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Borja Ramis Ferrer
FAST-Lab., Faculty of Engineering and Natural Sciences, Tampere University, Tampere, Finland

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Review
Published: 03 April 2021 in Knowledge and Information Systems
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The literature on the modeling and management of data generated through the lifecycle of a manufacturing system is split into two main paradigms: product lifecycle management (PLM) and product, process, resource (PPR) modeling. These paradigms are complementary, and the latter could be considered a more neutral version of the former. There are two main technologies associated with these paradigms: ontologies and databases. Database technology is widespread in industry and is well established. Ontologies remain largely a plaything of the academic community which, despite numerous projects and publications, have seen limited implementations in industrial manufacturing applications. The main objective of this paper is to provide a comparison between ontologies and databases, offering both qualitative and quantitative analyses in the context of PLM and PPR. To achieve this, the article presents (1) a literature review within the context of manufacturing systems that use databases and ontologies, identifying their respective strengths and weaknesses, and (2) an implementation in a real industrial scenario that demonstrates how different modeling approaches can be used for the same purpose. This experiment is used to enable discussion and comparative analysis of both modeling strategies.

ACS Style

Borja Ramis Ferrer; Wael M. Mohammed; Mussawar Ahmad; Sergii Iarovyi; Jiayi Zhang; Robert Harrison; Jose Luis Martinez Lastra. Comparing ontologies and databases: a critical review of lifecycle engineering models in manufacturing. Knowledge and Information Systems 2021, 63, 1271 -1304.

AMA Style

Borja Ramis Ferrer, Wael M. Mohammed, Mussawar Ahmad, Sergii Iarovyi, Jiayi Zhang, Robert Harrison, Jose Luis Martinez Lastra. Comparing ontologies and databases: a critical review of lifecycle engineering models in manufacturing. Knowledge and Information Systems. 2021; 63 (6):1271-1304.

Chicago/Turabian Style

Borja Ramis Ferrer; Wael M. Mohammed; Mussawar Ahmad; Sergii Iarovyi; Jiayi Zhang; Robert Harrison; Jose Luis Martinez Lastra. 2021. "Comparing ontologies and databases: a critical review of lifecycle engineering models in manufacturing." Knowledge and Information Systems 63, no. 6: 1271-1304.

Journal article
Published: 30 October 2020 in International journal of simulation: systems, science & technology
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ACS Style

Borja Ramis Ferrer; Sergii Iarovyi; Andrei Lobov; Jose Luis Martinez Lastra; Wael Mohammed. Exemplifying the Potentials of Web Standards for Automation Control in Manufacturing Systems. International journal of simulation: systems, science & technology 2020, 1 .

AMA Style

Borja Ramis Ferrer, Sergii Iarovyi, Andrei Lobov, Jose Luis Martinez Lastra, Wael Mohammed. Exemplifying the Potentials of Web Standards for Automation Control in Manufacturing Systems. International journal of simulation: systems, science & technology. 2020; ():1.

Chicago/Turabian Style

Borja Ramis Ferrer; Sergii Iarovyi; Andrei Lobov; Jose Luis Martinez Lastra; Wael Mohammed. 2020. "Exemplifying the Potentials of Web Standards for Automation Control in Manufacturing Systems." International journal of simulation: systems, science & technology , no. : 1.

Conference paper
Published: 01 October 2019 in IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society
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Manufacturing-oriented enterprises are investing in novel solutions to adapt their cyber and physical resources to the fast and, yet, unexpected changes of global industrial environment. One of the important trends is to work towards development of cognitive systems which are capable to process and analyze complex data using Artificial Intelligence (AI)-based tools and techniques. Therefore, cognition can be already viewed as a requirement for hyper-connected environments e.g., the factories of the future or the Internet of Things (IoT). In this context, there is a need to represent and store the data collected from machines in a format that can be understood and manipulated by both humans and machines. This is feasible by designing and implementing semantic models i.e., ontologies which, in turn, enable inferring implicit data of explicit knowledge, leading to cognition. Moreover, there is a need of granting the access to such information remotely and at system runtime. Within this conceptual article, the authors present a semantic workbench that was developed during a European project aiming at utilization of ontologies for knowledge representation and reasoning in industrial automation systems. Further, this research work proposes the encapsulation of semantic workbench as a service in order to be deployed in cloud-based platforms, hence, enabling remote access of authorized clients at system runtime. The proposed functionalities are also of critical importance in highly complex and distributed environments, like the IoT or industrial ecosystems.

