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An important issue in the design of a flexible manufacturing system (FMS) is the operational control of the materials handling subsystem, through which reparts are conveyed from one work station to the next. A popular type of materials handling device is the automatic guided vehicle (AGV), which has been widely adopted in FMS because of its versatility and speed. This paper presents a simulation study to investigate the effects of different AGV dispatching rules on the performance of an FMS under various operating conditions. The dispatching rules studied are: FAFS — select the first available AGV; MIT — select the AGV with the most idle time; STT — select the AGV with the shortest travel time; and LTT — select the AGV with the longest travel time. The performance measures adopted are: overall production rate of the system; mean work station utilisation; and mean AGV utilisation. Although the results obtained are related to the specific FMS layout studied in this paper, it is believed that the inferences drawn from them are applicable to any FMS with similar layout structure and can provide useful guidelines for AGV design.

This paper aims to propose a parallel automated assembly line system to produce multiple products in a semi-continuous system.

The control system developed in this research consists of a manufacturing system for two-level hierarchical dynamic decisions of autonomous/automated/automatic-guided vehicles (AGVs) dispatching/next station selection and machining schedules and a station control scheme for operational control of machines and components. In this proposed problem, the assignment of multiple AGVs to different assembly lines and the semi-continuous stations is a critical objective. AGVs and station scheduling decisions are made at the assembly line level. On the other hand, component and machining resource scheduling are made at the station level.

The proposed scheduler first decomposes the dynamic scheduling problems into a static AGV and machine assignment during each short-term rolling window. It optimizes weighted completion time of tasks for each short-term window by formulating the task and resource assignment problem as a minimum cost flow problem during each short-term scheduling window. A comprehensive decision making process and heuristics are developed for efficient implementation. A simulation study is worked out for validation.

Several assembly lines are configured to produce multiple products in which the technologies of machines are shared among the assembly lines when required. The sequence of stations is pre-specified in each assembly line and the components of a product are kept in machine magazine. The transportation between the stations in an assembly line (intra assembly line) and among stations in different assembly lines (inter assembly line) are performed using AGVs.

Process mining has emerged in the last decade as one of the most promising tools to discover and understand the actual execution of processes. This paper addresses the application of process mining techniques to analyze the performance of automatic guided vehicles (AGVs) in one of the Body in White circuits of the factory that Stellantis has in Vigo, Spain.

Standard process mining discovery and conformance algorithms are applied to analyze the different AGV execution paths, their lead times, main sources and identify any unexpected potential situations, such as unexpected paths or loops.

Results show that this method provides very useful insights which are not evident for logistics technicians. Even with such automated devices, where the room for decreased efficiency can be apparently small, process mining shows there are cases where unexpected situations occur, leading to an increase in circuit times and different variants for the same route, which pave the road for an actual improvement in performance and efficiency.

This paper provides evidence of the usefulness of applying process mining in manufacturing processes. Practical applications of process mining have traditionally been focused on processes related to services and management, such as order to cash and purchase to pay in enterprise resource planning software. Despite its potential for use in industrial manufacturing, such contributions are scarce in the current state of the art and, as far as we are aware of, do not fully justify its application.

Automatic guided vehicles (AGVs) are widely used in industrial fields. But most control strategies merely take the lateral force into consideration. This will reduce the accuracy, stability and robustness and will pay additional costs. Therefore, this paper aims to design a control strategy that initially considers lateral force. Thereby, it will improve the accuracy, stability and robustness and reduce the overall cost of AGV.

To achieve the goal of comprehensively improving AGV operating performance, this paper presents a new scheme, combining the dual-wheeled chassis model (DCM) using proportional–integral–differential (PID) control and a supporting quick response (QR) code navigation technology. DCM is the core, which analyzes the deviation caused by lateral force. Then, DCM with PID control by the control law is combined to suppress the errors. Meanwhile, QR code navigation technology provides effective data support for the control strategy.

Most AGV experiments are carried out in a standard environment. However, this study prepares unfavorable scenarios and operating conditions for the experiments that generate detailed data to demonstrate this study’s strategy, which can make an accurate, stable and robust operation process of AGV under various adverse environmental and mechanical factors.

