Reactive and energy-aware scheduling of flexible manufacturing systems using potential fields

This paper presents a reactive scheduling approach for flexible manufacturing systems, which integrates the overall energy consumption of the production. This work is justified by the growing needs of manufacturers for energy-aware control, due to new important environmental criteria, which holds true in the context of high reactivity. It makes production hard to predict. The proposed reactive scheduling model is based on potential fields. In this model, resources that sense the intentions from products are able to switch to standby mode to avoid useless energy consumption and emit fields to attract products. Simulations are provided, featuring three indicators: makespan, overall energy consumption and the number of resource switches. Real experiments were carried out to illustrate the feasibility of the approach on a real system and validate the simulation results.     

Distributed control of multi-robot systems using bifurcating potential fields

The distributed control of multi-robot systems has been shown to have advantages over that of conventional single-robot systems. These include scalability, flexibility and robustness to failures. This paper considers pattern formation and reconfigurability in a multi-robot system using a new control algorithm developed through bifurcating potential fields. It is shown how various patterns can be achieved autonomously through a simple free parameter change, with the stability of the system proven to ensure that desired behaviours always occur.     

Hierarchical and dynamic production control in flexible manufacturing systems

Job shop control involves directing the flow of products through the manufacturing system. Centralized and decentralized approaches have been proposed. This paper introduces first a mix approach in the organization of real time control level in flexible manufacturing systems: a hierarchical organization permits coordination of distributed decision centres and heterarchical consideration confers a partial autonomy to sub-level decision centres. Second, corrective actions against unexpected events are introduced to maintain as far as possible the forecasted scheduling.     

Constrained motion control using vector potential fields

Discusses the generation of a control signal that would instruct the actuators of a robotics manipulator to drive motion along a safe and well-behaved path to a desired target. The proposed concept of navigation control along with the tools necessary for its construction achieve this goal. The most significant tool is the artificial vector potential field which shows a better ability to steer motion than does a scalar potential field. The synthesis procedure emphasizes flexibility so that the effort needed to modify the control is commensurate with the change in the geometry of the workspace. Theoretical development along with simulation results are provided     

Maintenance scheduling and production control of multiple-machine manufacturing systems

This paper deals with the production and preventive maintenance control problem for a multiple-machine manufacturing system. The objective of such a problem is to find the production and preventive maintenance rates for the machines so as to minimize the total cost of inventory/backlog, repair and preventive maintenance. A two-level hierarchical control model is presented, and the structure of the control policy for both identical and non-identical manufacturing systems is described using parameters, referred to here as input factors. By combining analytical formalism with simulation-based statistical tools such as experimental design and response surface methodology, an approximation of the optimal control policies and values of input factors are determined. The results obtained extend those available in existing literature to cover non-identical machine manufacturing systems. A numerical example and a sensitivity analysis are presented in order to illustrate the robustness of the proposed approach. The extension of the proposed production and preventive maintenance policies to cover large systems (multiple machines, multiple products) is discussed.     

Adaptive control for manufacturing systems using infinitesimalperturbation analysis

Combining infinitesimal perturbation analysis (IPA) with stochastic approximation gives identification algorithms to estimate the optimal threshold value for failure-prone manufacturing systems consisting of one machine producing one part type. Two adaptive control schemes are proposed. The adaptive control schemes do not require the knowledge of the distribution functions of the up and down times. Under some appropriate conditions, the strong consistency, as well as the convergence rates, of the identification algorithms and the cost function is established for the adaptive control schemes. In particular, it is shown that central limit theorems hold for the identification algorithms     

应用控制变迁的柔性制造系统死锁控制策略

不同于目前许多文献中基于添加控制库所的死锁预防策略,本文提出了控制变迁方程(CTE)的概念和相应的基于添加控制变迁(CT)的死锁控制策略(DCP).通过分析存在死锁的原网(N0, M0)的可达图(RG),该DCP求解出所有死锁标识(DM).基于CTE,构造出所需的控制变迁.然后,对每个DM添加相应的CT,进而消除了原网(N_0, M_0)中的死锁标识,得到了活性受控网系统(N~?, M~?).通过理论分析和相关算例的应用,该DCP的正确性和有效性得到了验证.此外,该DCP获取的活性受控网系统(N~?, M~?)可达数目与原网(N_0, M_0)是相同的,即最大可达数(MRN).     

