‘Mover’ a Centralized Job Scheduling and Rapid Routing Solution

2015

Transportation is a serious issue deserving due concern in industries. Raw materials and finished goods must be moved within different work stations in an industry. The overall efficiency and production rate of an industry can be improved drastically by employing microcontroller based robots for carrying out these movements. This paper demonstrates the implementation of the prototype of such a robot. The robot is controlled by an ATMEGA 16 microcontroller. The communication with the robot from an external source is realized through a ST-TX01 315/433.92 MHZ ASK Transmitter and ST-RX04 315/433.92 MHZ ASK Receiver. The data transmitted is encoded through a HT12E chip and the same is decoded with HT12D chip fitted inside the robot. This decoded information dictates the orientation (clockwise or anticlockwise) of the gear motors fitted on the robot. The gear motors are interfaced through the motor driver IC L293D. The robot moves to its destination by tracing a black line (in white backg...

International Journal of Industrial Engineering Computations

In this research integrated scheduling of machines and automated guided vehicles (AGVs) in a flexible job shop environment is addressed. The scheduling literature generally ignores the transportation of jobs between the machines and when considered typically assumes an unlimited number of AGVs. In order to comply with Industry 4.0 requirements, today’s manufacturing systems make use of AGVs to transport jobs between the machines. The addressed problem involves simultaneous assignment of operations to one of the alternative machines, determining the sequence of operations on each machine and assignment of transportation operations between machines to an available AGV. We present a Microsoft Excel® spreadsheet-based solution for the problem. Evolver®, a proprietary GA is used for the optimization. The GA routine works as an add-in to the spreadsheet environment. The flexible job shop model is developed in Microsoft Excel® spreadsheet. The assignment of AGV is independent of the GA rou...

Journal of Project Management

The real-time scheduling of automatic guided vehicles (AGVs) in flexible manufacturing system (FMS) is observed to be highly critical and complex due to the dynamic variations of production requirements such as an imbalance of AGVs loading, the high travel time of AGVs, variation in jobs, and AGV routes to name a few. The output from FMS considerably depends on the efficient scheduling of AGVs in the FMS. The multi-objective scheduling decisions for AGVs by nature inspired algorithms yield a considerable reduction throughput time in the FMS. In this paper, investigations are carried out for the multi-objective scheduling of AGVs to simultaneously balance the workload of AGVs and to minimize the travel time of AGVs in the FMS. The multi-objective scheduling is carried out by the application of nature-inspired grey wolf optimization algorithm (GWO) to yield a balanced work-load for AGVs and also to minimize the travel time of AGVs simultaneously in the FMS. The output yield of the GWO algorithm is compared with the results of benchmark problems from the literature. The resulting yield of the proposed algorithm for the multi-objective scheduling of AGVs is observed to outperform the existing algorithms for scheduling of AGVs.

International Journal of Intelligent Systems and Applications in Engineering, 2016

Nowadays, automatic systems become crucial in many factories to achieve some tasks such as minimizing cost, maximizing efficiency, quality, and reliability. The planning is important for manufacturing systems to adopt changing conditions. Also, manufacturers want to obtain fast, reliable, qualified and economic products. Flexible Manufacturing Systems (FMSs) are used to meet this need. FMSs make production fast, qualified, reliable and economic by using computer-controlled structure that includes robots and transportation systems. Automated Guided Vehicles (AGVs) and FMS are thought to be integrated because FMSs use AGVs as a part of transportation in the factory. AGVs are used to carry loads, in other words products, in production areas, warehouses, factories that use magnets, landmarks, laser sensors, lines to know where they are. AGV scheduling and routing is NP-hard and open-ended problems. In the literature, there are many algorithms and methods are proposed to solve these problems. In this study, we present a hybrid algorithm that is composed of simulated annealing (SA) and Dijkstra's algorithm to solve the routing problem. The hybrid algorithm is compared with SA algorithm in terms of distance cost using benchmark problems in the literature.

Applied Soft Computing, 2019

h i g h l i g h t s • A new methodology has been developed for scheduling automated transport vehicles. • A GA and an IG algorithm have been proposed to solve the problem. • Designed a set of benchmark to test the performance of the approach. • The proposed approach improves overall performance of material handling systems.

