An ontological approach for modelling configuration of factory-wide data integration systems based on IEC-61499

The comprehensive study of Key Performance Indicators (KPIs) in nowadays manufac-turing systems has become a need for improving the efficiency of production processes, pressed by the market demand. To achieve this management, industrial control systems are being modelled robustly by using standards. This causes developers to use semantic technologies to deal with the complexity of data integration and modelling of systems. On the other hand, ISA-95 is an international standard that reduce human efforts by helping directly on the business logistics of man-ufacturing systems. Then, ISA-95-based implementations can be developed for data integration. Moreover, the current trend on systems modelling is the use of ontologies which provide models to be more descriptive, allowing knowledge to be decoupled from busi-ness logic, and extending modularity of the domain knowledge. In addition, the applica-tion of AI to industrial control systems is being developed by the interoperability be-tween a knowledge base, created by ontologies, and a reasoner. This thesis proposes a methodology for modelling configuration for heterogeneous data integration while considering the various information models contained in the sys-tems of the modelled manufacturing systems. The implementation of this work not only presents how to model a production line as an example of manufacturing system, but also allows carrying out the configuration of a Function Block Network (FBN) by speci-fying a KPI. Then, this work pretends to present a possible manner of KPI classification and its calculation by configuring a FBN, all of this by the use of ontologies

An Approach to Automatically Distribute and Access Knowledge within Networked Embedded Systems in Factory Automation

This thesis presents a novel approach for automatically distribute and access knowledge within factory automation systems built by networked embedded systems. Developments on information, communication and computational technologies are making possible the distribution of tasks within different control resources, resources which are networked and working towards a common objective optimizing desired parameters. A fundamental task for introducing autonomy to these systems, is the option for represent knowledge, distributed within the automation network and to ensure its access by providing access mechanisms. This research work focuses on the processes for automatically distribute and access the knowledge.Recently, the industrial world has embraced service-oriented as architectural (SOA) patterns for relaxing the software integration costs of factory automation systems. This pattern defines a services provider offering a particular functionality, and service requesters which are entities looking for getting their needs satisfied. Currently, there are a few technologies allowing to implement a SOA solution, among those, Web Technologies are gaining special attention for their solid presence in other application fields. Providers and services using Web technologies for expressing their needs and skills are called Web Services. One of the main advantage of services is the no need for the service requester to know how the service provider is accomplishing the functionality or where the execution of the service is taking place. This benefit is recently stressed by the irruption of Cloud Computing, allowing the execution of certain process by the cloud resources.The caption of human knowledge and the representation of that knowledge in a machine interpretable manner has been an interesting research topic for the last decades. A well stablished mechanism for the representation of knowledge is the utilization of Ontologies. This mechanism allows machines to access that knowledge and use reasoning engines in order to create reasoning machines. The presence of a knowledge base allows as clearly the better identification of the web services, which is achievable by adding semantic notations to the service descriptors. The resulting services are called semantic web services.With the latest advances on computational resources, system can be built by a large number of constrained devices, yet easily connected, building a network of computational nodes, nodes that will be dedicated to execute control and communication tasks for the systems. These tasks are commanded by high level commanding systems, such as Manufacturing Execution Systems (MES) and Enterprise Resource Planning (ERP) modules. The aforementioned technologies allow a vertical approach for communicating commanding options from MES and ERP directly to the control nodes. This scenario allows to break down monolithic MES systems into small distributed functionalities, if these functionalities use Web standards for interacting and a knowledge base as main input for information, then we are arriving to the concept of Open KnowledgeDriven MES Systems (OKD-MES).The automatic distribution of the knowledge base in an OKD-MES mechanism and the accomplishment of the reasoning process in a distributed manner are the main objectives for this research. Thus, this research work describes the decentralization and management of knowledge descriptions which are currently handled by the Representation Layer (RPL) of the OKD-MES framework. This is achieved within the encapsulation of ontology modules which may be integrated by a distributed reasoning process on incoming requests. Furthermore, this dissertation presents the concept, principles and architecture for implementing Private Local Automation Clouds (PLACs), built by CPS.The thesis is an article thesis and is composed by 9 original and referred articles and supported by 7 other articles presented by the author

Bridging food security gaps in the European High North through the Internet of Food