Synthesis of control policies for manufacturing systems using the control canonical form

In this paper, multivariable systems theory is used to synthesize control policies for a manufacturing system which is modelled as a linear discrete-time multivariable dynamical system. The state variables of the system are the rates-of-flow of parts at the various work stations, the buffer inventories, anil the finished product inventories. The control inputs are the man-hours per week required for the various processes involved in the manufacturing system, anil the disturbance inputs are the demands for semi-finished and finished parts. The behaviour of the controlled manufacturing system is illustrated by the presentation of the results of computer simulation studies showing typical transient and steady-state response characteristics,     

Joint production and supply control in three levels flexible manufacturing systems

This paper considers a stochastic optimal control problem of a three stages Flexible Manufacturing System. The supplier (i.e., upstream FMS) and the transformation stage (i.e., FMS) are both subject to random events. Our objective is to find a feedback control policy for the supply and production activities that minimizes the incurred cost. It is shown that the considered joint production and supply control problem is difficult to tackle using a dissociated analytical approach. A simulation based approach is thus proposed to achieve a close approximation of the optimal policy. The advantages of the approach include possible extensions after numerical characterization of the optimal control policy.     

Perturbation analysis for production control and optimization of manufacturing systems

We use stochastic fluid models (SFM) to capture the operation of threshold-based production control policies in manufacturing systems without resorting to detailed discrete event models. By applying infinitesimal perturbation analysis (IPA) to a SFM of a workcenter, we derive gradient estimators of throughput and buffer overflow metrics with respect to production control parameters. It is shown that these gradient estimators are unbiased and independent of distributional information of supply and service processes involved. In addition, based on the fact that they can be evaluated using data from the observed actual (discrete event) system, we use them as approximate gradient estimators in simple iterative schemes for adjusting thresholds (hedging points) on line seeking to optimize an objective function that trades off throughput and buffer overflow costs.     

Simulation-based benchmarking of production control schemes for complex manufacturing systems

In this paper, benchmarking efforts for production control approaches applied to complex manufacturing systems are described. Complex manufacturing systems are characterized by a large number of products, an over time changing product mix, sequence-dependent set-up times, unrelated parallel machines, a mix of different process types, and internal and external disturbances. In order to ensure comparison possibilities among different production control approaches, the usage of a simulation test-bed and a software architecture that allows for plug in of different production control software are suggested. Different application areas, the advantages, and also the limitations of the suggested approach are discussed.     

Optimality of hedging point policies in the production control offailure prone manufacturing systems

We study the necessary and sufficient conditions for the optimality of the hedging point policy for production systems in which the failure rate of machines depends on the rate of production. We focus on a one machine one part-type and infinite horizon discounted cost problem. It is shown that when the failure rate is independent of the rate of production and a constant, the hedging point policy is provably optimal. The main result of this paper is to show that the linearity of the failure rate function is both necessary and sufficient for the optimality of the hedging point policy     

A human-in-the-loop manufacturing control architecture for the next generation of production systems

In recent years, the introduction of Industry 4.0 technologies in the manufacturing landscape promoted the development of smart factories characterised by relevant socio-technical interactions between humans and machines. In this context, understanding and modelling the role of humans turns out to be crucial to develop efficient manufacturing systems of the future. Grounding on previous researches in the field of Human-in-the-Loop and Human Cyber-Physical Systems, the paper aims at contributing to a deep reflection about human-machine interaction in the wider perspective of Social Human-in-the-Loop Cyber-Physical Production Systems, in which more agents collaborate and are socially connected. After presenting an evolution of manufacturing control organisations, an architecture to depict social interactions in smart factories is proposed. The proposed architecture contributes to the representation of different human roles in the smart factory and the exploration of both hierarchical and heterarchical data-driven decision-making processes in manufacturing.     

