Quang-Vinh Dang

Scheduling a single mobile robot for part-feeding tasks of production lines

This study deals with the problem of sequencing feeding tasks of a single mobile robot which is able to provide parts for feeders of machines on production lines. The mobile robot has to be scheduled in order to stoppage from lack of parts in the production line. A method based on the characteristics of feeders and inspired by the (

Scheduling of Mobile Robots with Preemptive Tasks

s,Q

A Genetic Algorithm-Based Heuristic for Part-Feeding Mobile Robot Scheduling Problem

) inventory system, is thus applied to define time windows for the feeding tasks of the robot. The capacity of the robot is also taken into consideration. The performance criterion is to minimize total traveling time of the robot for a given planning horizon. A genetic algorithm-based heuristics is presented which results in a significant increase in the speed of finding near-optimal solutions. To evaluate the performance of the genetic algorithm-based heuristic, a mixed-integer programming model has been developed for the problem. A case study is implemented at an impeller production line in a real factory and computational experiments are also conducted to demonstrate the effectiveness of the proposed approach.

Simultaneous scheduling of machines and mobile robots

With the rapid development of technologies, many production systems and modes has been advanced with respect to manufacturing, management and information fields. The paper deals with the problem of the implementation of an autonomous industrial mobile robot in real-world industrial applications in which all these fields are considered, namely mobile robot technology, planning and scheduling and communication. A methodology for implementation consisting of: a mobile robot system design (Little Helper prototype), an appropriate industrial application (multiple-part feeding), an implementation concept for the industrial application (the Bartender Concept), a mathematical model and a genetic algorithm-based heuristic is proposed. Furthermore, in order for the mobile robot to work properly in a flexible (cloud-based) manufacturing environment, the communications and exchange of data between the mobile robot with other manufacturing systems and shop-floor operators are addressed in the methodology. The proposed methodology provides insight into how mobile robot technology and abilities contribute to cloud manufacturing systems. A real-world demonstration at an impeller production line in a factory and computational experiments are conducted to demonstrate the effectiveness of the proposed methodology.

Modelling and Scheduling Autonomous Mobile Robot for a Real-World Industrial Application

This paper deals with the problem of scheduling of mobile robots taking into account preemption cases in a flexible manufacturing system (FMS). In addition to capability of transporting materials between some machines, mobile robots are able to perform manufacturing tasks at other machines by using their manipulation arms. These manufacturing tasks can be preempted to allow mobile robots to transport materials when needed. The performance criterion is to minimize time required to complete all tasks, i.e. makespan. A mixed-integer programming (MIP) model is formulated to find the optimal solutions for the problem. Numerical experiments are investigated to demonstrate results of the proposed approach.

Multimodal Processes Cyclic Steady States Scheduling

Eco-production and logistics with environmental consciousness are playing a larger role in manufacturing firms. They involve scheduling, planning, developing and implementing manufacturing processes and technologies that are required not only to keep productivity high but also to respond to the challenges of issues such as energy conservation and pollution preventions. Facing the central tension between manufacturing and environmental drivers is difficult, but critical to develop new technologies, particularly mobile robots, that can be incorporated into production to achieve holistic solutions. This chapter deals with the problem of finding optimal operating sequence in a manufacturing cell of a mobile robot with manipulation arm that feeds materials to feeders. The “Bartender Concept” is discussed to show the cooperation between the mobile robot and industrial environment. The performance criterion is to minimize total traveling time of the robot with the smallest consumed amount of battery energy in a given planning horizon. A mixed-integer programming (MIP) model is developed to find the optimal solutions for the problem. Two case studies are implemented at an impeller production line to demonstrate the results of the proposed MIP model.

Multi-objective Genetic Algorithm for Real-World Mobile Robot Scheduling Problem

This present study deals with the problem of sequencing feeding tasks of a single mobile robot with manipulation arm which is able to provide parts or components for feeders of machines in a manufacturing cell. The mobile robot has to be scheduled in order to keep machines within the cell producing products without any shortage of parts. A method based on the characteristics of feeders and inspired by the (s, Q) inventory system, is thus applied to define time windows for feeding tasks of the robot. The performance criterion is to minimize total traveling time of the robot in a given planning horizon. A genetic algorithm-based heuristic is developed to find the near optimal solution for the problem. A case study is implemented at an impeller production line in a factory to demonstrate the result of the proposed approach.

Mathematical formulation for mobile robot scheduling problem in a manufacturing cell.

This paper deals with the problem of simultaneously scheduling machines and a number of autonomous mobile robots in a flexible manufacturing system (FMS). Besides capability of transporting materials between machines, the considered mobile robots are different from other material handling devices in terms of their advanced ability to perform tasks at machines by using their manipulation arms. The mobile robots thus have to be scheduled in relation to scheduling of machines so as to increase the efficiency of the overall system. The performance criterion is to minimize time required to complete all tasks or makespan. A heuristic based on genetic algorithm is developed to find the best solution for the problem. A numerical example is investigated to demonstrate results of the proposed approach. The implementation of the proposed approach in a multi-agent system is also generally described.