Food processing, storage, and distribution are at the centre of environmental damage. Food security gaps include failure to track the geographical origin of foods, food waste, food safety and the quality of food products. To achieve sustainability, changes are required in food supply chains and the entire food system. Consumers need information to make informed choices about what to eat. They need to know where food came from, the conditions under which it grew, and the food’s nutritional profile. The food industry has been slow to take advantage of the internet. However, with increasing interests in redistributed manufacturing, circumpolar regions such as the European High North will need to digitise. The Internet of Food (IoF) is an emerging trend. It will make food traceable, transparent, and trustworthy and empower consumers with more personalised food that caters precisely to individual food, diet, and health choices. It is therefore important to build an information infrastructure around the IoF. This chapter examines how food security gaps can be bridged by collating data that will help to leapfrog local foods into the digital era.Peer reviewe

Building University-Industry Co-Innovation Networks in Transnational Innovation Ecosystems : Towards a Transdisciplinary Approach of Integrating Social Sciences and Artificial Intelligence

This paper presents a potential solution to fill a gap in both research and practice that there are few interactions between transnational industry cooperation (TIC) and transnational university cooperation (TUC) in transnational innovation ecosystems. To strengthen the synergies between TIC and TUC for innovation, the first step is to match suitable industrial firms from two countries for collaboration through their common connections to transnational university/academic partnerships. Our proposed matching solution is based on the integration of social science theories and specific artificial intelligence (AI) techniques. While the insights of social sciences, e.g., innovation studies and social network theory, have potential to answer the question of why TIC and TUC should be looked at as synergetic entities with elaborated conceptualization, the method of machine learning, as one specific technic off AI, can help answer the question of how to realize that synergy. On the way towards a transdisciplinary approach to TIC and TUC synergy building, or creating transnational university-industry co-innovation networks, the paper takes an initial step by examining what the supports and gaps of existing studies on the topic are, and using the context of EU-China science, technology and innovation cooperation as a testbed. This is followed by the introduction of our proposed approach and our suggestions for future research.publishedVersionPeer reviewe

Product, process and resource model coupling for knowledge-driven assembly automation

: Accommodating frequent product changes in a short period of time is a challenging task due to limitations of the contemporary engineering approach to design, build and reconfigure automation systems. In particular, the growing quantity and diversity of manufacturing information, and the increasing need to exchange and reuse this information in an efficient way has become a bottleneck. To improve the engineering process, digital manufacturing and Product, Process and Resource (PPR) modelling are considered very promising to compress development time and engineering cost by enabling efficient design and reconfiguration of manufacturing resources. However, due to ineffective coupling of PPR data, design and reconfiguration of assembly systems are still challenging tasks due to the dependency on the knowledge and experience of engineers. This paper presents an approach for data models integration that can be employed for coupling the PPR domain models for matching the requirements of products for assembly automation. The approach presented in this paper can be used effectively to link data models from various engineering domains and engineering tools. For proof of concept, an example implementation of the approach for modelling and integration of PPR for a Festo test rig is presented as a case study

Implementing and Visualizing ISO 22400 Key Performance Indicators for Monitoring Discrete Manufacturing Systems

The employment of tools and techniques for monitoring and supervising the performance of industrial systems has become essential for enterprises that seek to be more competitive in today’s market. The main reason is the need for validating tasks that are executed by systems, such as industrial machines, which are involved in production processes. The early detection of malfunctions and/or improvable system values permits the anticipation to critical issues that may delay or even disallow productivity. Advances on Information and Communication Technologies (ICT)-based technologies allows the collection of data on system runtime. In fact, the data is not only collected but formatted and integrated in computer nodes. Then, the formatted data can be further processed and analyzed. This article focuses on the utilization of standard Key Performance Indicators (KPIs), which are a set of parameters that permit the evaluation of the performance of systems. More precisely, the presented research work demonstrates the implementation and visualization of a set of KPIs defined in the ISO 22400 standard-Automation systems and integration, for manufacturing operations management. The approach is validated within a discrete manufacturing web-based interface that is currently used for monitoring and controlling an assembly line at runtime. The selected ISO 22400 KPIs are described within an ontology, which the description is done according to the data models included in the KPI Markup Language (KPIML), which is an XML implementation developed by the Manufacturing Enterprise Solutions Association (MESA) international organization

An ontological approach for modelling configuration of factory-wide data integration systems based on IEC-61499