This study proposed DCM, fully considering lateral force and converting the force into velocity. Subsequently, PID controls the speed of two wheels to reduce the error. QR code provides an efficient and low – cost way to obtain information. The three are cleverly combined as a novel industrial AGV control strategy, which can comprehensively improve the operating performance while reducing overall costs.

The automated guided vehicle (AGV), one of the popular new technologies of the 1980s, is now seen more as a part of automated handling systems not a standalone concept. It is now applied across a range of industries and several applications are described. At Denso Manufacturing, AGVs are used as tugs to tow trailers delivering components to production lines, while at Perkins Engines they carry both part kits and finished engines to and from assembly dressing lines. At Kodak they handle heavy paper rolls serving coating machines. These applications use the traditional embedded wire navigation technology. Other guidance techniques are described including the more flexible laser scanner, which is being applied in a Belgian fruit and vegetable market to transport pre‐packed products to dispatch lines. Details are also given of an automatic docking system and a standard pallet truck that is available as a complete automated package with laser guidance.

This paper aims to focus on cybernetic transportation systems (CTS) due to their effectiveness for solving mobility problems in cities. A new mobility concept is proposed which allows to attain the same flexibility of the private passenger car but with much less nuisances. It is based on small semi‐autonomous electric vehicles, which may be used to complement mass public transportation, by providing passenger service for any location at any time.

A set of automatic guided vehicles for public transportation are described. Two different control paradigms of the fleet are compared: centralized vs distributed control.

The pros and cons of both control approaches are highlighted so as to support decisions about the configuration of a CTS for people transportation on public places.

The paper provides a new offer of transportation for people in short path cities downtown or public gardens, in order to move people based on sustainable and efficient public transportation systems.

This study aims to address the challenge of automatic guided vehicle (AGV) scheduling for parcel storage and retrieval in an intelligent warehouse.

This study presents a scheduling solution that aims to minimize the maximum completion time for the AGV scheduling problem in an intelligent warehouse. First, a mixed-integer linear programming model is established, followed by the proposal of a novel genetic algorithm to solve the scheduling problem of multiple AGVs. The improved algorithm includes operations such as the initial population optimization of picking up goods based on the principle of the nearest distance, adaptive crossover operation evolving with iteration, mutation operation of equivalent exchange and an algorithm restart strategy to expand search ability and avoid falling into a local optimal solution. Moreover, the routing rules of AGV are described.

By conducting a series of comparative experiments based on the actual package flow situation of an intelligent warehouse, the results demonstrate that the proposed genetic algorithm in this study outperforms existing algorithms, and can produce better solutions for the AGV scheduling problem.

This paper optimizes the different iterative steps of the genetic algorithm and designs an improved genetic algorithm, which is more suitable for solving the AGV scheduling problem in the warehouse. In addition, a path collision avoidance strategy that matches the algorithm is proposed, making this research more applicable to real-world scheduling environments.

Argues that the design of the Volvo Uddevalla plant may be described as a process with an “internal logic” in which design options were eliminated through irreversible design decisions until only one alternative remained ‐ an unorthodox alternative comprising, for example, long cycle time work never used before for full‐scale production of automobiles. Contends that the most innovative features of the Uddevalla plant ‐ i.e. the detailed layout in the assembly workshops and the corresponding unorthodox production principles used ‐ were in many respects an unanticipated outcome of the design process. Pre‐existing gross layout of the plant as well as the interaction between the materials feeding techniques adopted and the operation of the automated guided vehicle system. When this was perceived by the Volvo managers, the design process had passed the point of no return, i.e. the investments made and lack of time prevented regression to more traditional layouts and production principles.

The Kansas City Division of Allied Signal Aerospace operates a flexible manufacturing system which is described. Its components ‐ machining centres, co‐ordinate measuring machines, AGVs and materials handling systems, wash station, central chip and coolant system, systems hardware, control system ‐ are outlined. The process flow activities are described along with the benefits of the system.