Octavian Morariu

A genetic algorithm for workload scheduling in cloud based e-learning

Cloud computing is a game-changing paradigm in modern computing, offering a better utilization of IT resources and at the same time reducing the operational costs and increasing the elasticity of the IT infrastructure. Clouds exist in various shapes and dimensions, from general purpose public clouds having virtually unlimited resources, to small private clouds used inside enterprises for specific business goals. These private clouds have limited resources in terms of processing power and IO capability and therefore, an effective scheduling of workloads becomes very important. Another characteristic of small, private clouds is that they are built for a specific purpose, allowing an accurate prediction of the workloads that are going to be scheduled. This paper presents the characteristics of a private cloud used for e-Learning purposes along with a genetic algorithm that optimizes the scheduling of the e-Learning workloads according to a set of conditions that are imposed by the underlying virtualization technology such as memory over-commitment and IOPS rate distribution.

Customer order management in service oriented holonic manufacturing

One of the most important problems when considering the design of manufacturing systems based on SOA paradigms is the integration of shop floor devices in the business processes at the enterprise level. This paper presents the design and implementation of the Customer Order Management (COM) module based on SOA architecture in the context of holonic manufacturing systems. The COM module is integrating with SOA enabled shop floor devices using industry standards. The implementation leverages a multi agent system suited for industrial applications integrated in a SOA environment capable of dynamic BPEL workflow generation and execution. The prototype consists in a SCA application for core COM module functionality and an extension for NetLogo MAS platform for SOA integration. The COM module interacts with the MES layer using real time events handled by the BPEL process implementation in the execution stage. A web based portal frontend for the COM module has been developed to allow real time tracking of customer orders, providing data about product batch execution and individual progress of each product on the production line.

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.

Shop-floor resource virtualization layer with private cloud support

Large scale emergence of mature cloud solutions, ranging from software-as-a-service based solutions for business management, to very sophisticate private cloud solutions; offer the building blocks for constructing extremely flexible enterprise systems that can respond to environmental changes with great agility. Manufacturing enterprises need to adopt these new technologies 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 MES and shop floor architecture as an intermediate layer in the manufacturing stack and discusses the advantages offered by this approach for manufacturing enterprises. A classification of MES and shop floor devices is presented focusing on the virtualization techniques suitable for each device type, considering the level of distributed intelligence and the virtualization overhead. Shop floor virtualization through shop floor profiles is presented and discussed underlying the flexibility of the solution. A pilot multi-agent implementation for virtual shop floor configuration based on the CoBASA reference architecture is presented and discussed. The shop floor profiles which define the virtual layout and mappings of the robotized manufacturing system are also provided in this context. The pilot implementation using six Adapt robots and a IBM CloudBurst 2.1 private cloud, is described and virtualization overhead in terms of event propagation delays is measured and presented in several scenarios of resource workload collocation on physical cloud blades

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.

Formalized Information Representation for Intelligent Products in Service-Oriented Manufacturing

The Intelligent Product concept has been proposed almost a decade ago, gaining considerable traction in manufacturing enterprises as it helps aligning the information flow with the material flow even in the simplest implementations. In advanced applications it can provide support for executing complex algorithms allowing local decision making upon collective reasoning or individual and autonomous selection of the manufacturing operations. In the context of service-oriented manufacturing systems there are new requirements for intelligent products, such as standards adoption and SOA capabilities. This paper proposes a classification of intelligent products from a SOA integration point of view and introduces a formalized data structure for intelligent products in the form of a XSD schema for XML representation. The data flow during manufacturing is discussed in the context of lead time and lag time between operations in the product recipe with the goal to enable ETA estimation of the product and the product batch. An example is presented for assembly of an H- shaped product, focusing on representation of operation dependencies and lag time in XML format proposed.

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.

A Service Oriented Architecture for Total Manufacturing Enterprise Integration

The paper describes a, framework and implementing issues addressing service orientation in the management and control of enterprises. A hybrid, semi-heterarchical control model based on the paradigm of holonic manufacturing is proposed; it switches its operating mode from hierarchical to heterarchical in the presence of perturbations to ensure both global optimization and agility to changes in batch orders, while featuring robustness to disturbances in the production environment. In order to ensure these conflicting functionalities, a service oriented architecture is proposed and implemented, whose structure includes a distributed fault-tolerant Resource Service Access Model. Besides the design of a generic structural and dynamic model, a real implementation solution is proposed using a multi-agent framework.

ILOG-based mixed planning and scheduling system for job-shop manufacturing

The paper presents the design and realization of an optimization model for the jobshop planning and execution problem. The computational model is realized in using the IBM ILOG OPL application. The computation of optimized planning and scheduling is performed using the constraint programming technique. The model contains the input data (client orders and resource status), the objective function (makespan minimization) and the set of constraints related to the real execution of products and to the limitations of the production system. The proposed model, implemented in ILOG OPL, is integrated into a centralized Scheduling System which transfers the planning and scheduling results to the shop floor automation layer of the Manufacturing Execution System (MES).