Vehicles In Flexible Manufacturing System Research Articles

A bio-inspired scheduling approach for machines and automated guided vehicles in flexible manufacturing system using hormone secretion principle

The product quality and production efficiency of a flexible manufacturing system have improved effectively by introducing the computer management and the material transportation system. The flexible manufacturing system performance greatly depends on the performance of the material transportation system. As a mobile robot controlled by a central controller, an automated guided vehicle has a strong ability for material transportation. This article studies a dynamic scheduling problem in a shop floor, where machines and automated guided vehicles run at a specified speed and specifies a mathematical model for the dynamic scheduling problem with the goal of makespan minimization. Meanwhile, inspired by the hormone secretion principle of the endocrine system, a bio-inspired scheduling optimization approach is developed to solve the dynamic scheduling problem in the flexible manufacturing system. To verify its practical application, the bio-inspired scheduling optimization approach and other scheduling approaches are tested, and the results illustrate that the bio-inspired scheduling optimization approach has better scheduling performance as well as optimizes the quality of integrated and real-time scheduling of machines and automated guided vehicles.

A Clonal Selection Algorithm for Minimizing Distance Travel and Back Tracking of Automatic Guided Vehicles in Flexible Manufacturing System

The flexible manufacturing system (FMS) constitute of several programmable production work centers, material handling systems (MHSs), assembly stations and automatic storage and retrieval systems. In FMS, the automatic guided vehicles (AGVs) play a vital role in material handling operations and enhance the performance of the FMS in its overall operations. To achieve low makespan and high throughput yield in the FMS operations, it is highly imperative to integrate the production work centers schedules with the AGVs schedules. The Production schedule for work centers is generated by application of the Giffler and Thompson algorithm under four kind of priority hybrid dispatching rules. Then the clonal selection algorithm (CSA) is applied for the simultaneous scheduling to reduce backtracking as well as distance travel of AGVs within the FMS facility. The proposed procedure is computationally tested on the benchmark FMS configuration from the literature and findings from the investigations clearly indicates that the CSA yields best results in comparison of other applied methods from the literature.

A Multi-Fidelity Model Approach for Simultaneous Scheduling of Machines and Vehicles in Flexible Manufacturing Systems

Driven by sensor technologies and Internet of Things, massive real-time data from highly interconnected devices are available, which enables the improvement of decision-making quality. Scheduling of such production systems can be challenging as it must incorporate the latest data and be able to re-plan quickly. In this research, a multi-fidelity model for simultaneous scheduling problem of machines and vehicles at flexible manufacturing system has been proposed. In order to improve the computational efficiency, we extend the framework, called multi-fidelity optimization with ordinal transformation and optimal sampling, with combining with the K-means method. The proposed framework enables the benefits of both fast and inexpensive low-fidelity models with accurate but more expensive high-fidelity models. Results show that this approach can significantly decrease computational cost compared with other algorithms in the literature.

Scheduling of Machines and Automated Guided Vehicles in FMS Using Gravitational Search Algorithm

A new meta-heuristic gravitational search(GS) algorithm is proposed for simultaneous scheduling of machines, and two identical automated guided vehicles(AGVs) in a flexible manufacturing system(FMS). It minimize the makespan and completes the assigned jobs faster with possible savings of the resources. The adequacy of the algorithm is demonstrated by solving several problems and comparing with existing results.

Hybrid Architecture for Coordination of AGVs in FMS

This paper presents a hybrid control architecture that coordinates the motion of groups of automated guided vehicles in flexible manufacturing systems. The high-level control is based on a Petri net model, using the industrial standard ISA-95, obtaining a task-based coordination of equipment and storage considering process restrictions, logical precedences, shared resources and the assignment of robots to move workpieces individually or in subgroups. On the other hand, in the low-level control, three basic control laws are designed for unicycle-type robots in order to achieve desired formation patterns and marching behaviours, avoiding inter-robot collisions. The control scheme combines the task assignment for the robots obtained from the discrete-event model and the implementation of formation and marching continuous control laws applied to the motion of the mobile robots. The hybrid architecture is implemented and validated for the case of a flexible manufacturing system and four mobile robots using a virtual reality platform.

