibility schedule. was verified by performing real world.

Language: Английский

Citations

0