Herman Augusto Lepikson

Improving connectivity for runtime simulation of automation systems via OPC UA

Nowadays industrial companies need more agile and adaptable production systems to manufacture customized products faster and with a high level of process optimization. This agility in production requires flexible automation systems. One key capability such systems need to exhibit is effective connectivity and interoperability with different vendor-specific software and hardware tools, which often presents difficulties. This paper shares results and research experience in applying OPC UA technology, to establish communication between Programmable Logic Controller (PLC) based control systems and virtual engineering tool (Onevue) to enable interactive support and data collection during production. This paper provides an overview of the OPC UA client development for the Onevue. Based on the case study provided in the paper, results of the OPC UA client-server communication is reported.

A hybrid neural architecture for fuzzy rules extraction

This article proposes a hybrid neural architecture (i.e. neuro-fuzzy) capable to generate Takagi-Sugeno fuzzy rules and to adjust the membership functions and the output functions. The main idea is to apply this algorithm to function approach tasks, whose input-output relationships are the only available information. The proposed algorithm spares previous data analysis. Initially, the user only defines the number of fuzzy rules that the system should produce. This model has the convenience of not requesting the previous and empiric knowledge of the fuzzy rules structure. The proposed model is initiated with an architecture fully connected; in other words, implicit rules do not exist in the connections of the net. Instead of this, the connections between the entrance layer and the T-norms are linked by synaptic weights. These weights must be adjusted and, in a posterior stage, are partially eliminated. The training process occurs in four stages: in the first stage is adjusted the synapses and the function parameters. The second stage occurs when the quadratic error reaches acceptable values. Then, a part of the synapses introduced between the first and the second layer are eliminated. In this stage the proposed net is equaled to the ANFIS model, because the disabled synapses reveal the base rules generated automatically by the algorithm. In the third stage, the adjustment process continues from an identical way to the ANFIS. Finally, in the fourth stage, is eliminated the lower relevant rules. This process makes the base of rules more intelligible.

Developing Interfaces Based on Services to the Cloud Manufacturing: Plug and Produce

In the last decade the industrial automation had been making important changes integrating Internet and other emergent technologies, concepts, methods and tools, as cloud computing and Service Oriented Architecture(SOA) approaches. As a first consequence, the industrial automation context is also increasing in complexity, presenting new challenges for engineers and managers. Examples include dealing with autonomous cyber physical systems, evolvable heterogeneous structures that do not appear completely formed and where functions and goal are added, removed or modified along the life cycle, as well as handling emergent properties and behaviours of entire systems, e.g. resulting from integrating new systems being not localized to any single system component. [1]. The objective of this paper is to make a review in industrial automation background, analyze the technological trends and challenges and propose a flexible and autoconfigurable service-oriented model, making up basis for the cloud manufacturing. In this model the entities are loosely coupled, due the fact that a service’s functionality communication is showed through its interfaces.

Service-Oriented Framework for Oil Fields Automation

The actual manufacturing enterprises are characterized by frequently changing market demands, global competition, rising require production systems concerning flexibility and adaptability, besides exigency for new industrial control systems providing lower time-to market and shorter product cycles. The inflexible communication infrastructure between the manufacturing process elements difficulties the adoption of porting production with high degree of reconfigurability and interoperability. The adoption of a service-oriented architecture (SOA) can bring real benefits to the industrial automation communication. Service-oriented architecture provides a flexible, open solution for manufacturing plants. Besides good endeavors proposed by consortiums and standard institutions, the market still shows the dominance of proprietary standards. In oil fields, managing the new technologies requires from the decision-making an integrated analysis of data that enables the understanding of interventions in the field in a comprehensive manner. For this, we propose a context-oriented framework to exploit Internet-based business models beside Service-oriented Architecture principles that relies on service oriented paradigm and open standards as, Webservices, XML, and Devices Profiles for Web (DPWS). This higher integration can affect daily oilfield operations, and the vision for an autonomous industrial automation as simple as plug and play.