The comprehensive study of Key Performance Indicators (KPIs) in nowadays manufac-turing systems has become a need for improving the efficiency of production processes, pressed by the market demand. To achieve this management, industrial control systems are being modelled robustly by using standards. This causes developers to use semantic technologies to deal with the complexity of data integration and modelling of systems. On the other hand, ISA-95 is an international standard that reduce human efforts by helping directly on the business logistics of man-ufacturing systems. Then, ISA-95-based implementations can be developed for data integration. Moreover, the current trend on systems modelling is the use of ontologies which provide models to be more descriptive, allowing knowledge to be decoupled from busi-ness logic, and extending modularity of the domain knowledge. In addition, the applica-tion of AI to industrial control systems is being developed by the interoperability be-tween a knowledge base, created by ontologies, and a reasoner. This thesis proposes a methodology for modelling configuration for heterogeneous data integration while considering the various information models contained in the sys-tems of the modelled manufacturing systems. The implementation of this work not only presents how to model a production line as an example of manufacturing system, but also allows carrying out the configuration of a Function Block Network (FBN) by speci-fying a KPI. Then, this work pretends to present a possible manner of KPI classification and its calculation by configuring a FBN, all of this by the use of ontologies

Bridging food security gaps in the European High North through the Internet of Food

Food processing, storage, and distribution are at the centre of environmental damage. Food security gaps include failure to track the geographical origin of foods, food waste, food safety and the quality of food products. To achieve sustainability, changes are required in food supply chains and the entire food system. Consumers need information to make informed choices about what to eat. They need to know where food came from, the conditions under which it grew, and the food’s nutritional profile. The food industry has been slow to take advantage of the internet. However, with increasing interests in redistributed manufacturing, circumpolar regions such as the European High North will need to digitise. The Internet of Food (IoF) is an emerging trend. It will make food traceable, transparent, and trustworthy and empower consumers with more personalised food that caters precisely to individual food, diet, and health choices. It is therefore important to build an information infrastructure around the IoF. This chapter examines how food security gaps can be bridged by collating data that will help to leapfrog local foods into the digital era.acceptedVersionPeer reviewe

A solution for processing supply chain events within ontology-based descriptions

The industry is constantly moving towards the research, implementation and deployment of new solutions that permit the optimization of processes. Nowadays, such solutions consist mostly on ICT developments, which permit the collection, distribution, integration, analysis, and manipulation of heterogeneous data. The under way Cloud Collaborative Manufacturing Networks (C2NET) project targets the development of cloud-enabled tools for supporting the SMEs supply network optimization of manufacturing and logistic assets. The C2NET solution includes the implementation of paradigms as e.g. cloud computing or service-oriented and event-driven architectures, used for wide data integration. Among its requirements, the C2NET platform needs a solution for catch, process and react to events triggered in different locations of collaborative manufacturing networks, which are endowed with devices that permits the integration of Cyber-Physical Systems (CPS). This paper presents the architecture and main functionality of a knowledge-based approach that allows processing supply chain events handled by CPS devices. The main component of the presented solution is the SECA ontology, which is a knowledge base that can be updated at runtime. The main purpose of the ontology is to describe events, their status and the actions to be performed once a set of events are triggered in certain order. This research work offers a solution that can be employed by the C2NET platform not only to catch and process events; but also to notify linked data consumers.acceptedVersionPeer reviewe

An Approach for Managing Manufacturing Assets through Radio Frequency Energy Harvesting

The manufacturing industry requests novel solutions that will permit enterprises to stay competitive in the market. This leads to decisions being made based on different technologies that are focused on real-time accurate measurement and monitoring of manufacturing assets. In the context of traceability, radio frequency identification (RFID) tags have been traditionally used for tracking, monitoring, and collecting data of various manufacturing resources operating along the value chain. RFID tags and microelectromechanical systems (MEMS) sensors enable the monitoring of manufacturing assets by providing real-time data. Such devices are usually powered by batteries that need regular maintenance, which in turn leads to delays that affect the overall manufacturing process time. This article presents a low-cost approach to detect and measure radio frequency (RF) signals in assembly lines for optimizing the manufacturing operations in the manufacturing industry. Through the detection and measurement of RF signals, the RF energy can be harvested at certain locations on the assembly line. Then, the harvested energy can be supplied to the MEMS sensors, minimizing the regular maintenance for checking and replacing batteries. This leads to an increase in the operational efficiency and an overall reduction in operational and maintenance costs