FMS Environment Research Articles

Hybridised ant colony optimisation for convoy movement problem

The convoy movement problem (CMP) is a routing and scheduling problem for military convoys across a network where encounters of vehicles in the network are restricted and the movements of vehicles must occur within given time windows. This problem finds applications in many real-world problems such as scheduling and routing freight trains along a single line network, scheduling aircraft landings on runways, routing of automated guided vehicles in an FMS environment, handling baggage along a common automated conveyor belt system. The CMP is known to be hard computationally. Therefore, heuristic algorithms are the key to obtain quick and reliable solutions. This paper proposes a novel hybridised ant colony algorithm that combines a local search procedure with the ant colony optimisation to solve large and dense instances of the problem. We generate a new dataset which includes small to large instances with a wide range of arc densities to simulate real-world instances. We run a comprehensive computational experiment on our generated dataset to examine the efficiency of our approach. Our experiments show that our approach well handles large and dense instances with reasonably fine solutions. Furthermore, we show the importance of using a good seed solution for initialisation of the algorithm. We analyse the convergence of the algorithm for this seed solution and hybridising the ant colony algorithm with a local search procedure.

Design and Fabrication of Flexible Management Robot Vehicle AGV

This project is focusing on developing a multifunctional automated guided vehicle. This AGV system has to be obtained by the major part of all workstations into shop floor. This type of vehicle is assigned to all over the shop floor. This article has presented as an analytical concept of design a AGV system. The concept model has obtained a performing of design procedure which consists of two steps, ‘selection of feasible zones’ and ‘selection of final guide path.’This AGV for all manufacturing industry which contains the features like it can carry the finished component pallets, collision detection and computer control. A command based or teach pendent interface based wireless control is provided to control the robot. A collision detection sensor ensures robot may not hit any obstacles in its path. The robot has compact size which can easily move on rough area. In this project we describe the development of automated guided vehicle that provides you with a FMS environment for modeling and prototyping automated guided vehicles

GTA-based framework for evaluating the effectiveness of material handling equipment's in FMS environment

In this paper, a methodology to evaluate the effectiveness of material handling equipments variables using graph theoretic approach (GTA) is presented. Variables affecting the effectiveness of material handling equipments and their interactions are analysed by developing a mathematical model using GTA. Permanent function performance index is obtained from the matrix model developed from the digraph. This permanent function value ranks the equipment variables which help in selection of optimum process parameters during flexible and automated material handling system adoption.

GTA-based framework for evaluating the effectiveness of material handling equipment's in FMS environment

GTA-based framework for evaluating the effectiveness of material handling equipment's in FMS environment

A Trajectory Based Methods for Parallel Scheduling of Machines and AGV’S in an FMS Environment

A Trajectory Based Methods for Parallel Scheduling of Machines and AGV’S in an FMS Environment

Makespan minimisation for pre-emptive scheduling of mobile robots in FMS environment

Modern manufacturing models demand customisation and service orientation. The generations of mobile robots will hence have to cope with more complex tasks and rapidly adapt to new situations. With the high level of flexibility, the mobile robots are able to not only transport materials as conventional transporting robots, but also perform manufacturing tasks at some certain machines using their mounted manipulation arms. This paper considers the problem of simultaneous scheduling of machines and such mobile robots in a flexible manufacturing system. The pre-emption occurs when manufacturing tasks are interrupted to allow the mobile robots to carry out the transport. The performance criterion is to minimise the makespan. A genetic-algorithm-based heuristic is developed to find near-optimal solutions. To evaluate the performance of the proposed heuristic, a mixed-integer programming model is also presented. A numerical example and computational experiments are conducted to demonstrate the effectiveness of the proposed approaches.

Utilization of AGVs and Machines in FMS Environment

Automatic guided vehicle systems are now well known and recognized in automated material handling systems, FMS and also in container handling applications. It improves response time for material movement. It is an efficient, dependable and versatile material handling solution. AGVs consist of one or more computer-controlled wheel based load carriers that run on the plant floor without the need for a driver. These are designed to perform their operations without direct human guidance and are used in a wide variety of industrial applications. This paper presents a review on design and control of automated guided vehicle systems. The paper present a methodology to unify various lines of research related to AGVs and to suggest directions for future work for most key related issue i.e., including vehicle scheduling. Various types of scheduling problems are solved in different job shop environments, vehicle routing, guide-path design, vehicle dispatching. The prior objective of this paper is to extend previous research by examining the effects of scheduling rules and routing flexibility on the performance of a constrained and utilization of AGVs and machines.