CPPM: A Logical Architecture for the Cyber-Physical Production Model

Cyber-Physical Systems (CPS) are not a fad anymore, they are changing the way industries and companies plan and model their businesses in a distributed, dynamic, service-oriented way using virtualized resources that are scalable and accessed over the Internet. This change raises new challenges and opportunities for companies. In the last decade the industrial automation field has been introducing important technologies that are changing and integrating the Internet and other emerging technologies, concepts, methods and tools, such as cloud computing, agents and Service Oriented Architecture (SOA). These new approaches are resulting in the convergence of the physical world and the virtual world (cyberspace) in the direction of Industry 4.0. Industries are being forced to change and manage their IT and automation services through IT-enabled services to use new paradigms, and huge efforts of R & D are being made in this field. It is clear that in order to change the automation state many possibilities and paradigms are on the table. This work introduces a logical architecture for a cyber-physical production model, intending to help organizations adopting cyber- physical based services.

New Approach to Calculate Adiabatic Curves of Bound States and Reactive Scattering in Quantum Chemistry Problems

This paper presents a new approach to calculate adiabatic curves in quantum chemistry problem. Based on the Shifted Inverse, the proposed approach differs from the others especially because the initial guesses (eigenvectors and offsets) are not arbitrary. Instead, they are chosen in coherence with the Potencial Energy Surface and quantum number. Initial guesses are determined from the knowledge of experts about the problem under study. From the numerical experiments, it was noticed that the new approach has proved to be more efficient than the Divider and Conquer Method in cases where the problem requires that only some eigenvalues of interest need to be calculated, as often occurs in problems of quantum chemistry.

Collaborative Agents Supporting Tactical Planning Activities – An Industrial Application

This paper presents a collaborative agents model for Sales and Operation Planning (S&OP) in industry. We show how an S&OP system can be used in a multi-agent approach considering existing legacy software and how people and software agents interact in a planning environment in a process industry, such as the petrochemical industry. The model helps to describe the process, determine the pre-existing software integrations, define responsibilities, and promote communication and learning. The solution adopted is crucial for a high performance S&OP. It is also important to consider the interaction among human agents and software agents, which are required for its success. The multi-agent system (MAS) paradigm is useful for helping industries handle distributed information sources and interactions between a number of actors and teams. We examine activities of an S&OP in a petrochemical company and how these activities can be more efficiently performed through MAS.

A Multi-agent Approach for Production Management

Multi-agent systems have been successfully used to represent distributed manufacturing systems. Each part or characteristic of the system can be represented by an agent which acts independently and in a cooperative way. A better integrated operation can emerge as the result of each agent following its own rules and communicating with the others. Better decisions from a holistic viewpoint can be achieved when manufacturing asset management is supported by a multi-agent approach. A model to manage distributed manufacturing is proposed and applied to on-shore oil fields. The distributed characteristics of oil field units, such as wells, collecting stations, compressing stations and supplies mean that they have to cooperate to reach production targets. The integrated management model carries out a cost analysis and helps to identify unprofitable assets and to support decision making processes. Agents help to reduce the load of information for the operator, giving more time to focus on situations that require greater attention. Example applications are presented in which the proposed multi-agent model, its ontology and rules, could help oil field surveillance and support decision-making process.

A Multi-Agent System for Oil Field Management

This paper presents SGCP, an acronym in Portuguese for a Multi-agent System for Oil Field Management. The SGCP was developed for use in managing onshore oil field facilities. The main functions of the system are diagnosis of problems related to the productivity of each oil field component, analysis of profitability and decision-making support. In the SGCP, each agent represents one oil field function. Some agents are directly linked to production (operational agents), others are linked to maintenance activities (intervention agents), and others are linked to supply of materials and equipment (supply agents). The agents perform tasks by adding value to the processed oil, gas and water and transferring costs among themselves. In the model, production problems are identified by agent actions. The agents monitor their environment using statistical process control techniques and send alerts requesting intervention as necessary.

New Technologies for Asset Management Applied to Oil Fields

Asset management is an integrated process that aims to achieve the alignment of corporate goals, information systems capable of making rigorous and consistent spending decisions based on asset-level data and cross-functional expertise between the various business process skills. In oil fields, managing the asset requires the decision-making from an integrated analysis of data that enables the understanding of interventions in the field in a comprehensive manner. For this, we propose an approach that by building a database of technical and economic variables, procedures and engineering methods to structure the information, and alignment with organizational strategy, more rational decision and better performances will be possible. These decisions can affect daily oilfield operations, direct investments or even disable an oil field facility.