Sergii Iarovyi

Cyber–Physical Systems for Open-Knowledge-Driven Manufacturing Execution Systems

Manufacturing execution systems play an important role of bridging high-level enterprise functions and production or manufacturing operations. The embedded systems are usually in charge of controlling execution of the operations. Modern embedded systems have become capable of simultaneous and deterministic execution of control algorithms and IP-based communication, making it possible to create complex cyber-physical systems (CPSs), where the computational and communication resources of a device can be used directly for various control, supervisory, or monitoring functions. The complexity for defining open-knowledge-driven manufacturing execution system (OKD-MES) is in maintaining awareness of overall system state to avoid disruptive actions as various functions may be requested from a system. The problem is that obtaining such information on system state may necessitate collecting data from a number of devices, as there may not be a single data point for state information. This paper describes and illustrates an approach for designing OKD-MES on top of CPSs that controls robot workstations and conveyor-based transportation system of a pallet-based production system.

Knowledge-based web service integration for industrial automation

Web services are widely used for enterprise software development. Web service protocols simplify application integration thanks to interface description that can be processed at runtime and, in addition, due to mature and widely used standards for transportation and internetworking. Implementation of service-oriented architecture starts to get acceptance in the field of industrial automation ranging from international research project to the first implementations in industry including first commercial controller devices supporting web service communication protocols and executing deterministic control at the same time. The current research step is to allow knowledge-based integration of industrial automation systems and to exploit full potentials of run-time reconfiguration and adaptation of industrial systems. This paper demonstrates implementation of knowledge-based industrial system, the architecture and ontology model that can be generalized for implementation of other production systems.

An approach for OSGi and DPWS interoperability: Bridging enterprise application with shop-floor

Scope and importance of the enterprise applications are increasing constantly, as these information systems allow more effective usage of enterprise time and resources. The enterprise applications are retrieving the information about the production processing the data from outer sources. The factory shop-floor devices are among the most important data sources. The exposure of the shop-floor devices information and functionality to information systems is currently being implemented employing Service-Oriented Architecture (SOA) paradigm. Device Profile for Web Services (DPWS) is among the most employed technologies providing the service functionality to devices. The contemporary factory information system is usually a continuously expanding set of dissimilar, independent applications, which are separately retrieving the information about enterprise processes. These applications frequently duplicate information or functionality of each other. The necessity to integrate these applications emerges, once the overlap between applications should be removed. Creation of multiple custom integrations between the applications in constantly developing system, commonly, is not an effective practice. The Message Oriented Middleware (MOM) can simplify and standardize the integration, providing neutral messaging system. Currently MOM and factory information systems are often implemented employing dynamic packaging systems such as OSGi. The approach for interoperability of OSGi and DPWS presented in this article is based on the DPWS adapter function block. This block can be deployed in OSGi system, instantiated and configured for particular integration tasks. This approach aims to introduce the loose connection between the enterprise information system and devices.

Management of distributed knowledge encapsulated in embedded devices

Embedded electronic devices are now to be found everywhere. In general, they can be used to collect different sorts of data (e.g. on temperature, humidity, illumination and locations). In some specific domains, such as industrial automation, embedded devices are used for process control. The devices may have a programme that can respond immediately to environmental changes perceived through sensors. In the control of large sites, where there are many devices, higher level decisions are made or processed in dedicated computers far away from the sources (devices) where the initial data are collected. This article shows how it is possible to manage portions of distributed knowledge, hosted in embedded devices, making it possible for each embedded device to hold and manage its piece of knowledge. In addition, presented approach allows keeping locus of control at the embedded device level, where the embedded device can make decisions knowing the status of the rest of the world, device contributions and their effects in the overall distributed system knowledge base.

Representation of manufacturing equipment and services for OKD-MES: From service descriptions to ontology

Demand for efficiency in the domain of manufacturing increases driven by competition for resources and customers. Adaptation of the modern concepts which have proven their benefits in other domains to the automation of manufacturing systems provides a field for innovation. Recent developments in Cyber-Physical Systems, Service-oriented Architecture and Knowledge-Driven Approach suggest an ecosystem for contemporary factory. Such set of concepts is applied in the eScop project for implementation of Open Knowledge-Driven Manufacturing Execution System (OKD-MES). The Knowledge-Driven approach introduces new possibilities for efficient operation of the system, but also requires significant effort to describe knowledge about the system. Significant part of this knowledge may be provided by the equipment in the factory shop floor. The approach which facilitates the process of population of knowledge base using the data from manufacturing equipment in automated manner should lower the cost and the organizational threshold for introduction of OKD-MES to the industry. This paper evaluates the possibilities for extraction of required semantic data from the descriptions provided by the smart service-oriented manufacturing equipment.