Simultaneous scheduling of machines and automated guided vehicles in flexible manufacturing systems using genetic algorithms

The problem of simultaneous scheduling of machines and vehicles in flexible manufacturing system (FMS) was addressed. A spreadsheet based genetic algorithm (GA) approach was presented to solve the problem. A domain independent general purpose GA was used, which was an add-in to the spreadsheet software. An adaptation of the propritary GA software was demonstrated to the problem of minimizing the total completion time or makespan for simultaneous scheduling of machines and vehicles in flexible manufacturing systems. Computational results are presented for a benchmark with 82 test problems, which have been constructed by other researchers. The achieved results are comparable to the previous approaches. The proposed approach can be also applied to other problems or objective functions without changing the GA routine or the spreadsheet model.

Modeling Distributed Transportation Systems Composed of Flexible Automated Guided Vehicles in Flexible Manufacturing Systems

This paper proposes a methodology for modeling and controlling a flexible material handling system (MHS), composed of multiple automated guided vehicles (AGVs), suitable for Flexible Manufacturing Systems (FMSs). The AGVs incorporate artificial intelligent techniques to: i) facilitate the configuration and adaptation when there are layout modifications and ii) simplify the interaction between them using simple coordination models. In order to achieve higher flexibility, the MHS makes use of a decentralized navigation control, which increases autonomy and scalability, and a distributed Petri net for solving task allocation and traffic control problems. In order to facilitate the integration with the manufacturing processes, tasks dispatched by manufacturing cells are allocated by the MHS itself, taking into account pending transportation tasks and the system's performance. The whole system has been tested in a real factory and is currently in operational use.

Implementation Issues of AGVs in Flexible Manufacturing System : A Review

The future success of a manufacturing endeavor is likely to be determined by the speed and efficiency with which it incorporates new technologies into its operations. The objectives of production planning have shifted from how fast parts can be made to how efficiently parts can be transported between stations and in and out of storage. The responsibility for efficient work flow falls on the material handling system. Automated Guided Vehicle (AGV) systems have gained widespread use and their importance for material handling is expected to grow rapidly. The advantages that such systems can offer include easier interface with other automated systems such as flexible manufacturing system. This paper presents a review on implementation issues of automated guided vehicle systems in flexible manufacturing system context. These issues will be discussed under design, panning and control strategies that arise in AGV system. In addition, we propose a integrated framework for implementation of automated guided vehicles in flexible manufacturing system.

Scheduling of machines and automated guided vehicles in FMS using differential evolution

This paper addresses the problem of simultaneous scheduling of machines and two identical automated guided vehicles (AGVs) in a flexible manufacturing system (FMS). For solving this problem, a new meta-heuristic differential evolution (DE) algorithm is proposed. The problem consists of two interrelated problems, scheduling of machines and scheduling of AGVs. A simultaneous scheduling of these, in order to minimise the makespan will result in a FMS being able to complete all the jobs assigned to it at the earliest time possible, thus saving resources. An increase in the performance of the FMS under consideration would be expected as a result of making the scheduling of AGVs as an integral part of the overall scheduling activity. The algorithm is tested by using problems generated by various researchers and the makespan obtained by the algorithm is compared with that obtained by other researchers and analysed.

A simple metaheuristic approach to the simultaneous scheduling of machines and automated guided vehicles

In this paper we address the problem of simultaneous scheduling of machines and vehicles in flexible manufacturing systems. The studied problem is a job shop where the jobs have to be transported between the machines by automatic guided vehicles. In addition to the processing of jobs, we consider the transportation aspect as an integral part of the optimization process. To deal with this problem, we propose a new solution representation based on vehicles rather than machines. Each solution can thus be evaluated using a discrete event approach. An efficient neighbouring system is then described and implemented into three different metaheuristics: iterated local search, simulated annealing and their hybridisation. Computational results are presented for a benchmark of 40 literature instances. New upper bounds are found for 11 of them, showing the effectiveness of the presented approach.

Real‐time routing selection for automated guided vehicles in a flexible manufacturing system

PurposeThe purpose of this paper is to present the development of an architecture for real‐time routing of automated guided vehicles (AGV) in a random flexible manufacturing system (FMS).Design/methodology/approachAGV routing problem is modeled using an evolutionary algorithm‐based intelligent path planning model, which handles vehicle assignments to material handling requests and makes routing decisions with the objective of maximizing the system throughput. The architecture is implemented on a 3‐layer software environment in order to evaluate the effectiveness of the proposed model.FindingsThe proposed architecture, along with the evolutionary algorithm‐based routing model, is implemented in a simulated FMS environment using hypothetical production data. In order to benchmark the performance of the path planning algorithm, the same FMS model is run by traditional dispatching rules. The analysis shows that the proposed routing model outperforms the traditional dispatching rules for real‐time routing of AGVs in many cases.Research limitations/implicationsFuture work includes expanding the scope of the current work by developing and implementing other routing models and benchmarking them against the proposed model on different performance measures.Originality/valueThe implementation of evolutionary algorithms in real‐time routing of AGVs is unique. In addition, due to its modularity, the proposed 3‐layer architecture can allow effective and efficient integration of different real‐time routing algorithms; therefore it can be used as a benchmarking platform.