ACS Style

Borja Ramis Ferrer; Wael Mohammed; Jose L.; Jose Luis Martinez Lastra; Stanislaw Strzelczak. A Semantic Workbench for Editing, Querying, Navigating and Distributing Ontologies for Cognitive Manufacturing. IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society 2019, 1, 2767 -2772.

AMA Style

Borja Ramis Ferrer, Wael Mohammed, Jose L., Jose Luis Martinez Lastra, Stanislaw Strzelczak. A Semantic Workbench for Editing, Querying, Navigating and Distributing Ontologies for Cognitive Manufacturing. IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society. 2019; 1 ():2767-2772.

Chicago/Turabian Style

Borja Ramis Ferrer; Wael Mohammed; Jose L.; Jose Luis Martinez Lastra; Stanislaw Strzelczak. 2019. "A Semantic Workbench for Editing, Querying, Navigating and Distributing Ontologies for Cognitive Manufacturing." IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society 1, no. : 2767-2772.

Journal article
Published: 26 August 2019 in Sustainability
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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.

ACS Style

Yuzhuo Cai; Borja Ramis Ferrer; Jose Luis Martinez Lastra. Building University-Industry Co-Innovation Networks in Transnational Innovation Ecosystems: Towards a Transdisciplinary Approach of Integrating Social Sciences and Artificial Intelligence. Sustainability 2019, 11, 4633 .

AMA Style

Yuzhuo Cai, Borja Ramis Ferrer, Jose Luis Martinez Lastra. Building University-Industry Co-Innovation Networks in Transnational Innovation Ecosystems: Towards a Transdisciplinary Approach of Integrating Social Sciences and Artificial Intelligence. Sustainability. 2019; 11 (17):4633.

Chicago/Turabian Style

Yuzhuo Cai; Borja Ramis Ferrer; Jose Luis Martinez Lastra. 2019. "Building University-Industry Co-Innovation Networks in Transnational Innovation Ecosystems: Towards a Transdisciplinary Approach of Integrating Social Sciences and Artificial Intelligence." Sustainability 11, no. 17: 4633.

Conference paper
Published: 01 July 2019 in 2019 IEEE 17th International Conference on Industrial Informatics (INDIN)
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Over the last decades, the Industrial Automation domain has exhibited an exponential growth of robots’ deployment at factory shop floors. The main objective is to increase efficiency and productivity at a reasonable cost, which is lowered thanks to the robot lifespan. But not all the manual tasks, the tasks requiring high-level of dexterity, are yet replaced by robots. In fact, Europe is moving towards the creation of efficient workspaces where both robots and human operators can work safely. In this context, there is a clear intention of achieving solutions that involve collaborative robots, a.k.a. "cobots" or co-robots, for permitting a safe interaction between robots and humans working for the same or interrelated processes. Many manufactures started to present their products but those arrived before the industry have clear and several needs of this particular technology. This article presents a human-robot collaborative assembly workstation, composed by the ABB YuMi robot that interacts with a human operation in order to assembly a product box, as a part of a large-scale process. Assembly process, workstation design, implementation and its validation are illustrated. Then, this paper aims to summarize advantages and challenges of implementing cobots by exemplifying a real scenario of collaborative interaction between a cobot and a human operator, feasible to implement at any industrial facility.

ACS Style

Ronal Bejarano; Borja Ramis Ferrer; Wael Mohammed; Jose Luis Martinez Lastra. Implementing a Human-Robot Collaborative Assembly Workstation. 2019 IEEE 17th International Conference on Industrial Informatics (INDIN) 2019, 1, 557 -564.

AMA Style

Ronal Bejarano, Borja Ramis Ferrer, Wael Mohammed, Jose Luis Martinez Lastra. Implementing a Human-Robot Collaborative Assembly Workstation. 2019 IEEE 17th International Conference on Industrial Informatics (INDIN). 2019; 1 ():557-564.

Chicago/Turabian Style

Ronal Bejarano; Borja Ramis Ferrer; Wael Mohammed; Jose Luis Martinez Lastra. 2019. "Implementing a Human-Robot Collaborative Assembly Workstation." 2019 IEEE 17th International Conference on Industrial Informatics (INDIN) 1, no. : 557-564.