Computers & Operations Research - CoR, 2007

We propose a hybrid method designed to solve a problem of dispatching and conflict free routing of automated guided vehicles (AGVs) in a flexible manufacturing system (FMS). This problem consists in the simultaneous assignment, scheduling and conflict free routing of the vehicles. Our approach consists in a decomposition method where the master problem (scheduling) is modelled with constraint programming and the subproblem (conflict free routing) with mixed integer programming. Logic cuts are generated by the sub problems and used in the master problem to prune optimal scheduling solutions whose routing plan exhibits conflicts. The hybrid method presented herein allowed to solve instances with up to six AGVs. 2005 Published by Elsevier Ltd.

Simulation Modelling Practice and Theory, 2007

Automated Guided Vehicle (AGV) systems have been frequently used as material handling equipment in manufacturing systems since the last two decades. The use of AGV systems has taken attention of practitioners and researchers. Although there are numerous studies concerning with AGV systems in literature, a few of them deal with the adaptation of these systems into JIT systems. Moreover, the facility layouts considered in those studies have flow-shop environment. In this paper, a simulation model of a hypothetical system which has a job shop environment and which is based on JIT philosophy was developed. In addition, a dispatching algorithm for vehicles moving through stations was presented in order to improve transportation efficiency. In given layout, multiple vehicles can move and their bi-directional flow is allowed. After the model had been established, it was mentioned how to perform simulation output analysis. The factors which may be important for the system were determined by output analysis. An experiment plan was prepared by taking into account these factors. In this plan, two levels were selected for each factor and an experimental design was conducted. The effect of each factor on each performance measure and the interaction of these factors were examined.

Global Journal of Materials Science and Engineering, 2023

Material Handling is an important activity within the larger system by which material is moved, stored, and tracked in commercial infrastructure. The primary goal of this project is to optimize material transportation systems in laboratories and small-scale industries by using Automated Guided Vehicle. An Automated Guided Vehicle is the emerging trend in this field that uses independently operated, selfpropelled vehicles guided along the defined route in the facility for easy and durable operations. The most common application of such a system is to move materials around a manufacturing facility or warehouse. An Automated Guided Vehicle for transporting material from the storage area to the required work areas is designed and fabricated. Here the Automated Guided Vehicle is navigated by RFID tags which is the current trend for navigating the AGV system. Implementing this technique would reduce the time, and also the transportation will be fully automated which would be a new and advanced environment to work in. It can almost carry weights up to 50 kg in single transportation to the workstation. It is designed in such a way that it can be used in both industrial and commercial areas. The main objective is to fabricate a simple and cost-efficient AGV which was later achieved.

2021

Automated Guided Vehicle (AGV) is an automated vehicle that is used to increase efficiency and flexibility in material handling. AGV is part of Flexible Manufacturing Systems for the automation of material handling and storage systems. The application of AGV at PT XYZ is expected to increase efficiency and reduce the risk of work accidents as one of the requirements of PT XYZ's customers in implementing the second Phase Flexible Manufacturing System (FMS). The AGV that will make is a Tow type that will use to transport large and heavy objects, using the DDA algorithm as a reference for one of the AGV work functions, and using a PID controller for speed control, so the motion system more stable. Finally, testing was carried out to find out the advantages of AGV compared to Conventional Tows. The results of the test and observations show that the AGV system has a superior position in several aspects. The AGV has a faster braking response than conventional tows. If AGV is applied at PT XYZ, it will increase the efficiency of material handling.

International Journal of Production Research, 1992

In this paper, an on-line dispatching algorithm is proposed for the FMS scheduling problem. The algorithm uses various priority schemes and relevant information concerning the load of the system and the status of jobs in the scheduling process. This information is organized into hierarchical levels. The scheduling decision process is hierarchical in the sense that different decision criteria are applied sequentially to identifythe most appropriate part and the machine to be served.The algorithm schedules the jobs on a machine or an automated guided vehicle(AGV) one at a time as the scheduling decision is needed (or as the status of the system changes). Performance ofthe proposed algorithm iscompared with severalmachine and AGV scheduling rules by using the mean flow-time and the mean tardiness criteria. Simulation results indicate that the proposed algorithm produces significant mean flow-time and mean tardiness improvements over existing scheduling rules for a variety of experimental conditions.