Optimal Number of Automatic Guided Vehicles in FMS. Lower Bound on the Optimal Numbers.

An optimal design problem is considered for a flexible-manufacturing system (FMS), which consists of a group of numerically controlled machines, automatic guided vehicles (AGVs) and an auto-storage. The processing times of materials (jobs) at each machine form a sequence of identically, independenly distributed (i.i.d.) random variables (r.v.s.). The transferring times of jobs by each AGV from the auto-storage to a machine or from a machine to the total storage also form a sequence of i.i.d.r.v.s. The decision variable is the number of AGVs in the system when the number of machines is fixed. We propose a method for obtaining a lower bound NL on the optimal numbers of AGVs under some important economic criteria which have been used extensively for optimal machining speed problems: This means that at least NL AGVs should be installed in the system. Some numerical examples are presented that demonstrate the practical usefulness of the proposed method.

Load selection of automated guided vehicles in flexible manufacturing systems

This paper examines the operation of multiple-load AGVs in a flexible manufacturing system where AGVs in the system are capable of carrying two or more loads. The load selection problem arises when an AGV stops at a pick-up queue and has to decide which part(s) should be picked up. Five heuristic rules that may be used to select the load to be carried were suggested and evaluated under a hypothetical flexible manufacturing system with the aid of computer simulation. The results revealed that the variable-route-part-priority (VP) rule and fixed-route-part-priority (FP) rule generated significantly higher throughput than their counterparts, while the ’pick-all-send-nearest’ (PN) rule outperformed the other rules in part flowtime and work-in-process level. The results also suggest that when the carrying capacity of the AGV increases, the performance differences among the rules also increase. This finding sustains the need to explore an efficient operation strategy of multiple-load AGVs in flexible manufactur...

Vehicle scheduling in two-cycle flexible manufacturing systems

Flexible manufacturing systems (FMSs) have received much attention recently due to their importance for designing modern factories producing small lots of complicated products to specific customer orders. One of the most important problems arising in this context is scheduling parts on machines and, connected with it, an appropriate routing of automated guided vehicles (AGVs) ensuring on-time delivery of parts to particular machines. This paper generalizes a new approach to model flexible manufacturing systems, motivated by the practical application. The objective is to develop algorithmic procedures that integrate the production schedules with the routing of automated guided vehicles in FMS. The transportation system of the FMS model consists of two cycles, leading to two separate machining centers. These cycles are interconnected, with a common stretch at the inspection and retrieval area, so that the AGVs can switch between the cycles to obtain a higher routing flexibility. In order to keep a complex system simple, a routing strategy is proposed that maintains a steady, regular, cyclic flow of all available vehicles. We develop, by means of a number theoretic concept, vehicle schedules that are collision-free for any cycle sequence. For a given production plan, we then present an efficient dynamic programming approach to check whether or not the required raw material (for machining parts) can be supplied in time to the various NC-machines. This method also solves an open problem in processor scheduling where a set of jobs with a restricted number of distinct processing times is to be scheduled before deadlines on m parallel processors.

A simulation study of multiple-load-carrying automated guided vehicles in a flexible manufacturing system

Abstract Although the technology exists for more advanced applications of automated guided vehicles in flexible manufacturing systems, the current employment of these vehicles in material handling generally subscribes to a simple mode of operation : single-load-carrying capacity for each vehicle and unidirectional traffic on each route of the system. Through a simulation programme, this study investigates the effect of several key factors related to the automated guided vehicles on the overall performance of a flexible manufacturing system. These are the number of pallets allowed in the system, the number of vehicles used and the carrying capacity of each and the input and output queue capacities of the machining stations; finally bidirectional traffic is allowed in some routes. The results show that there is a strong interaction among these factors and reveal their combined effects on the throughput from a small flexible manufacturing system. Upon the user's request, the simulation program also provides ...