A visual language and environment for enterprise system modelling and automation

Objective: We want to support enterprise service modelling and generation using a more end user-friendly metaphor than current approaches, which fail to scale to large organisations with key issues of "cobweb" and "labyrinth" problems and large numbers of hidden dependencies. Method: We present and evaluate an integrated visual approach for business process modelling using a novel tree-based overlay structure that effectively mitigate complexity problems. A tree-overlay based visual notation (EML) and its integrated support environment (MaramaEML) supplement and integrate with existing solutions. Complex business architectures are represented as service trees and business processes are modelled as process overlay sequences on the service trees. Results: MaramaEML integrates EML and BPMN to provide complementary, high-level business service modelling and supports automatic BPEL code generation from the graphical representations to realise web services implementing the specified processes. It facilitates generated service validation using an integrated LTSA checker and provides a distortion-based fisheye and zooming function to enhance complex diagram navigation. Evaluations of EML show its effectiveness. Conclusions: We have successfully developed and evaluated a novel tree-based metaphor for business process modelling and enterprise service generation. Practice implications: a more user-friendly modelling approach and support tool for business end users.

Automatic detection of thermal damage in grinding process by artificial neural network

Esse trabalho tem por objetivo o desenvolvimento de um sistema inteligente para detecção da queima no processo de retificação tangencial plana através da utilização de uma rede neural perceptron multi camadas, treinada para generalizar o processo e, conseqüentemente, obter o limiar de queima. em geral, a ocorrência da queima no processo de retificação pode ser detectada pelos parâmetros DPO e FKS. Porém esses parâmetros não são eficientes nas condições de usinagem usadas nesse trabalho. Os sinais de emissão acústica e potência elétrica do motor de acionamento do rebolo são variáveis de entrada e a variável de saída é a ocorrência da queima. No trabalho experimental, foram empregados um tipo de aço (ABNT 1045 temperado) e um tipo de rebolo denominado TARGA, modelo ART 3TG80.3 NVHB.

Automation and cybernetics: Control of a flexible one-link manipulator

States that control is of the essence in cybernetics. Summarizes the dynamic equations for a flexible one-link manipulator moving in the horizontal plane. Employs the finite element method, based on elementary beam theory, during the process of formulation. Develops and instruments a one-link flexible manipulator in order to control its vibration modes. Uses a simple second-order vibration model which permits vibrations on the rod to be estimated using the hub angle. The validation of the dynamic model and the structural analysis of the flexible manipulator is reached using proper infrared cameras and active light sources for determining actual positions of objects in space. Shows that the performance of the control is satisfactory, even under perturbation action.

IEEE 1451-based multi-interface module (I2M) for industrial processes automation

This paper describes the implementation of a multi-interface module (I2M) for automation of industrial processes, based on the IEEE1451 standard. Process automation with I2M can communicate through either wires or using wireless communication, without any hardware or software changes. We used FPGA resources to implement the I2M functions FPGA, with a NIOS II processor and ZigBee communication system (IEEE802.15), as well as RS232 serial standard. Part of the project was done in the SOPC Builder environment, which gave the designer flexibility and speed to implement the NIOS II-based microprocessor system. To test the I2M implementation, a didactic Industrial Hydraulic Module (MHI-01) was used to simulate two industrial processes to be controlled by the system proposed.

Automation in fault detection using neural network and model updating

In this article, an implementation of structural health monitoring process automation based on vibration measurements is proposed. The work presents an alternative approach which intent is to exploit the capability of model updating techniques associated to neural networks to be used in a process of automation of fault detection. The updating procedure supplies a reliable model which permits to simulate any damage condition in order to establish direct correlation between faults and deviation in the response of the model. The ability of the neural networks to recognize, at known signature, changes in the actual data of a model in real time are explored to investigate changes of the actual operation conditions of the system. The learning of the network is performed using a compressed spectrum signal created for each specific type of fault. Different fault conditions for a frame structure are evaluated using simulated data as well as measured experimental data.

In-process thermal damage detection in grinding with monitoring via Internet

This work aims the development of a dedicated system for detection of burning in surface grinding process, where the process will constantly be monitored through the acoustic emission and electric power of the induction motor drive. Acquired by an analog-digital converter, algorithms process the signals and a control signal is generated to inform the operator or interrupt the process in case of burning occurrence. Moreover, the system makes possible the process monitoring via Internet. Additionally, a comparative study between parameters DPO and FKS is carried through. In the experimental work one type of. steel (ABNT-1020 annealed) and one type of grinding wheel referred to as TARGA, model ART 3TG80.3 NVHB, were employed.