Dynamic Drum-Buffer-Rope approach for production planning and control in capacitated flow-shop manufacturing systems

Drum-Buffer-Rope-based production planning and control (PPC) approaches provide production managers with effective tools to manage production disruptions and improve operational performance. The corner stone of these approaches is the proper selection of time-buffers which are considered as exogenously defined constant. However, the majority of real-world manufacturing systems are characterized by the dynamic change of demand and by stochastic production times. This fact calls for a dynamic approach in supporting the decision making on time-buffer policies. To this end, we study a capacitated, single-product, three-operation, flow-shop manufacturing system. We propose a dynamic time-buffer control mechanism for short/medium-term PPC with adaptive response to demand changes and robustness to sudden disturbances in both internal and external shop environment. By integrating the control mechanism into the flow-shop system, we develop a system dynamics model to support the decision-making on time-buffer policies. Using the model, we study the effect of policies on shop performance by means of analysis of variance. Extensive numerical investigation reveals the insensitivity of time-buffer policies to key factors related to demand, demand due date and operational characteristics such as protective capacity and production times.     

Nonhierarchical control of manufacturing systems

An alternative to the high cost of development, maintenance, operation and modification of complex manufacturing systems with hierarchical architectures is under study at the University of Wisconsin-Madison. Nonhierarchical control architectures offer prospects of reduced complexity by localizing information and control, reducing software development costs, increasing maintanability and modifiability, and improving reliability.     

ManufAg: a multi-agent-system framework for production control of complex manufacturing systems

In this paper, we present a framework for the implementation of multi-agent-systems for production control of complex manufacturing systems. We present the results of a requirement analysis for production control systems for complex manufacturing systems; then we describe the framework design criteria. Our framework supports the inclusion of distributed hierarchical decision-making schemes into the production control. Furthermore, in order to increase the coordination abilities of multi-agent-systems, we follow the decision-making and staff agent architecture suggested in the PROSA reference architecture. We indicate the usage of the framework for designing and implementing an agent-based production control system for semiconductor manufacturing processes in a case study.     

Time-optimal production control in a manufacturing system

This study demonstrates the use of control engineering techniques to regulate the product inventory levels of a workshop in a manufacturing system by manipulating the number of machines and the labour time employed during production. The production policy that minimizes the production time is obtained by time-optimal control techniques.     

Deadlock control methods in automated manufacturing systems

As more and more producers move to use flexible and agile manufacturing as a way to keep them with a competitive edge, the investigations on deadlock resolution in automated manufacturing have received significant attention for a decade. Deadlock and related blocking phenomena often lead to catastrophic results in automated manufacturing systems. Their efficient handling becomes a necessary condition for a system to gain high productivity. This paper intends to present a tutorial survey of state-of-the art modeling and deadlock control methods for discrete manufacturing systems. It presents the updated results in the areas of deadlock prevention, detection and recovery, and avoidance. It focuses on three modeling methods: digraphs, automata, and Petri nets. Moreover, for each approach, the main and relevant contributions are selected enlightening pros and cons. The paper concludes with the future research needs in this important area in order to bridge the gap between the academic research and industrial needs.     

Model-based low-level control in flexible manufacturing systems

Low-level (supervisory) control of flexible manufacturing systems (FMS) assures conflict-free operation and enforces production requirements such as priorities. It forms a crucial link between medium and higher-level decision making, on the one hand, and the various machine-controllers and servomechanisms on the other. In the absence of a suitable control methodology, ad hoc development is the current practice and compromised results at high cost are far too common. Here we described a model-based framework for a new, systematic approach to supervisory control.