A multi-attribute dispatching rule for automated guided vehicle systems

This paper considers the dispatching problem associated with operations of automated guided vehicles (AGVs). A multi-attribute dispatching rule for dispatching of an AGV is developed and evaluated. The multi-attribute rule, using the additive weighting method, considers three system attributes concurrently: the remaining space in the outgoing buffer of a workstation, the distance between an idle AGV and a workstation with a job waiting for the vehicle to be serviced, and the remaining space in the input buffer of the destination workstation of a job. A neural network approach is used to obtain dynamically adjusting attribute weights based on the current status of the manufacturing system. Simulation analysis of a job shop is used to compare the multi-attribute dispatching rule with dynamically adjusting attribute weights to the same dispatching rule with fixed attribute weights and to several single attribute rules. Results show that the multi-attribute dispatching rule with the ability to adapt attribute weights to job shop operational conditions provides a better balance among the performance measures used in the study.     

Simulation analysis of dispatching rules for an automated interbay material handling system in wafer fab

Here, the performance evaluation of a double-loop interbay automated material handling system (AMHS) in wafer fab was analysed by considering the effects of the dispatching rules. Discrete event simulation models based on SIMPLE++ were developed to implement the heuristic dispatching rules in such an AMHS system with a zone control scheme to avoid vehicle collision. The layout of an interbay system is a combination configuration in which the hallway contains double loops and the vehicles have double capacity. The results show that the dispatching rule has a significant impact on average transport time, waiting time, throughput and vehicle utilization. The combination of the shortest distance with nearest vehicle and the first encounter first served rule outperformed the other rules. Furthermore, the relationship between vehicle number and material flow rate by experimenting with a simulation model was investigated. The optimum combination of these two factors can be obtained by response surface methodology.     

Heavy traffic analysis of a single vehicle loop in an automated storage and retrieval system

We consider an automated storage/retrieval system in which cargo moves between the storage/retrieval machines and the system entrance/exit stations through a single automated vehicle loop. Past studies indicated that the cargo waiting time in the loop is affected by the dispatching rules, which govern the sequence of the cargo to be handled. In this paper, we show that the loop configuration, which has received little research attention, also has a big impact on the cargo waiting time. When the first-come-first-served dispatching rule is used, we derive the relationship between the number of stations and the ratio of the average cargo retrieval time to the average cargo storage time. When the first-encountered-first-served dispatching rule is used, we show that even the arrangement of the input channel and the output channel of a station can have significant impact on the cargo waiting time. Furthermore, we derive a formula for the vehicle visit rate for each station under heavy traffic conditions. This formula helps to explain the phenomenon that the waiting times at different stations can be very different even when the loop is symmetrically designed and the cargo arrival rates to the stations are similar. In addition to analytical models, we use simulations to evaluate the performance of different loop configurations. Our research suggests that a substantial improvement can be achieved by making proper adjustments to the loop configuration.     

A synchronized strategy to minimize vehicle dispatching time: a real example of steel industry

Time compression in supply chains is a crucial aspect involved in the integration of warehousing and transport operations in the manufacturing industries. Supply chain flows could be interrupted due to many sources of delays that lead to additional time in dispatching process and reduction in customer service level. The problem considered in this paper consists of long waiting times of loading vehicles inside the plant. This work presents a simulation-based study to minimize vehicle dispatching time in a steel wire plant. Value stream map is developed to present a system perspective of processes involved in the overall supply chain. Process activity mapping is completed to provide a step by step analysis of activities involved in the vehicle dispatch process. A simulation model is developed for the system and a new model is proposed to improve the delivery performance by minimizing vehicles’ waiting time.     

Synchronized strategy to minimize vehicle dispatching time:a real example of steel industry

Time compression in supply chains is a crucial aspect involved in the integration of warehousing and transport operations in the manufacturing industries.Supply chain flows could be interrupted due to many sources of delays that lead to additional time in dispatching process and reduction in customer service level.The problem considered in this paper consists of long waiting times of loading vehicles inside the plant.This work presents a simulation-based study to minimize vehicle dispatching time in a steel wire plant.Value stream map is developed to present a system perspective of processes involved in the overall supply chain.Process activity mapping is completed to provide a step by step analysis of activities involved in the vehicle dispatch process.A simulation model is developed for the system and a new model is proposed to improve the delivery performance by minimizing vehicles' waiting time.     