Virtual instrumentation: A practical approach to control and supervision process

This work describes a control and supervision application takes into account the virtual instrumentation advantages to control and supervision industrial manufacturing stations belonging to the modular production system MPS® by Festo. These stations integrate sensors, actuators, conveyor belt and other industrial elements. The focus in this approach was to replace the use of programmable logic controllers by a computer equipped with a software application based on Labview and, together, performs the functions of traditional instruments and PLCs. The manufacturing stations had their processes modeled and simulated in Petri nets. After the models were implemented in Labview environment. Tests and previous similar works in MPS® installed in Automation Laboratory, at UNESP Sorocaba campus, showed the materials and methods used in this work allow the successful use of virtual instrumentation. The results indicate the technology as an advantageous approach for the automation of industrial processes, with gains in flexibility and reduction in project cost. © 2011 IEEE.

A Framework for the Automation of Discrete-Event Simulation Experiments

Simulation is an important resource for researchers in diverse fields. However, many researchers have found flaws in the methodology of published simulation studies and have described the state of the simulation community as being in a crisis of credibility. This work describes the project of the Simulation Automation Framework for Experiments (SAFE), which addresses the issues that undermine credibility by automating the workflow in the execution of simulation studies. Automation reduces the number of opportunities for users to introduce error in the scientific process thereby improvingthe credibility of the final results. Automation also eases the job of simulation users and allows them to focus on the design of models and the analysis of results rather than on the complexities of the workflow.

Generalizability and Applicability of Model-Based Business Process Compliance-Checking Approaches – A State-of-the-Art Analysis and Research Roadmap

With a steady increase of regulatory requirements for business processes, automation support of compliance management is a field garnering increasing attention in Information Systems research. Several approaches have been developed to support compliance checking of process models. One major challenge for such approaches is their ability to handle different modeling techniques and compliance rules in order to enable widespread adoption and application. Applying a structured literature search strategy, we reflect and discuss compliance-checking approaches in order to provide an insight into their generalizability and evaluation. The results imply that current approaches mainly focus on special modeling techniques and/or a restricted set of types of compliance rules. Most approaches abstain from real-world evaluation which raises the question of their practical applicability. Referring to the search results, we propose a roadmap for further research in model-based business process compliance checking.

The reviewing process: validating results

Any scientific publication aims to advance the field of knowledge that it deals with, and therefore the editorial staff will always be seeking the most revolutionary papers among all of those received. On the other hand, the reviewers’ task is usually a much more conservative one, as reviewers are responsible for verifying the realism of the methods proposed and the veracity of the claimed results.

Functional modeling applied to HAZOP automation

In this paper we present a new tool to perform guided HAZOP analyses. This tool uses a functional model of the process that merges its functional and its structural information in a natural way. The functional modeling technique used is called D-higraphs. This tool solves some of the problems and drawbacks of other existing methodologies for the automation of HAZOPs. The applicability and easy understanding of the proposed methodology is shown in an industrial case.

Real time optimization in chemical process: evaluation of strategies, improvements and industrial application.

The increasing economic competition drives the industry to implement tools that improve their processes efficiencies. The process automation is one of these tools, and the Real Time Optimization (RTO) is an automation methodology that considers economic aspects to update the process control in accordance with market prices and disturbances. Basically, RTO uses a steady-state phenomenological model to predict the process behavior, and then, optimizes an economic objective function subject to this model. Although largely implemented in industry, there is not a general agreement about the benefits of implementing RTO due to some limitations discussed in the present work: structural plant/model mismatch, identifiability issues and low frequency of set points update. Some alternative RTO approaches have been proposed in literature to handle the problem of structural plant/model mismatch. However, there is not a sensible comparison evaluating the scope and limitations of these RTO approaches under different aspects. For this reason, the classical two-step method is compared to more recently derivative-based methods (Modifier Adaptation, Integrated System Optimization and Parameter estimation, and Sufficient Conditions of Feasibility and Optimality) using a Monte Carlo methodology. The results of this comparison show that the classical RTO method is consistent, providing a model flexible enough to represent the process topology, a parameter estimation method appropriate to handle measurement noise characteristics and a method to improve the sample information quality. At each iteration, the RTO methodology updates some key parameter of the model, where it is possible to observe identifiability issues caused by lack of measurements and measurement noise, resulting in bad prediction ability. Therefore, four different parameter estimation approaches (Rotational Discrimination, Automatic Selection and Parameter estimation, Reparametrization via Differential Geometry and classical nonlinear Least Square) are evaluated with respect to their prediction accuracy, robustness and speed. The results show that the Rotational Discrimination method is the most suitable to be implemented in a RTO framework, since it requires less a priori information, it is simple to be implemented and avoid the overfitting caused by the Least Square method. The third RTO drawback discussed in the present thesis is the low frequency of set points update, this problem increases the period in which the process operates at suboptimum conditions. An alternative to handle this problem is proposed in this thesis, by integrating the classic RTO and Self-Optimizing control (SOC) using a new Model Predictive Control strategy. The new approach demonstrates that it is possible to reduce the problem of low frequency of set points updates, improving the economic performance. Finally, the practical aspects of the RTO implementation are carried out in an industrial case study, a Vapor Recompression Distillation (VRD) process located in Paulínea refinery from Petrobras. The conclusions of this study suggest that the model parameters are successfully estimated by the Rotational Discrimination method; the RTO is able to improve the process profit in about 3%, equivalent to 2 million dollars per year; and the integration of SOC and RTO may be an interesting control alternative for the VRD process.

