A system architecture for holonic manufacturing planning and control (EtoPlan)

In this paper, we present the system architecture of a flexible manufacturing planning and control system, named EtoPlan. The concept is based on the holonic control approach of building multiple and temporary hierarchies (holarchies). This paper describes the system architecture for flexible planning and control of activities and (groups of) Resources in a manufacture-to-order environment. The system architecture consists of generic control modules that can be applied on different hierarchical levels and for different kinds of manufacturing activities. The main function of the Resource Controller is the Determine Applicability function.     

Collaborative reconfiguration mechanism for holonic manufacturing systems

Although holonic manufacturing systems (HMS) are recognized as a paradigm to cope with the changes in manufacturing environment based on a flexible architecture, development of reconfiguration mechanism is required to realize the advantages of HMS. Finding a solution from scratch to deal with changes in HMS is not an appropriate approach as it may lead to chaos at the shop floor. The objective of this paper is to propose a viable design methodology to achieve effective reconfiguration in HMS based on the cooperation of holons. We formulate and study a holarchy reconfiguration problem and define an impact function to characterize the impact of resource failures on different holons in a holarchy. A collaborative reconfiguration algorithm based on the impact function is proposed to effectively reconfigure the systems to achieve minimal cost solutions.     

Pull control for job shop: holonic manufacturing system approach using multicriteria decision-making

Faced with international competition, industrial production increasingly requires implementation conditions which, in some cases, lead to seek new techniques for workshop control. This is the case when it is asked to establish Just in Time management in a Job Shop having the characteristics of working with small series. A new approach for the organization of the ‘control’ function in such a context is presented here. This approach relies on the use of the holonic paradigm on an isoarchic architecture and on a decision-making capacity based on a multicriteria analysis. The various concepts of this approach are addressed first. Then, the multicriteria decision mechanisms that are used are detailed, as well as the implementation and instrumentation phases. The first results that were obtained are presented.     

Engineering framework for agent-based manufacturing control

MAS (multi-agent systems) and HMS (holonic manufacturing systems) are enabling the vision of the Plug & Play Factory and paving the way for future autonomous production systems. This paper reviews the state of the art in implementations of agent-based manufacturing systems, and identifies the lack of engineering tools as a technological gap for widespread industrial adoption of the paradigm. The lack of tools limits the implementation of agent-based manufacturing systems within reach of only a handful of domain experts. One of the current challenges for the design and implementation of intelligent agents is the simulation and visualization of the agent societies. This issue is significant as soon as the software agent is embedded into a mechatronic device or machine resulting in a physical intelligent agent with 3D-mechanical restrictions. These mechanical restrictions must be considered in the negotiations between agents in order to coordinate the execution of physical operations. This paper presents an engineering framework that contributes towards overcoming the identified technology gap. The framework consists of a comprehensive set of software tools that facilitate the creation, simulation and visualization of agent societies. The 3D framework is innovative in fully emulating the deployed agents, recreating multi-agent negotiations and societies that coordinate and execute control of assembly operations. The documented research describes the methodology for the 3D representation of individual physical agents, the related identified objects present in the interaction protocols, and the assembly features and clustering algorithms.     

Industry 4.0: contributions of holonic manufacturing control architectures and future challenges

Journal of Intelligent Manufacturing - The flexibility claimed by the next generation production systems induces a deep modification of the behaviour and the core itself of the control systems....     

An object-oriented simulation framework for real-time control of automated flexible manufacturing systems

This paper describes an object-oriented simulation approach for the design of a flexible manufacturing system that allows the implementation of control logic during the system design phase. The object-oriented design approach is built around the formal theory of supervisory control based on Finite Automata. The formalism is used to capture inter-object relationships that are difficult to identify in the object-oriented design approach. The system resources are modeled as object classes based on the events that have to be monitored for real-time control. Real-time control issues including deadlock resolution, resource failures in various modes of operation and recovery from failures while sustaining desirable logical system properties are integrated into the logical design for simulating the supervisory controller.     

A multilevel multilayer framework for manufacturing control

As a contribution to the debate on CAPM reference models derived from control theory concepts, we formulate the basic computer-aided production management problem from a control theoretic point of view and examine the main difficulties in using this crude framework as a basis for decision-making. Next, different hierarchical approaches are shown to be potentially of value in overcoming the two main difficulties highlighted by the control theoretic paradigm, i.e. dimensionality and the discrete event nature of manufacturing systems. In this context, we examine the literature concerned with both multilevel control as well as multilayer control where the notion of aggregation plays a key role. Next, a mixture of multilevel and multilayer control is used to provide a framework for production planning and scheduling for multiline batch manufacture with application to detergents plants. This framework would appear to be of values also in discrete parts manufacture and this is also highlighted.     