Conference paper
Published: 01 July 2019 in 2019 IEEE 17th International Conference on Industrial Informatics (INDIN)
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Currently, the implementation of virtual, augmented and mixed realities-based solutions is one of the megatrends in the Industrial Automation domain. In this context, Virtual Reality (VR) permits the development of virtual environments that can be used for different purposes, such as designing, monitoring and/or training industrial machinery. Moreover, the access to such environments can be remote, facilitating the interaction of humans with cyber models of real-world systems without the need of being at the system facilities. This article presents a virtual environment that has been developed within VR technologies not only for training and monitoring robot tasks but also to be done at robot operation runtime within an on-line mode. In this manner, the user of the presented environment is able to train and monitor de tasks at the same time that the robot is operating. The research work is validated within the on-line training and monitoring tasks of an ABB IRB 14000 industrial robot.

ACS Style

Leire Amezua Hormaza; Wael Mohammed; Borja Ramis Ferrer; Ronal Bejarano; Jose Luis Martinez Lastra. On-line Training and Monitoring of Robot Tasks through Virtual Reality. 2019 IEEE 17th International Conference on Industrial Informatics (INDIN) 2019, 1, 841 -846.

AMA Style

Leire Amezua Hormaza, Wael Mohammed, Borja Ramis Ferrer, Ronal Bejarano, Jose Luis Martinez Lastra. On-line Training and Monitoring of Robot Tasks through Virtual Reality. 2019 IEEE 17th International Conference on Industrial Informatics (INDIN). 2019; 1 ():841-846.

Chicago/Turabian Style

Leire Amezua Hormaza; Wael Mohammed; Borja Ramis Ferrer; Ronal Bejarano; Jose Luis Martinez Lastra. 2019. "On-line Training and Monitoring of Robot Tasks through Virtual Reality." 2019 IEEE 17th International Conference on Industrial Informatics (INDIN) 1, no. : 841-846.

Conference paper
Published: 01 July 2019 in 2019 IEEE 17th International Conference on Industrial Informatics (INDIN)
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One of the major objectives of international projects in the field of Industrial Automation is to achieve a proper and safe human-robot collaboration. This will permit the coexistence of both humans and robots at factory shop floors, where each one has a clear role along the industrial processes. It’s a matter of fact that machines, including robots, have specific features that determine the kind of operation(s) that they can perform better. Similarly, human operators have a set of skills and knowledge that permits them to accomplish their tasks at work. This article proposes the adaptation of robots to the skills of human operators in order to implement an efficient, safe and comfortable synergy between robots and humans that are working at the same workspace. As a representative case of study, this research work describes an approach for adapting a cobot workstation to human operators within an installed deep learning camera on the cobot. First, the camera is used to recognize the human operator that collaborates with the robot. Then, the corresponding profile is processed and serves as an input to a module in charge of adapting specific features of the robot. In this manner, the robot can adapt e.g., to the speed of operation according to the skills of the worker or deliver parts to be manipulated according to the handedness of the human worker. In addition, the deep learning camera is used for stopping the process at any time that the worked leaves unexpectedly the workstation.

ACS Style

Olatz De Miguel Lazaro; Wael Mohammed; Borja Ramis Ferrer; Ronal Bejarano; Jose Luis Martinez Lastra. An Approach for adapting a Cobot Workstation to Human Operator within a Deep Learning Camera. 2019 IEEE 17th International Conference on Industrial Informatics (INDIN) 2019, 1, 789 -794.

AMA Style

Olatz De Miguel Lazaro, Wael Mohammed, Borja Ramis Ferrer, Ronal Bejarano, Jose Luis Martinez Lastra. An Approach for adapting a Cobot Workstation to Human Operator within a Deep Learning Camera. 2019 IEEE 17th International Conference on Industrial Informatics (INDIN). 2019; 1 ():789-794.

Chicago/Turabian Style

Olatz De Miguel Lazaro; Wael Mohammed; Borja Ramis Ferrer; Ronal Bejarano; Jose Luis Martinez Lastra. 2019. "An Approach for adapting a Cobot Workstation to Human Operator within a Deep Learning Camera." 2019 IEEE 17th International Conference on Industrial Informatics (INDIN) 1, no. : 789-794.