Literature review on recent international activity in cooperative vehicle-highway automation systems /

This literature review supports the report, Recent International Activity in Cooperative Vehicle-Highway Automation Systems. It reviews the published literature in English dating from 2007 or later about non-U.S.-based work on cooperative vehicle-highway automation systems. This review covers work performed in Europe and Japan, with application to transit buses, heavy trucks, and passenger cars. In addition to fully automated driving of the vehicles (without human intervention), it also covers partial automation systems, which automate subsets of the total driving process. Recent International Activity in Cooperative Vehicle Highway Automation Systems is published separately as FHWA-HRT-12-033.

Towards Automation in Digital Investigations : Seeking Efficiency in Digital Forensics in Mobile and Cloud Environments

Cybercrime and related malicious activity in our increasingly digital world has become more prevalent and sophisticated, evading traditional security mechanisms. Digital forensics has been proposed to help investigate, understand and eventually mitigate such attacks. The practice of digital forensics, however, is still fraught with various challenges. Some of the most prominent of these challenges include the increasing amounts of data and the diversity of digital evidence sources appearing in digital investigations. Mobile devices and cloud infrastructures are an interesting specimen, as they inherently exhibit these challenging circumstances and are becoming more prevalent in digital investigations today. Additionally they embody further characteristics such as large volumes of data from multiple sources, dynamic sharing of resources, limited individual device capabilities and the presence of sensitive data. These combined set of circumstances make digital investigations in mobile and cloud environments particularly challenging. This is not aided by the fact that digital forensics today still involves manual, time consuming tasks within the processes of identifying evidence, performing evidence acquisition and correlating multiple diverse sources of evidence in the analysis phase. Furthermore, industry standard tools developed are largely evidence-oriented, have limited support for evidence integration and only automate certain precursory tasks, such as indexing and text searching. In this study, efficiency, in the form of reducing the time and human labour effort expended, is sought after in digital investigations in highly networked environments through the automation of certain activities in the digital forensic process. To this end requirements are outlined and an architecture designed for an automated system that performs digital forensics in highly networked mobile and cloud environments. Part of the remote evidence acquisition activity of this architecture is built and tested on several mobile devices in terms of speed and reliability. A method for integrating multiple diverse evidence sources in an automated manner, supporting correlation and automated reasoning is developed and tested. Finally the proposed architecture is reviewed and enhancements proposed in order to further automate the architecture by introducing decentralization particularly within the storage and processing functionality. This decentralization also improves machine to machine communication supporting several digital investigation processes enabled by the architecture through harnessing the properties of various peer-to-peer overlays. Remote evidence acquisition helps to improve the efficiency (time and effort involved) in digital investigations by removing the need for proximity to the evidence. Experiments show that a single TCP connection client-server paradigm does not offer the required scalability and reliability for remote evidence acquisition and that a multi-TCP connection paradigm is required. The automated integration, correlation and reasoning on multiple diverse evidence sources demonstrated in the experiments improves speed and reduces the human effort needed in the analysis phase by removing the need for time-consuming manual correlation. Finally, informed by published scientific literature, the proposed enhancements for further decentralizing the Live Evidence Information Aggregator (LEIA) architecture offer a platform for increased machine-to-machine communication thereby enabling automation and reducing the need for manual human intervention.