From artificial cognitive systems and open architectures to cognitive manufacturing systems

Considering constantly increasing demand for shift from mass production to mass customization and the need to maintain high level of automation despite permanent changes in manufacturing technologies and tools new approaches and solutions have to be provided in manufacturing. Cyber-Physical Systems and Industrial Internet of Things are enabling smart manufacturing to tackle the challenge of data processing, integration and interpretation, but beyond uniformed data collection and visualization. The cognitive approach is argued to introduce brain and biologically-inspired algorithms capable to better adapt industrial systems for unforeseen conditions. Such approach should provide flexible and robust solution for manufacturing systems, enabling new level of adaptability and re-configurability in the system by self-X capabilities. In this paper contemporary solutions applicable for introduction of cognitive capabilities in manufacturing systems are studied and the architecture for cognitive manufacturing system employing benefits of Industrial Internet and Cognitive Control is proposed.

A web-based simulator for a discrete manufacturing system

Virtualization has become a supportive approach for simulating system behaviour efficiently thanks to the revolution of computer and smart devices. In fact, the employment of running virtual tools that mimic the real physical world is nowadays a requirement in some fields as in e.g. industrial automation. This research work presents a virtual tool that simulates a real assembly line. The main features of this simulator are listed as; web application that can be accessed with any devices that supports html web pages, animated application that provides a UI for the user, discovery mechanism that allows web applications to interact with the simulator automatically and RESTful-based services, which increases the flexibility and versatility in terms of deployment. FASTory simulator has been developed and deployed during the eScop project. In addition, presented simulator has been employed by C2NET (Cloud Collaborative Manufacturing Networks) project for development some of its tools. Furthermore, the exploitation of the FASTory simulator is extended to cover as well the education of next generation of engineers for design and implementation of modern CPS. As Tampere University of Technology provides a M.Sc. degree in automation engineering, students use the simulator for their experiments, ensuring that mistakes are recoverable and harmless.

Generic platform for manufacturing execution system functions in knowledge-driven manufacturing systems

ABSTRACT Information technologies grow rapidly nowadays with the advance and extension of computing capabilities. This growth affects several fields, which consume these technologies. Industrial Automation is not an exception. This publication describes a general and flexible architecture for implementing Manufacturing Execution System (MES) function, which can be deployed in multiple industrial cases. These features are achieved by combining the flexibility of knowledge-driven systems with the vendor-independent property of RESTful web services. With deployment of this solution, MES functions may gain more versatility and independency. This research work is a continuation of the development of the OKD-MES (Open Knowledge-Driven Manufacturing Execution System) framework during the execution of the eScop project. The OKD-MES framework consists on a semantic-based solution for controlling and enhancing the flexibility and re-configurability of MES. In such scope, this research presents MES functions architecture that might be implemented in the OKD-MES framework in order to increase the flexibility of event-driven manufacturing systems.

Architecture for Open, Knowledge-Driven Manufacturing Execution System

Manufacturing Execution Systems (MES) are a bridge between the enterprise solutions and factory shop floors. MES allows the performance of contemporary factories by closer integration of the needs of enterprise stakeholders with the actual manufacturing hardware and software components. Considering different nature of the factories the application of MES has significant difference across industry. Such constrain requires a sophisticated solutions to contain the generality of application. Most of currently available solutions are proprietary and tightly coupled to the ecosystem of devices and enterprise resource planning systems. In current paper the architecture for the open, knowledge-driven MES is discussed. Authors argue that such MES will provide smart extensibility based on base-of-breed approach and hence will improve the quality of MES application, while reducing the introduction costs and system downtime due to reconfiguration.

Towards processing and reasoning streams of events in knowledge-driven manufacturing execution systems

The incessant need of the industry to optimize processes due to market demands derived in a huge investment on information communication technologies implementation during last decades, in the industrial automation domain. This caused the implementation of paradigms as service-oriented or event-driven architectures in factories, used for wide data integration. Moreover, the use of knowledge representation, within ontologies, permitted the description of system status in knowledge bases, which can be queried and updated at runtime. Due to the massive occurrence of events at any location of the enterprise, complex event processing (CEP) technologies can be used for anticipating facts that can compromise the production at shop floors. In fact, recent implementations on processing and reasoning streams of events in the Semantic Web can be applied also in the industrial automation domain because they combine CEP and SPARQL, which are technologies nowadays used by factory systems. This article describes how these technologies can support the study of the ontological system models evolution through time and an approach to bring predictability to current knowledge-based systems.