Effectiveness of vehicle reassignment in a large-scale overhead hoist transport system

This paper proposes an efficient vehicle reassignment dispatching rule and demonstrates the effectiveness of the rule using an overhead hoist transport (OHT) system for a semiconductor fabrication line. The OHT system has more than 150 OHT vehicles and its target vehicle utilization level is 70%. It allows direct delivery such that an inter-bay wafer movement can be accomplished by a single vehicle. Simulation analysis is used to compare the proposed rule with the shortest travel distance first (STDF) rule and existing reassignment-based rules. While STDF rule requires 170 vehicles for the target utilization level, the proposed vehicle reassignment rule requires only 161 vehicles. At the same time, the lead time and the variance of the lead time have been significantly reduced. The proposed rule also improves system performance compared to existing reassignment-based rules.     

Heuristic dispatching rule to maximize TDD and IDD performance

Although mean flow time and tardiness have been used for a long time as indicators in both manufacturing plants and academic research on dispatching rules, according to Theory of Constraints (TOC), neither indicator properly measures deviation from production plans. TOC claims that using throughput dollar-day (TDD) and inventory dollar-day (IDD) can induce the factory to take appropriate actions for the organization as a whole, and that these can be applied to replace various key performance indices used by most factories. However, no one has studied dispatching rules based on TDD and IDD performance indicators. The study addresses two interesting issues. (1) If TDD and IDD are used as performance indicators, do those dispatching rules that yield a better performance in tardiness and mean flow time still yield satisfactory results in terms of TDD and IDD performance? (2) Does a dispatching rule exist to outperform the current dispatching rules in terms of TDD and IDD performance? First, a TDD/IDD-based heuristic dispatching rule is developed to answer these questions. Second, a computational experiment is performed, involving six simulation examples, to compare the proposed TDD/IDD-based heuristic-dispatching rule with the currently used dispatching rules. Five dispatching rules, shortest processing time, earliest due date, total profit, minimum slack and apparent tardiness cost, are adopted herein. The results demonstrate that the developed TDD/IDD-based heuristic dispatching rule is feasible and outperforms the selected dispatching rules in terms of TDD and IDD.     

Analysis of Dispatching Rules of AGV Systems with Multiple Vehicles

We study automated guided vehicle systems that contain multiple vehicles. Each vehicle transports an item from a certain point to its destination. The inter-arrival time of items to each node is assumed to be independently and geometrically distributed. Each node has an infinite buffer capacity, and thus no item is lost. The deadhead time of the empty vehicle and the transportation time of the loaded vehicle are assumed to be arbitrarily distributed. We propose two empty vehicle dispatching policies, and numerically calculate the waiting time distributions of the items for each policy using a state-space reduction technique for Markov chains. Several examples are given to demonstrate the advantages and disadvantages of each policy.     

电动汽车智能充放电控制与应用综述

随着电动汽车规模的增大,电动汽车接入电网对电力系统运行与控制的影响不容忽视。电动汽车作为一种可控负荷,对其进行充放电控制可以有效削弱充电负荷带来的不利影响,同时还能起到削峰填谷、促进新能源消纳的作用,这将成为电力系统运行控制的一种重要手段。给出了充电负荷建模需要考虑的因素,总结了建立电动汽车负荷预测模型的方法。归纳了电动汽车参与电网调度的可行方法,并分析了不同方法的特点。同时,为了提高电动汽车参与调度的积极性,介绍了用区块链完成电动汽车电力交易的架构与方法。最后,对尚未解决的问题和可能的研究方向进行了讨论。     

A simulation study of new multi-objective composite dispatching rules,CONWIP, and push lot release in semiconductor fabrication

This paper evaluates dispatching rules and order release policies in two wafer fabrication facilities (thereafter referred to as ‘fab’) representing ASIC (application specific integrated circuit) and low-mix high-volume production. Order release policies were fixed-interval (push) release, and constant work-in-process (CONWIP) (pull) policy. Following rigorous fab modelling and statistical analysis, new composite dispatching rules were found to be robust for average and variance of flow time, as well as due-date adherence measures, in both production modes.     

