MULTIAGENT SYSTEMS FOR SHOP FLOOR ARHITECTURE MANAGEMENT

The paper presents the problem of shop floor agility. In order to cope with the disturbances and uncertainties that characterise the current business scenarios faced by manufacturing companies, the capability of their shop floors needs to be improved quickly, such that these shop floors may be adapted, changed or become easily modifiable (shop floor reengineering). One of the critical elements in any shop floor reengineering process is the way the control/supervision architecture is changed or modified to accommodate for the new process and equipment. This paper, therefore, proposes an multi-agent architecture to support the fast adaptation or changes in the control/supervision architecture.multi-agent system, shop floor agility, control/supervision architecture, virtual organisation.

An ‘on-demand’ Data Communication Architecture for Supplying Multiple Applications from a Single Data Source: An Industrial Application Case Study

A key aspect of automation is the manipulation of feedback sensor data for the automated control of particular process actuators. Often in practice this data can be reused for other applications, such as the live update of a graphical user interface, a fault detection application or a business intelligence process performance engine in real-time. In order for this data to be reused effectively, appropriate data communication architecture must be utilised to provide such functionality. This architecture must accommodate the dependencies of the system and sustain the required data transmission speed to ensure stability and data integrity. Such an architecture is presented in this paper, which shows how the data needs of multiple applications are satisfied from a single source of data. It shows how the flexibility of this architecture enables the integration of additional data sources as the data dependencies grow. This research is based on the development of a fully integrated automation system for the test of fuel controls used on civil transport aircraft engines

Nature-Inspired Adaptive Architecture for Soft Sensor Modelling

This paper gives a general overview of the challenges present in the research field of Soft Sensor building and proposes a novel architecture for building of Soft Sensors, which copes with the identified challenges. The architecture is inspired and making use of nature-related techniques for computational intelligence. Another aspect, which is addressed by the proposed architecture, are the identified characteristics of the process industry data. The data recorded in the process industry consist usually of certain amount of missing values or sample exceeding meaningful values of the measurements, called data outliers. Other process industry data properties causing problems for the modelling are the collinearity of the data, drifting data and the different sampling rates of the particular hardware sensors. It is these characteristics which are the source of the need for an adaptive behaviour of Soft Sensors. The architecture reflects this need and provides mechanisms for the adaptation and evolution of the Soft Sensor at different levels. The adaptation capabilities are provided by maintaining a variety of rather simple models. These particular models, called paths in terms of the architecture, can for example focus on different partition of the input data space, or provide different adaptation speeds to changes in the data. The actual modelling techniques involved into the architecture are data-driven computational learning approaches like artificial neural networks, principal component regression, etc

Using ATL to define advanced and flexible constraint model transformations

Transforming constraint models is an important task in re- cent constraint programming systems. User-understandable models are defined during the modeling phase but rewriting or tuning them is manda- tory to get solving-efficient models. We propose a new architecture al- lowing to define bridges between any (modeling or solver) languages and to implement model optimizations. This architecture follows a model- driven approach where the constraint modeling process is seen as a set of model transformations. Among others, an interesting feature is the def- inition of transformations as concept-oriented rules, i.e. based on types of model elements where the types are organized into a hierarchy called a metamodel

Searching for improvement

Engineering design can be thought of as a search for the best solutions to engineering problems. To perform an effective search, one must distinguish between competing designs and establish a measure of design quality, or fitness. To compare different designs, their features must be adequately described in a well-defined framework, which can mean separating the creative and analytical parts of the design process. By this we mean that a distinction is drawn between coming up with novel design concepts, or architectures, and the process of detailing or refining existing design architecture. In the case of a given design architecture, one can consider the set of all possible designs that could be created by varying its features. If it were possible to measure the fitness of all designs in this set, then one could identify a fitness landscape and search for the best possible solution for this design architecture. In this Chapter, the significance of the interactions between design features in defining the metaphorical fitness landscape is described. This highlights that the efficiency of a search algorithm is inextricably linked to the problem structure (and hence the landscape). Two approaches, namely, Genetic Algorithms (GA) and Robust Engineering Design (RED) are considered in some detail with reference to a case study on improving the design of cardiovascular stents

THE ROLE OF DATA ARCHITECTURE AS A PART OF ENTERPRISE ARCHITECTURE

In the early days of computing, technology simply automated manual processes with greater efficiency. The new organizational context provides input into the data architecture and is the primary tool for the management and sharing of enterprise data. It enables architects, data modelers, and stakeholders to identify, classify, and analyze information requirements across the enterprise, allowing the right priorities for data sharing initiatives. Data architecture states how data are persisted, managed, and utilized within an organization. Data architecture is made up of the structure of all corporate data and its relationships to itself and external systems. In far too many situations, the business community has to enlist the assistance of IT to retrieve information due to the community's inconsistency, lack of intuitiveness, or other factors. The goal of any architecture should illustrate how the components of the architecture will fit together and how the system will adapt and evolve over time.data architecture, enterprise architecture, business process planning,databases, business objects.

The Twenty Year Test: Principles for an Enduring Counterterrorism Legal Architecture

The United States faces three enduring terrorism-related threats. First, there is the realistic prospect of additional attacks in the United States including attacks using weapons of mass destruction (“WMD”). Second, in responding to this threat, we may undermine the freedoms that enrich our lives, the tolerance that marks our society, and the democratic values that define our government. Third, if we are too focused on terrorism, we risk losing sight of this century’s other certain threats as well as the capacity to respond to them, including the state proliferation of nuclear weapons, nation-state rivalry, pandemic disease, oil dependency, and environmental degradation. The United States should respond to these threats using all available and appropriate security tools, on offense and in defense. Law is one of the essential security tools. Law provides substantive authority to act. Law can also provide and embed an effective process of preview and review to test proposals and validate actions, ensuring that they are both lawful and effective. However, the United States has been slow, or perhaps unwilling, to adopt a legal architecture that maximizes each of these legal benefits. Instead, the political branches have generally adopted an incremental approach, or relied on the President’s authority as Commander in Chief to define the law. This paper describes four principles that should inform the design of a lasting legal architecture to counterterrorism: First, the architecture should reflect an understanding of the strategic value of law in substance, process, and policy. Second, the architecture should reflect the threats it is intended to address, including the potential catastrophic nature of the physical threat, which distinguishes this form of terrorism from that of the past. Third, with limited exception, the law should avoid absolutes—in the authority asserted; in the authority prohibited; or, in bureaucratic design. Finally, the architecture should be lasting, which means among other things that it should be “constitutionally inclusive” in design. A lasting and inclusive architecture will improve security—by maximizing the Executive’s authority to act, sustaining support for tools and policies, and improving the opportunity and efficacy to appraise U.S. actions

Neural Network architectures design by Cellular Automata evolution

4th Conference of Systemics Cybernetics and Informatics. Orlando, 23-26 July 2000The design of the architecture is a crucial step in the successful application of a neural network. However, the architecture design is basically, in most cases, a human experts job. The design depends heavily on both, the expert experience and on a tedious trial-and-error process. Therefore, the development of automatic methods to determine the architecture of feedforward neural networks is a field of interest in the neural network community. These methods are generally based on search techniques, as genetic algorithms, simulated annealing or evolutionary strategies. Most of the designed methods are based on direct representation of the parameters of the network. This representation does not allow scalability, so to represent large architectures very large structures are required. In this work, an indirect constructive encoding scheme is proposed to find optimal architectures of feed-forward neural networks. This scheme is based on cellular automata representations in order to increase the scalability of the method.Publicad