Intelligent agent based framework for manufacturing systems control

Existing modeling frameworks for manufacturing system control can be classified into hierarchical, heterarchical, and hybrid control frameworks. The main drawbacks of existing frameworks are discussed in this paper. A new hybrid modeling framework is also described. It is a hybrid of the two: hierarchical and heterarchical frameworks. In this proposed framework, entities (e.g., parts) and resources (e.g., material handling devices, machines, cells, departments) are modeled as holonic structures that use intelligent agents to function in a cooperative manner so as to accomplish individual, as well as cell-wide and system-wide objectives. To overcome the structural rigidity and lack of flexibility, negotiation mechanisms for real-time task allocation are used. Lower-level holons may autonomously make their negotiations within the boundary conditions that the higher-level holons set. Horizontal, as well as vertical decisions, are made between various levels of controllers, and these are explicitly captured in the model.     

Modeling and reconfiguring intelligent holonic manufacturing systems with Internet-based mobile agents

A holonic manufacturing system (HMS) represents a new breed of intelligent shop-floor management technology for the production of artifacts that satisfy unique customer requirements. Flexibility is an essential characteristic of the HMS in order to manufacture high-variety low-volume artifacts. Autonomous smart entities called holons interact, via cooperation protocols, within a HMS to support the runtime reconfiguration demanded by such an agile shop-floor. This paper presents a framework to model and reconfigure, in real-time, the holons' abstract behavioral specifications through the application of Internet-based mobile agents. A tool is also described to convert these specifications into a corresponding implementation model (based on the IEC 61499 function block architecture) that holons can execute across an open network of controller devices.     

An object-oriented framework for developing distributed manufacturing architectures

Management of complexity, changes and disturbances is one of the key issues of production today. Distributed, agent-based structures represent viable alternatives to hierarchical systems provided with reactive/proactive capabilities. In the paper, approaches to distributed manufacturing architectures are surveyed, and their fundamental features are highlighted, together with the main questions to be answered while designing new structures. Moreover, an object-oriented simulation framework for development and evaluation of multi-agent manufacturing architectures is introduced.     

An effective potential field approach to FMS holonic heterarchical control

This paper points out the capabilities of a heterarchical control approach, based on potential fields, to simultaneously solve the problems of dynamic allocation and routing in a real flexible manufacturing system. This paper proposes a “Potential fields” approach, as the key reactive mechanism to handle the transient state of ADACOR designed by Leitão & Restivo (2006) and its real implementation. First, a “Potential fields” model, which takes certain constraints into account, such as dynamic transportation times and limited resource storage capacities is presented. Then, the flexibility and robustness of the approach are highlighted, with a set of scenarios performed in simulation and on a real physical system: the AIP-PRIMECA cell. These results are compared to the results provided by a mixed-integer linear model that was used to compute lower bounds.     

Model and control holonic manufacturing systems based on fusion of contract nets and Petri nets

Holonic manufacturing systems (HMS) can be modeled as multi-agent systems to which contract net protocol can be effectively and robustly applied. However, the lack of analysis capability of contract nets makes it difficult to avoid undesirable states such as deadlocks in HMS. This paper presents a framework to model and control HMS based on fusion of Petri net and multi-agent system theory. The main results include: (1) a multi-agent model and a collaboration process to form commitment graphs in HMS based on contract net protocol, (2) a procedure to convert commitment graph to collaborative Petri net (CPN), and (3) feasible conditions and collaborative algorithms to award contracts in HMS based on CPNs.     

The control of myopic behavior in semi-heterarchical production systems: A holonic framework

Heterarchical control architectures are essentially founded on cooperation and full local autonomy, resulting in high reactivity, no master/slave relationships and local information retention. Consequently, these architectures experience myopic decision-making, bringing entities towards local optimality rather than the system’s overall performance. Although this issue has been identified as an important problem within heterarchical control architectures, it has not been formally studied. The aim of this paper is to identify the dimensions of myopic behavior and propose mechanisms to control this behavior. This study focuses on myopic behavior found in manufacturing control. For this particular study, we propose a holonic framework and a holonic organization that integrates specific mechanisms to control the temporal and social myopia. Our proposal was validated using simulations designed for solving the allocation problem in flexible manufacturing systems. These simulations were conducted to show the improvement by integrating the new mechanisms. These simulation results indicate that the myopic control mechanisms achieve better performance than the reactive strategies, because not only they introduce a planning horizon, but also because they balance local and global objectives, seeking a consensus.     