Conference paper
Published: 01 July 2019 in 2019 IEEE 17th International Conference on Industrial Informatics (INDIN)
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Robots are widely used in industrial manufacturing processes and play an important role in the enhancement of industrial organizations productivity. One of the major issues that engineers are facing is that, current programming methods are too time-consuming and they lack of intuitiveness use by human users. However, the latest advances in the field of sensors, let manufacturers to develop and produce devices that allow humans to interact with machines in a more intuitive way, reducing the need of additional complex software components, and hence, the required time to establish the aforementioned human-machine interactions. This research work presents an approach for gesture-based on-line programming of industrial robot manipulators. This is achieved by utilizing a combination of devices with a set of integrated, cost-effective visual and bending sensors, in order to precisely track the user's hand position and gestures at system run-time. This continuous tracking allows the robot manipulator to mimic the operator’s hand motion. In addition, desired paths performed by a human with expertise on task execution, are translated into robot targets, composing a new robot path, and are stored for later use. Such path can be modified to fit into different robot manufacturers, programming language. Further steps of the presented approach will include the possibility of path optimization by the industrial manipulator itself.

ACS Style

Antonios Sylari; Borja Ramis Ferrer; Jose Luis Martinez Lastra. Hand Gesture-Based On-Line Programming of Industrial Robot Manipulators. 2019 IEEE 17th International Conference on Industrial Informatics (INDIN) 2019, 1, 827 -834.

AMA Style

Antonios Sylari, Borja Ramis Ferrer, Jose Luis Martinez Lastra. Hand Gesture-Based On-Line Programming of Industrial Robot Manipulators. 2019 IEEE 17th International Conference on Industrial Informatics (INDIN). 2019; 1 ():827-834.

Chicago/Turabian Style

Antonios Sylari; Borja Ramis Ferrer; Jose Luis Martinez Lastra. 2019. "Hand Gesture-Based On-Line Programming of Industrial Robot Manipulators." 2019 IEEE 17th International Conference on Industrial Informatics (INDIN) 1, no. : 827-834.

Journal article
Published: 22 January 2019 in Sensors
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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.

ACS Style

Muhammad Ashhal Tahir; Borja Ramis Ferrer; Jose Luis Martinez Lastra. An Approach for Managing Manufacturing Assets through Radio Frequency Energy Harvesting. Sensors 2019, 19, 438 .

AMA Style

Muhammad Ashhal Tahir, Borja Ramis Ferrer, Jose Luis Martinez Lastra. An Approach for Managing Manufacturing Assets through Radio Frequency Energy Harvesting. Sensors. 2019; 19 (3):438.

Chicago/Turabian Style

Muhammad Ashhal Tahir; Borja Ramis Ferrer; Jose Luis Martinez Lastra. 2019. "An Approach for Managing Manufacturing Assets through Radio Frequency Energy Harvesting." Sensors 19, no. 3: 438.

Conference paper
Published: 01 October 2018 in IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society
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The global market is susceptible to the variation of customer demands and, in turn, the competition among different stakeholders. Lack of resources on factory shop floors may result in many challenges for industries to address customers' needs. Therefore, the adaptation of production systems to ever-increasing demands is crucial for maintaining companies' competitivity. This article presents an approach for developing a flexible manufacturing system throughout the implementation of cloud robotics. The proposed solution employs cloud resources in order to incorporate new functionalities and capabilities in industrial robot cells. As a result, the system will be able to accommodate customized product variants without the need of process and system reconfiguration, at runtime.

ACS Style

Ali Hussnain; Borja Ramis Ferrer; Jose Luis Martinez Lastra. An application of Cloud Robotics for enhancing the Flexibility of Robotic Cells at Factory Shop Floors. IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society 2018, 2963 -2970.

AMA Style

Ali Hussnain, Borja Ramis Ferrer, Jose Luis Martinez Lastra. An application of Cloud Robotics for enhancing the Flexibility of Robotic Cells at Factory Shop Floors. IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society. 2018; ():2963-2970.

Chicago/Turabian Style

Ali Hussnain; Borja Ramis Ferrer; Jose Luis Martinez Lastra. 2018. "An application of Cloud Robotics for enhancing the Flexibility of Robotic Cells at Factory Shop Floors." IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society , no. : 2963-2970.