Dynamic Task Assignment of Autonomous Distributed AGV in an Intelligent FMS Environment

Dynamic Task Assignment of Autonomous Distributed AGV in an Intelligent FMS Environment

Simultaneous scheduling of machines and vehicles in an FMS environment with alternative routing

Scheduling of flexible manufacturing systems is a well-known NP-hard problem which is very complex, due to additional considerations like material handling, alternative routing, and alternative machines. Improvement in the performance of a flexible manufacturing system can be expected by efficient utilization of its resources, by proper integration and synchronization of their scheduling. Differential evolution is a powerful tool which proved itself as a better alternative for solving optimization problems like scheduling. In this paper, the authors addressed simultaneous scheduling of both machines and material handling system with alternative machines for the makespan minimization objective. The authors proposed a machine selection heuristic and a vehicle assignment heuristic which are incorporated in the differential evolution approach to assign the tasks, to appropriate machine and vehicle, and to minimize cycle time.

A Real Time Mechanism for Operation Assignment in a Flexible Manufacturing System: A Combined Operations Splitting and Balanced Workload Approach

In a flexible manufacturing environment, the determination of operational sequences is very important for the balanced utilization of resources and the optimal throughput of the system. In this paper, a real time scheduling approach for assignment of operations to machines in terms of minimization of flow distances, operational time and balance of workload is proposed through a fourphase heuristic. In phase 1, primary assignment of operations to machines based on the minimization of flow distances is done. Phase 2 involves final assignment of operations by assigning highest time consuming operations to quick processing machines. Phase 3 involves balance of workload by shifting operations among the machines. Phase 4 involves minimization of inter machine flow distances among machines. In order to show the capability of the proposed real-time scheduling heuristic, a reasonable sample of nineteen parts and twelve machines in a FMS environment is considered and solved. Numerical results show that the real time scheduling heuristic is extremely adaptive and highly time efficient even for solving a system with large number of parts and machines. The method is highly time efficient even for solving an FMS system with large number of parts and machines within a reasonable time.

Simultaneous scheduling of parts and automated guided vehicles in an FMS environment using adaptive genetic algorithm

Simultaneous scheduling of parts and automated guided vehicles in an FMS environment using adaptive genetic algorithm

A multi-objective model of operation allocation and material handling system selection in FMS design

This paper proposes a method for simultaneously determining the operation allocation and material handling system selection in an FMS environment with multiple performance objectives. The 0–1 integer programming model is developed to select machines, assign operations of part types to the selected machines, and assign material handling equipment to transport the parts from machine to machine, as well as to handle the part at a given machine. The selection is based on the compatibility between the material handling equipment and the parts. The objective is to minimize the costs of operations, material handling, machine setups, and to maximize the part–equipment compatibility. A numerical example has been presented to illustrate the application of model.

Reactive scheduling in a dynamic and stochastic FMS environment

In this paper, we study the reactive scheduling problems in a dynamic and stochastic manufacturing environment. Specifically, we develop a simulation-based scheduling system for flexible manufacturing systems. We also propose several reactive scheduling policies (i.e. when-to-schedule and how-to-schedule policies) and test their performances under various experimental conditions, processing time variations, and machine breakdowns. Moreover, we compare offline and online scheduling schemes in a dynamic manufacturing environment. The results of extensive simulation experiments indicate that the variable-time-response is better than the fixed-time-response. The full scheduling scheme generally performs better than the partial scheduling. Finally, the online scheduling is more robust to uncertainty and variations in processing times than the optimum-seeking offline scheduling. A comprehensive bibliography is also provided in the paper.

Mathematical modelling and heuristic approaches to operation scheduling problems in an FMS environment

This paper addresses an operation scheduling problem with the objective of minimizing total tardiness in a flexible manufacturing system with setup time consideration. The addressed problem is first described as a 0?1 integer programming model, and is then solved optimally. Subsequently, a heuristic is proposed to solve the problem in an acceptable running time. The heuristic begins on a schedule generator called ESCH to obtain an initial solution; then two procedures are designed to improve the solution quality. One is a sequence-improving procedure (SIP) for determining a better performance schedule from a certain routing plan; the other is a routing-exchanging procedure (REP) for selecting a good routing plan. Both procedures are achieved by simulated annealing. Computational experiments show that the proposed simulated annealing based heuristic performs well with respect to solution accuracy and efficiency.

