A study of the robustness of the group scheduling method using an emulation of a complex FMS

International audienceIn the field of predictive-reactive scheduling methods, group sequencing is reputed to be robust (in terms of uncertainties absorption) due to the flexibility it adds with regard to the sequence of operations. However, this assumption has been established on experiments made on simple theoretical examples. The aim of this paper is to carry out experimentation on a complex flexible manufacturing system in order to determine whether or not the flexibility of the group scheduling method can in fact absorb uncertainties. In the study, transportation times of parts between machines are considered as uncertain. Simulation studies have been designed in order to evaluate the relationship between flexibility and the ability to absorb uncertainties. Comparisons are made between schedules generated using the group sequencing method with different flexibility levels and a schedule with no flexibility. A last schedule takes into account uncertainties whereas schedules generated using the group sequencing method do not. As it is the best possible schedule, it provides a lower bound and enables to calculate the degradation of performance of calculated schedules. The results show that group sequencing perform very well, enabling the quality of the schedule to be improved, especially when the level of uncertainty of the problem increases. The results also show that flexibility is the key factor for robustness. The rise in the level of flexibility increases the robustness of the schedule towards the uncertainties

Tool flow management in batch manufacturing systems for cylindrical components

The objective of the research is to study the design of and operating strategies for advanced tool flow systems in highly automated turning systems. A prototype workstation has been built to aid this process. The thesis consists of three main parts. In the first part the current flexible manufacturing technology is reviewed with emphasis laid on tool flow and production scheduling problems. The 'State-of-the-Art' turning systems are studied, to highlight the requirement of the computer modelling of tool flow systems. In the second part, the design of a computer model using fast modelling algorithms is reported. The model design has concentrated on the tool flow system performance forecasting and improving. Attention has been given to the full representation of highly automatic features evident in turning systems. A number of contemporary production scheduling rules have been incorporated into the computer model structure, with the objectives of providing a frontend to the tool flow model, and to examine the tool flow problems interactively with the production scheduling rules. The user-interface of the model employs conversational type screens for tool flow network specification and data handling, which enhances its user friendliness greatly. An effective, fast, and easy to handle data base management system for tool, part, machine data entries has been· built up to facilitate the model performance. The third part of the thesis is concerned with the validation and application of the model with industry supplied data to examine system performance, and to evaluate alternative strategies. Conclusions drawn from this research and the recommendations for further work are finally indicated

The investigation of the effect of scheduling rules on FMS performance

The application of Flexible Manufacturing Systems (FMSs) has an effect in competitiveness, not only of individual companies but of those countries whose manufactured exports play a significant part in their economy (Hartley, 1984). However, the increasing use of FM Ss to effectively provide customers with diversified products has created a significant set of operational challenges for managers (Mahmoodi et al., 1999). In more recent years therefore, there has been a concentration of effort on FMS scheduling without which the benefits of an FMS cannot be realized. The objective of the reported research is to investigate and extend the contribution which can be made to the FMS scheduling problem through the implementation of computer-based experiments that consider real-time situations. [Continues.

Analusis and Modeling of Flexible Manufacturing System

Analysis and modeling of flexible manufacturing system (FMS) consists of scheduling of the system and optimization of FMS objectives. Flexible manufacturing system (FMS) scheduling problems become extremely complex when it comes to accommodate frequent variations in the part designs of incoming jobs. This research focuses on scheduling of variety of incoming jobs into the system efficiently and maximizing system utilization and throughput of system where machines are equipped with different tools and tool magazines but multiple machines can be assigned to single operation. Jobs have been scheduled according to shortest processing time (SPT) rule. Shortest processing time (SPT) scheduling rule is simple, fast, and generally a superior rule in terms of minimizing completion time through the system, minimizing the average number of jobs in the system, usually lower in-process inventories (less shop congestion) and downstream idle time (higher resource utilization). Simulation is better than experiment with the real world system because the system as yet does not exist and experimentation with the system is expensive, too time consuming, too dangerous. In this research, Taguchi philosophy and genetic algorithm have been used for optimization. Genetic algorithm (GA) approach is one of the most efficient algorithms that aim at converging and giving optimal solution in a shorter time. Therefore, in this work, a suitable fitness function is designed to generate optimum values of factors affecting FMS objectives (maximization of system utilization and maximization of throughput of system by Genetic Algorithm (GA) approach

Réduction du comportement myope dans le contrôle des FMS : une approche semi-hétérarchique basée sur la simulation-optimisation