Allocation of quality control stations in multistage manufacturing systems

The allocation of quality control stations (AQCS) in multistage manufacturing systems has been studied extensively over the decades. This paper reviews the existing approaches, models comparison and solution techniques applied in AQCS. The relevance of the models and the effectiveness of the inspection strategies are examined by developing a generalised model. The conducting simulation experiments show that as the number of workstation increases the processing time to solve the problem increases significantly. This led to the development of a heuristic algorithm with local search. The performance the heuristic was compared with the optimization method based on complete enumeration method (CEM). It was found that the heuristic method can derive an acceptable solution significantly faster than the CEM. The review has shown that the most common techniques used are dynamic programming and non-linear programming. The paper suggests some biologically inspired optimisation algorithms can be of interest for further study.     

Holarchy formation and optimization in holonic manufacturing systems with contract net

Holonic manufacturing systems (HMS) is based on the notion of holon, an autonomous, cooperative and intelligent entity to provide a econfigurable, flexible and decentralized manufacturing environment to respond to changing needs and opportunities. A set of holons that cooperate to achieve a goal forms a holarchy. How to design a mechanism to form a holarchy to achieve a goal while minimizing the overall cost is a challenge. The objectives of this paper are to propose models and develop collaborative algorithms to guide the holons to form a holarchy to coherently move toward the desired goal state ultimately. We adopt contract net protocol (CNP) to model mutual selection of holons in forming a holarchy. We formulate a holarchy optimization problem to minimize the cost subject to the feasibility constraints. To analyze the feasibility of a holarchy, a Petri net (PN) model is proposed. As classical PN models do not take into account the cost involved in firing transitions, we augment the PN model with cost functions in the problem formulation. Due to the distributed architecture of HMS, the internal structure of each potential holarchy that acts as bidder in CNP is not available to the manager. A key issue is to determine the feasibility of a holarchy without constructing the whole PN model of the given hierarchy. We study the feasible conditions for a holarchy and propose a collaborative algorithm to analyze the feasibility and award contracts to holons without constructing the whole model of a holarchy.     

Design of reconfiguration mechanism for holonic manufacturing systems based on formal models

One of the key design issues of holonic manufacturing systems (HMS) is to effectively respond to resource failures based on the flexible holonic architecture. The objective of this paper is to propose a viable design methodology to implement reconfiguration mechanism in HMS. A reconfiguration mechanism is developed to accommodate changes based on collaboration of holons without leading to chaos at the shop floor. To deal with resource failures in HMS, an impact function is defined to characterize the impact of resource failures on different holons in a holarchy. A collaborative reconfiguration mechanism based on an impact function is proposed to effectively reconfigure the systems to achieve minimal cost solutions. The design and implementation methodology combines contract net protocol for negotiation of holons, Petri net for the representation of individual product holons and resource holons and FIPA-compliant agent platform for publication/discovery of holons. A simulation system is developed to verify the proposed reconfiguration mechanism.     

Production control of a manufacturing system with multiple machinestates

The production control of a single-product manufacturing system with arbitrary number of machine states (failure modes) is discussed. The objective is to find a production policy that would meet the demand for the product with minimum average inventory or backlog cost. The optimal production policy has a special structure and is called a hedging-point policy. If the hedging points are known, the optimal production rate is readily specified. Assuming a set of tentative hedging points, the simple structure of the optimal policy is utilized to find the steady-state probability distribution of the surplus (inventory or backlog). Once this function is determined, the average surplus cost is easily calculated in terms of the values of the hedging points. The average cost is then minimized to find the optimum hedging points     

An expert system for manufacturing cell control

An expert control system was designed to control an unmanned manufacturing cell in order to meet the operational requirements of a cellular Manufacturing System (CMS). In this paper, a knowledge-based three-layer control concept was used to build the cell control system. This cell control system is built to include workers' experience and problem handling ability. The cell control algorithms and heuristics are based on the pull system control principle. A Petri net is used to generate the cell control algorithm. The structure of the control system and the application of the Petri net method will be demonstrated.     

An on-line framework for monitoring nonlinear processes with multiple operating modes

A multivariate statistical process monitoring scheme should be able to describe multimodal data. Multimodality typically arises in process data due to varying production regimes. Moreover, multimodality may influence how easy it is for process operators to interpret the monitoring results. To address these challenges, this paper proposes an on-line monitoring framework for anomaly detection where an anomaly may either indicate a fault occurring and developing in the process or the process moving to a new operating mode. The framework incorporates the Dirichlet process, which is an unsupervised clustering method, and kernel principal component analysis with a new kernel specialized for multimode data. A monitoring model is trained using the data obtained from several healthy operating modes. When on-line, if a new healthy operating mode is confirmed by an operator, the monitoring model is updated using data collected in the new mode. Implementation issues of this framework, including the parameter tuning for the kernel and the selection of anomaly indicators, are also discussed. A bivariate numerical simulation is used to demonstrate the performance of anomaly detection of the monitoring model. The ability of this framework in model updating and anomaly detection in new operating modes is shown on data from an industrial-scale process using the PRONTO benchmark dataset. The examples will also demonstrate the industrial applicability of the proposed framework.