Conference paper
Published: 01 October 2018 in IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society
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Multi-cloud environments are complex in nature owing to their distributed architecture. This has made it challenging to ascertain the security status and overall performance of multi-cloud application components hosted across several clouds. It has further made it challenging to determine when to carry out corrective actions required to restore normalcy within the environment in the case of anomaly detection. In addition, the increasing security concerns in cloud environments has led to many cloud customers now being interested in knowing the condition of their applications, regarding security. In view of this, it thus becomes necessary to ensure adequate transparency and security awareness in multi-cloud environments. However, this is threatened by absence of standardization and diverse Cloud Service Providers (CSP) platforms. This article presents a framework for evaluating security in multi-cloud applications. The main purpose is to promote transparency and security awareness in multi-cloud environments through the evaluation of application components spread across diverse clouds. The result of this will be the determination of the security status of all the application components as well as the overall multi-cloud environment. This will also improve trust in utilizing multi-clouds.

ACS Style

Samuel Olaiya Afolaranmi; Borja Ramis Ferrer; Jose Luis Martinez Lastra. A Framework for Evaluating Security in Multi-Cloud Environments. IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society 2018, 3059 -3066.

AMA Style

Samuel Olaiya Afolaranmi, Borja Ramis Ferrer, Jose Luis Martinez Lastra. A Framework for Evaluating Security in Multi-Cloud Environments. IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society. 2018; ():3059-3066.

Chicago/Turabian Style

Samuel Olaiya Afolaranmi; Borja Ramis Ferrer; Jose Luis Martinez Lastra. 2018. "A Framework for Evaluating Security in Multi-Cloud Environments." IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society , no. : 3059-3066.

Journal article
Published: 01 September 2018 in Machines
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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.

ACS Style

Borja Ramis Ferrer; Usman Muhammad; Wael M. Mohammed; José L. Martínez Lastra. Implementing and Visualizing ISO 22400 Key Performance Indicators for Monitoring Discrete Manufacturing Systems. Machines 2018, 6, 39 .

AMA Style

Borja Ramis Ferrer, Usman Muhammad, Wael M. Mohammed, José L. Martínez Lastra. Implementing and Visualizing ISO 22400 Key Performance Indicators for Monitoring Discrete Manufacturing Systems. Machines. 2018; 6 (3):39.

Chicago/Turabian Style

Borja Ramis Ferrer; Usman Muhammad; Wael M. Mohammed; José L. Martínez Lastra. 2018. "Implementing and Visualizing ISO 22400 Key Performance Indicators for Monitoring Discrete Manufacturing Systems." Machines 6, no. 3: 39.

Conference paper
Published: 01 July 2018 in 2018 IEEE 16th International Conference on Industrial Informatics (INDIN)
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Cyber-physical Systems (CPS) in industrial manufacturing facilities demand a continuous interaction with different and a large amount of distributed and networked computing nodes, devices and human operators. These systems are critical to ensure the quality of production and the safety of persons working at the shop floor level. Furthermore, this situation is similar in other domains, such as logistics that, in turn, are connected and affect the overall production efficiency. In this context, this article presents some key steps for integrating three pillars of CPS (production line, logistics and facilities) into the current smart manufacturing environments in order to adopt an industrial Cyber-Physical Systems of Systems (CPSoS) paradigm. The approach is focused on the integration in several digital functionalities in a cloud-based platform to allow a real time multiple devices interaction, data analytics/sharing and machine learning-based global reconfiguration to increase the management and optimization capabilities for increasing the quality of facility services, safety and energy efficiency and industrial productivity. Conceptually, isolated systems may enhance their capabilities by accessing to information of other systems. The approach introduces particular vision, main components, potential and challenges of the envisioned CPSoS. In addition, the description of one scenario for realizing the CPSoS vision is presented. The results herein presented will pave the way for the adoption of CPSoS that can be used as a pilot for further research on this emerging topic.

ACS Style

Borja Ramis Ferrer; Wael M. Mohammed; Jose L. Martinez Lastra; Alberto Villalonga; Gerardo Beruvides; Fernando Castano; Rodolfo E. Haber. Towards the Adoption of Cyber-Physical Systems of Systems Paradigm in Smart Manufacturing Environments. 2018 IEEE 16th International Conference on Industrial Informatics (INDIN) 2018, 792 -799.

AMA Style

Borja Ramis Ferrer, Wael M. Mohammed, Jose L. Martinez Lastra, Alberto Villalonga, Gerardo Beruvides, Fernando Castano, Rodolfo E. Haber. Towards the Adoption of Cyber-Physical Systems of Systems Paradigm in Smart Manufacturing Environments. 2018 IEEE 16th International Conference on Industrial Informatics (INDIN). 2018; ():792-799.

Chicago/Turabian Style

Borja Ramis Ferrer; Wael M. