Silviu Raileanu

Distributed manufacturing control with extended CNP interaction of intelligent products

This paper describes two heterarchical architectures which use distributed intelligence for the control (operation scheduling, resource allocation and product routing) of a manufacturing cell. In these architectures intelligence is put respectively at the product and through the network of workstation computers. The cost of embedded specialized hardware required for the first option is still very high. The second option needs the utilization of Automatic Identification and Data Capture technology close to the product to permit its identification and tracking by the computer system. These technologies enable the automated identification of objects, the collection of data about them, and the storage of that data directly into computer systems. Through this network, the computer system can access or update information in databases about the products and connect with software agents that represent production orders and resources and take in common decisions through negotiation and contract-based rules. The theory of the proposed solutions is based on the holonic manufacturing and product-driven automation concepts. The implementation methodology along with experimental results is presented, emphasizing the advantages of each solution.

Semi-heterarchical control of FMS: From theory to application

This paper presents both a model and a real implementation of a semi-heterarchical control system for flexible manufacturing systems (FMS). After presenting the concepts of heterarchical and semi-heterarchical control, a product-based control structure, composed of a dynamic allocation process (DAP) and a dynamic routing process (DRP), is proposed. Though the associated control processes (DAP and DRP) are hierarchically dependant, each is managed heterarchically, with no supervisor. The dynamic allocation algorithms are presented, and our highly distributed approach to routing control is then explained in detail. A real distributed application of the active entities and the control architecture was implemented in the AIP-PRIMECA pole at the University of Valenciennes, and this implementation is described in detail. A mixed-integer linear model of the FMS was used to compute lower bounds. The flexibility and robustness of our approach are highlighted through several real experiments.

Personal rapid transit in open control framework

Since last decade, the use of safe, comfortable and ecologic vehicles to operate in urban context as an alternative to private car has been required by authorities. Several projects have emerged on on-demand transport with new automated vehicles known as Cybercars or PRTs. In the context of intelligent transportation, where vehicles can be seen as autonomous and decisional entities composing a self-organized system to be controlled, this paper presents the open-control paradigm and gives an example of its instantiation with stigmergic scheme. The open-control concept, developed in our Lab (LAMIH), exhibits the classic explicit control, as well as an innovative type of control called implicit control. The implicit control allows system entities to be influenced via an Optimization Mechanism (OM). After introducing the open-control paradigm, we illustrate one possible implementation based upon a stigmergic approach and applied to a PRTs network. Implementation architecture and first experimental results are reported.

vMES: Virtualization aware manufacturing execution system

Abstract The large scale emergence in the last decade of various cloud solutions, ranging from software-as-a-service (SaaS) based solutions for business process management and implementation to very sophisticated private cloud solutions capable of high performance computing (HPC) and efficient virtualization, constitute the building blocks for engineering the next generation of flexible enterprise systems that can respond with great agility to changes in their environment. These new technologies are adopted at a certain level by manufacturing enterprises in order to advance in a new era of mass customization where flexibility, scalability and agility are the differentiating factors. In this context, this paper introduces the virtualized manufacturing execution system (vMES), an intermediate layer in the manufacturing stack, and discusses the advantages and limitations offered by this approach for manufacturing enterprises. A classification of MES workloads based on the ISA-95 function model is presented, focusing on the virtualization techniques suitable for each workload, considering the algorithms and technologies used and the virtualization overhead. A pilot vMES implementation using a parallel process for smart resource provisioning and automatic scaling is also presented. The pilot implementation using six Adept robots and one IBM CloudBurst 2.1 private cloud and an ISA-95 based MES is described; the virtualization sequence is analyzed in several scenarios of resource workload collocation on physical cloud blades with and without perturbations.

Manufacturing Service Bus Integration Model for Implementing Highly Flexible and Scalable Manufacturing Systems

Abstract This paper presents an integration model for designing manufacturing systems using the concept of manufacturing service bus. The manufacturing service bus (MSB) provides a uniform communication framework at the shop floor layer, integrating all components involved. The main characteristics of the MSB integration layer together with the advantages and requirements of the software products used in this model are discussed. The overall architectural goal of this integration model is to assure a very low coupling between the modules at the shop floor level, providing a high degree of flexibility for the manufacturing enterprises. Physical resources as production line robots, conveyors and existing transportation paths, scheduling algorithms can be plugged in and out without or with a very low impact on the entire system functionality. Another important aspect of this design is that it provides elasticity through a dynamic queued communication model, allowing a seamless scaling capability at the shop floor level.

A JADE Environment for Product Driven Automation of Holonic Manufacturing

This chapter presents a system control frame for implementing the switch between three different production strategies, each with its own planning objective (e.g. makespan, resource load) and perturbation avoidance capabilities. In order to implement such a system, Intelligent Products that possess computing and decision taking abilities are used, the system model and class diagram being presented for all the system agents that are implemented using the JADE Environment.

Resource scheduling based on energy consumption for sustainable manufacturing

The paper proposes an agent-based approach for measuring in real time energy consumption of resources in job-shop manufacturing processes. Data from industrial robots is collected, analysed and assigned to operation types, and then integrated in an optimization engine in order to estimate how alternating between makespan and energy consumption as objective functions affects the performances of the whole system. This study focuses on the optimization of energy consumption in manufacturing processes through operation scheduling on available resources. The decision making algorithm relies on a decentralized system collecting data about resources implementing thus an intelligent manufacturing control system; the optimization problem is implemented using IBM ILOG OPL.

Distributed Manufacturing Control with Extended CNP Interaction of Intelligent Products

Abstract This paper describes the heterarchical control aspect of a semi-heterarchical control architecture. The theory of the proposed solution is based on the product-driven automation and on the holonic manufacturing concepts. Regarding the practical implementation aspects the proposed solution is based on the new advances in IT and electronics which made possible attaching Intelligent Embedded Devices to almost all of the elements of a Flexible Manufacturing System. In this framework the structure of the control model is presented and using elements defined here the FIPA Contract Net Protocol is extended in order to accommodate some physical and synchronization issues.

Management of changes in a holonic manufacturing system with dual-horizon dynamic rescheduling of production orders

Abstract The paper describes a solution and implementing framework for the management of changes which may occur in a holonic manufacturing system. This solution is part of the semi-heterarchical control architecture developed for agile job shop assembly with intelligent robots-vision workstations. Two categories of changes in the manufacturing system are considered: (i) changes occurring in resource status at process level: resource breakdown, failure of (vision-based) in-line inspection operation, and depletion of local robot storages; (ii) changes in production orders at business (ERP) level: rush orders. All these situations trigger production plan update and rescheduling (redefine the list of Order Holons) by pipelining CNP-type resource bidding at shop-floor horizon with global product scheduling at aggregate batch horizon. Failure- and recovery management are developed as generic scenarios embedding the CNP mechanism into production self-rescheduling. Implementing solutions and experimental results are reported for a 6-station robot-vision assembly cell with twin-track closed-loop pallet transportation system and product tracking RD/WR devices. Future developments will consider manufacturing integration at enterprise level.

Redundancy and scalability for virtualized MES systems with programmable infrastructure

We introduce the vMES virtualization layer for manufacturing execution systems.Workload identification at MES layer according to ISA-95.03 functions.We present a process for private cloud redundancy and scaling for MES workload.Experimental results showing perturbation handling in cloud environment.Benefits of virtualization and programmable infrastructure for MES workloads. Virtualization of manufacturing execution system (vMES) workloads offers a set of design and operational advantages to enterprises, the most visible being improved resource utilization and flexibility of the overall solution. This paper explores redundancy and scalability, as other important operational advantages introduced by the use of private clouds for MES virtualization in the context of the programmable infrastructure (PI) concept. PI is a new architectural approach in which the computing infrastructure, represented by resources, networks, storage, becomes dynamic and is controlled by the application, in contrast with traditional architectures where the application has to adapt to a static infrastructure. For MES applications, the adoption of PI has the potential to add a new layer of flexibility and optimization by allowing quick configuration and re-configuration based on environmental changes, especially in the context of virtualization in private cloud where workloads can be provisioned and de-provisioned in real time. In this context, this paper presents the main redundancy and scalability requirements for the workloads identified in ISA-95.03 based solutions and discusses in detail the strategies to assure the redundancy and scalability requirements of these workloads both individually and at the system level. The main contributions of this paper are therefore the introduction of PI combined with private cloud virtualization at the MES layer in order to achieve redundancy and scalability of the control solution. The pilot implementation presented is based on PI concepts and is realized in practice using SOA BPEL and IBM CloudBurst REST APIs. The MES system considered for the pilot implementation adopts a multi-agent vMES architecture having COBASA-type functionality. The experimental results presented in this paper show the system response in a set of failure scenarios, with focus on the reconfiguration time of workloads, and the dynamic response to perturbations in the system.