Heterarchical-based control for flexible manufacturing systems (FMS) localizes control capabilities in decisional entities (DE), resulting in highly reactive and low complex control architectures. However, these architectures present myopic behavior since DEs have limited visibility of other DEs and their behavior, making difficult to ensure certain global performance. This dissertation focuses on reducing myopic behavior. At first, a definition and a typology of myopic behavior in FMS is proposed. In this thesis, myopic behavior is dealt explicitly so global performance can be improved. Thus, we propose a semi-heterarchical architecture in which a global decisional entity (GDE) deals with different kinds of myopic decisions using simulation-based optimization (SbOs). Different optimization techniques can be used so myopic decisions can be dealt individually, favoring GDE modularity. Then, the SbOs can adopt different roles, being possible to reduce myopic behavior in different ways. More, it is also possible to grant local decisional entities with different autonomy levels by applying different interaction modes. In order to balance reactivity and global performance, our approach accepts configurations in which some myopic behaviors are reduced and others are accepted. Our approach was instantiated to control the assembly cell at Valenciennes AIPPRIMECA center. Simulation results showed that the proposed architecture reduces myopic behavior whereby it strikes a balance between reactivity and global performance. The real implementation on the assembly cell verified the effectiveness of our approach under realistic dynamic scenarios, and promising results were obtained.Le contrôle hétérarchique des systèmes de production flexibles (FMS) préconise un contrôle peu complexe et hautement réactif supporté par des entités décisionnelles locales (DEs). En dépit d'avancées prometteuses, ces architectures présentent un comportement myope car les DEs ont une visibilité informationnelle limitée sue les autres DEs, ce qui rend difficile la garantie d'une performance globale minimum. Cette thèse se concentre sur les approches permettant de réduire cette myopie. D'abord, une définition et une typologie de cette myopie dans les FMS sont proposées. Ensuite, nous proposons de traiter explicitement le comportement myope avec une architecture semi-hétérarchique. Dans celle-ci, une entité décisionnelle globale (GDE) traite différents types de décisions myopes à l'aide des différentes techniques d'optimisation basée sur la simulation (SbO). De plus, les SbO peuvent adopter plusieurs rôles, permettant de réduire le comportement myope de plusieurs façons. Il est également possible d'avoir plusieurs niveaux d'autonomie en appliquant différents modes d'interaction. Ainsi, notre approche accepte des configurations dans lesquelles certains comportements myopes sont réduits et d'autres sont acceptés. Notre approche a été instanciée pour contrôler la cellule flexible AIP- PRIMECA de l'Université de Valenciennes. Les résultats des simulations ont montré que l'architecture proposée peut réduire les comportements myopes en établissant un équilibre entre la réactivité et la performance globale. Des expérimentations réelles ont été réalisées sur la cellule AIP-PRIMECA pour des scenarios dynamiques et des résultats prometteurs ont été obtenus

Platooning-based control techniques in transportation and logistic

This thesis explores the integration of autonomous vehicle technology with smart manufacturing systems. At first, essential control methods for autonomous vehicles, including Linear Matrix Inequalities (LMIs), Linear Quadratic Regulation (LQR)/Linear Quadratic Tracking (LQT), PID controllers, and dynamic control logic via flowcharts, are examined. These techniques are adapted for platooning to enhance coordination, safety, and efficiency within vehicle fleets, and various scenarios are analyzed to confirm their effectiveness in achieving predetermined performance goals such as inter-vehicle distance and fuel consumption. A first approach on simplified hardware, yet realistic to model the vehicle's behavior, is treated to further prove the theoretical results. Subsequently, performance improvement in smart manufacturing systems (SMS) is treated. The focus is placed on offline and online scheduling techniques exploiting Mixed Integer Linear Programming (MILP) to model the shop floor and Model Predictive Control (MPC) to adapt scheduling to unforeseen events, in order to understand how optimization algorithms and decision-making frameworks can transform resource allocation and production processes, ultimately improving manufacturing efficiency. In the final part of the work, platooning techniques are employed within SMS. Autonomous Guided Vehicles (AGVs) are reimagined as autonomous vehicles, grouping them within platoon formations according to different criteria, and controlled to avoid collisions while carrying out production orders. This strategic integration applies platooning principles to transform AGV logistics within the SMS. The impact of AGV platooning on key performance metrics, such as makespan, is devised, providing insights into optimizing manufacturing processes. Throughout this work, various research fields are examined, with intersecting future technologies from precise control in autonomous vehicles to the coordination of manufacturing resources. This thesis provides a comprehensive view of how optimization and automation can reshape efficiency and productivity not only in the domain of autonomous vehicles but also in manufacturing

Implementation of continuous flow manufacturing in United States industries

Continuous Flow Manufacturing (CFM) is one of the key strategies to enable the United States industries to adapt to any volume increase and rapidly changing requirements of the market place. CFM is an on-going analysis and improvement activity used to optimize the efficiency, effectiveness and flexibility of any process. The two basic goals of CFM are to reduce cycle time to less than customer order leadtime and to eliminate inefficiencies from the overall manufacturing processes. The thesis will describe reasons for the scarcity of CFM in United States industries. The methodology applied was a detailed six page questionnaire sent to over thirty-five industries in United States, using CFM as a part in their manufacturing operations. The research focused on difficulties experienced during preparation and implementation of CFM. The theoretical research and the questionnaire analysis revealed that CFM is indeed partially culture-based, difficult to understand, not easy to accept and hard enough to implement. Although the research was taken from a stratified sample of already known CFM implementors, full scale implementation fell very short. In fact, most industries in United States seemed to be engaged in preparing for CFM. Hopefully, the information presented will help the United States industries to formulate plans and strategies to implement further actions that will lead to more efficiency and effectiveness in their manufacturing operations