A beam search-based algorithm and evaluation of scheduling approaches for flexible manufacturing systems

This paper presents a new algorithm for the flexible manufacturing system (FMS) scheduling problem. The proposed algorithm is a heuristic based on filtered beam search. It considers finite buffer capacity, routing and sequence flexibilities and generates machine and automated guided vehicle (AGV) schedules for a given scheduling period. A new deadlock resolution mechanism is also developed as an integral part of the proposed algorithm. The performance of the algorithm is compared with several machine and AGV dispatching rules using mean flow time, mean tardiness and makespan criteria. It is also used to examine the effects of scheduling factors (i.e., machine and AGV load levels, routing and sequence flexibilities, etc.) on the system performance. The results indicate that the proposed scheduling algorithm yields considerable improvements in system performance over dispatching rules under a wide variety of experimental conditions.     

A coloured Petri net-based hybrid heuristic search approach to simultaneous scheduling of machines and automated guided vehicles

To achieve a significant improvement in the overall performance of a flexible manufacturing system, the scheduling process must consider the interdependencies that exist between the machining and transport systems. However, most works have addressed the scheduling problem as two independent decision making problems, assuming sufficient capacity in the transport system. In this paper, we study the simultaneous scheduling (SS) problem of machines and automated guided vehicles using a timed coloured Petri net (TCPN) approach under two performance objectives; makespan and exit time of the last job. The modelling approach allows the evaluation of all the feasible vehicle assignments as opposed to the traditional dispatching rules and demonstrates the benefits of vehicle-controlled assignments over machine-controlled for certain production scenarios. In contrast with the hierarchical decomposition technique of existing approaches, TCPN is capable of describing the dynamics and evaluating the performance of the SS problem in a single model. Based on TCPN modelling, SS is performed using a hybrid heuristic search algorithm to find optimal or near-optimal schedules by searching through the reachability graph of the TCPN with heuristic functions. Large-sized instances are solved in relatively short computation times, which were a priori unsolvable with conventional search algorithms. The algorithm’s performance is evaluated on a benchmark of 82 test problems. Experimental results indicate that the proposed algorithm performs better than the conventional ones and compares favourably with other approaches.     

Modelling of an automated guided vehicle system (AG VS) in a just-in-time (JIT) environment

Like other production systems, just-in-time (JIT) systems need to address the issue of material transport between workstations such as those served by automated guided vehicles (AGVs). Unlike other production systems, however, the JIT philosophy imposes strict requirements on inventory levels and supply-demand protocols which render conventional AGV delivery strategies ineffective and counter-productive. This paper describes the modelling of an AGV system (AGVS) in a JIT environment in a way that is consistent with JIT principles. The influence of a ‘JIT perspective’ is emphasized throughout the model by introducing threshold values for both input and output queues, performance measures that emphasize lower inventories in addition to transport efficiency, and a new dispatching rule that implements better inventory and transport control. The dispatching rule is shown to perform better in a JIT environment than previously developed AGV dispatching rules in both transport and logistic criteria.     

A study on the performance of scheduling rules in buffer-constrained dynamic flowshops

Most studies on scheduling in manufacturing systems using dispatching rules deal with jobshops, while there are only few reports dealing with dynamic flowshops. It is known that the performance of many dispatching rules in dynamic jobshops is different from that in dynamic flowshops. Moreover, many research reports assume that there are no buffer constraints in the shop, and even those reports dealing with buffer-constrained shops present the evaluation of existing dispatching rules for unconstrained shops in the context of buffer constraints with the consideration of a limited number of objectives of scheduling. In this study, we deal with the problem of scheduling in dynamic flowshops with buffer constraints. With respect to different time-based objectives, the best dispatching rules for scheduling in unconstrained shops have been identified from the existing literature. In addition, two new dispatching rules specially designed for flowshops with buffer constraints are proposed. All dispatching rules under consideration are evaluated in dynamic flowshops with buffer constraints on the basis of an extensive simulation study covering different levels of buffer constraints, shop load or utilization, and missing operations in flowshops. The proposed rules are found to perform better than the existing dispatching rules in buffer-constrained flowshops with respect to many measures of performance.     