Dynamic process planning system for a machining center in an FMS environment

A dynamic process planning system under a competitive environment for the machining operations on a pallet in an FMS is proposed. This system consists of four sub-systems, and is developed as a hierarchical system, with a strategic decision under the minimum elapsed time criterion. Finally, an actual system architecture of the proposed dynamic process planning model is shown.

A branch and bound based heuristic for multi-product resource constrained scheduling problem in FMS environment

This paper addresses an inter-dependent multiple-product resource-constrained scheduling problem with the objective of makespan minimization in a flexible manufacturing system with resource flexibility. Both consumable and non-consumable resources are considered along with their alternative types and constrained utilization rates. A 0–1 integer linear programming formulation is presented for the problem. The complexity of the problem is observed to be at increase with the availability of alternate resources for product operations. A branch and bound based heuristic is proposed as a solution methodology. A numerical example is presented to illustrate the problem and the effectiveness of the heuristic.

Rescheduling frequency in an FMS with uncertain processing times and unreliable machines

Abstract This paper studies the scheduling/rescheduling problem in a multi-resource FMS environment. Several reactive scheduling policies are proposed to address the effects of machine breakdowns and processing time variations. Both off-line and on-line scheduling methods are tested under a variety of experimental conditions. The performance of the system is measured for mean tardiness and makespan criteria. The relationships between scheduling frequency and other scheduling factors are investigated. The results indicated that a periodic response with an appropriate period length would be sufficient to cope with interruptions. It was also observed that machine breakdowns have more significant impact on the system performance than processing time variations. In addition, dispatching rules were found to be more robust to interruptions than the optimum-seeking off-line scheduling algorithm. A comprehensive bibliography is also included in the paper.

A genetic algorithm for scheduling flexible manufacturing systems

General job shop scheduling and rescheduling with alternative route choices for an FMS environment is addressed in this paper. A genetic algorithm is proposed to derive an optimal combination of priority dispatching rules “pdrs” (independentpdrs one each for one Work Cell “WC”), to resolve the conflict among the contending jobs in the Giffler and Thompson “GT” procedure. The performance is compared with regard to makes-pan criteria and computational time. The optimal WCwise-pdr is proved to be efficient in providing optimal solutions in a reasonable computational time. Also, the proposed GA based heuristic method is extended to revise schedules on the arrival of new jobs, and on the failure of equipment to address the dynamic operation mode of flexible manufacturing systems. An iterative search technique is proposed to find the best route choice for all operations to provide a feasible and optimal solution. The applicability and usefulness of the proposed methodology for the operation and control of FMS in real-time are illustrated with examples. The scope of the genetic search process and future research directions are discussed.

Determination of optimal AGV fleet size for an FMS

The required number of AGVs necessary to perform a given level of material handling task in an FMS environment is determined using analytical and simulation modelling. The analytical method involves consideration of load handling time, empty travel time, and waiting and blocking time. Load handling time is computed from given system parameters. Determination of empty vehicle travel is difficult due to the inherent randomness of an FMS. Several research studies for this purpose are discussed and a new model is proposed. It entails formulation of a mixed integer programme with an objective of minimizing empty trips. The constraints are in the form of upper and lower bounds placed on the total number of empty trips starting from or ending at a load transfer station. The phenomena of vehicle waiting and blocking are also discussed. The cumulative impact of these three time estimates are then translated into an initial estimate of AGV fleet size as predicted by individual models. The method is applied to an illustrative example. Finally, simulation methodology is used to validate the initial estimates of fleet size. The results indicate that the different models either under-estimate or over-estimate the actual number of vehicles required in the system. The proposed model, though under-estimates the minimum AGV requirement, yet provides results which are close to the simulation results. Hence, it can be used as an analytical tool prior to the simulation phase of AGVS design.

Simultaneous scheduling of machines and automated guided vehicles

Abstract This paper is an attempt to make scheduling of AGVs an integral part of the overall scheduling activity in an FMS environment. The sequence-dependent nature of travel times for the deadheading trips between successive loaded trips of the AGVs increases the problem difficulty. The problem is decomposed into two subproblems, and previous work on machine scheduling and vehicle scheduling has been exploited to arrive at an iterative heuristic procedure where makespan is the performance criterion. At each iteration, a new machine schedule, generated by a heuristic procedure, is investigated for its feasibility to the vehicle scheduling subproblem. The operation completion times obtained from the machine schedule are used to construct time windows for each material handling trip, and the second subproblem is handled as a sliding time window problem. A set of problems are solved to analyse the impact of the process times/travel times ratio on the performance of the procedure. The interaction between the...