Interaction between dispatching and next station selection rules in a dedicated flexible manufacturing system

The interaction between nine dispatching and four next station selection rules in a relatively large dedicated FMS is investigated. The FMS contains 16 workstations with local buffers, nine load/unload stations, and produces six different part types. A simulation model is used, and analysed as a steady-state model. Flowtime is taken as the main criterion. It is found that WINQ (select the station whose input buffer contains the smallest amount of work) dominates, performing significantly better than the other next station selection rules considered across all dispatching rules, with few significant differences between dispatching rules when combined with WINQ. SIO/TOT (select the job with the smallest ratio obtained by dividing the processing time of the imminent operation by the total processing time for the part) performs marginally better than the other dispatching rules, particularly SIO (select the job with the shortest imminent processing time). Reasons for when a next station selection rule is more important than a dispatching rule, and vice versa, are discussed.     

基于遗传算法的共享助力车调度问题研究

为了减少调度运营成本,减少调度时间,研究共享助力车的调度问题。将助力车调度和电池配送统一进行,考虑载重对燃油调度车的油耗影响,以燃油调度车固定使用成本和耗油成本最小为目标函数,构建助力车重分配的调度模型。通过AP算法对大范围内的电子围栏进行区域划分,确定助力车的服务范围和调度中心选址的基础上,用遗传算法对各个区域分别求解最小成本的路径规划方案。用算例验证了本模型与算法的有效性和可行性。     

A hybrid modelling approach to the design of an AGV-based material handling system for an FMS

The problem of organizing and controlling the material handling activity in an AGV-based material handling system for a flexible manufacturing system involves several decisions such as the number of vehicles required for the system, the layout of the tracks, the dispatching rules for the vehicles and the provision of control zones and buffers. This paper demonstrates the use of a two-stage approach for solving the problem. The required number of vehicles is estimated using an analytical model in the first stage. In the next stage, the effects of AGV failures and AGV dispatching rules on the system performance are observed through simulation studies based on which the AGV dispatching rule can be chosen.     

A construction algorithm for designing guide paths of automated guided vehicle systems

A construction algorithm is suggested to design guide path networks for automated guided vehicle systems (AGVSs). This study uses the total travel time, including waiting and interference time, of vehicles as the decision criteria for determining the direction of path segments on unidirectional guide path layouts. The Q-learning technique is applied to estimate the travel times of vehicles on path segments. Computational experiments were performed to evaluate the performance of the proposed algorithm. The simulation results showed that the proposed algorithm is superior to Kim & Tanchoco's (1993) algorithm in terms of the average travel time, the interference time and the number of deliveries.     

Effect of load,processing time and due date variation on the effectiveness of scheduling rules

In real manufacturing environments, variations in production factors (i.e. processing time, demand, due-dates) are inevitable facts. All these dynamic changes, together with random disturbances (e.g. machine breakdowns) can seriously affect the system performance. In this paper we focus on load, processing time and due date variation and analyse their impacts on a scheduling system. Specifically, we investigate the impact of variation on dispatching policies in a job shop environment via simulation. The statistical analysis of the results leads to two major conclusions: first, the relative performance of rules is not threatened much by PV (processing time variation), LV (load variation) or DDV (due date variation) -- a result that can be a consolation for practitioners in the field. Secondly, the performance of the rules deteriorates, in particular at high levels of PV, LV and DDV -- a result that can provide new insights into the problem and produces useful information for researchers in their continuous effort to develop better dispatching rules.     

Simulation-based regression analysis for the rack configuration of an autonomous vehicle storage and retrieval system

In this paper, a simulation-based regression analysis for the rack configuration of an autonomous vehicle storage and retrieval system (AVS/RS) is presented. The aim of this study is to develop mathematical functions for the rack configuration of an AVS/RS that reflects the relationship between the outputs (responses) and the input variables (factors) of the system under various scenarios. In the regression model, we consider five outputs: the average cycle time of storage and retrieval transactions, the average waiting time for vehicle transactions, the average waiting time of vehicles (transactions) for the lift, the average utilisation of vehicles and the average utilisation of the lifts. The input variables are the number of tiers, aisles and bays that determine the size of the warehouse. Thirty regression models are developed for six warehouse scenarios. The simulation model of the system is developed using ARENA 12.0 commercial software and the statistical analyses are completed using MINITAB statistical software. Two different approaches are used to fit the regression functions–stepwise regression and the best subsets. After obtaining the regression functions, we optimise them using the LINGO software. We apply the approach to a company that uses AVS/RS in France.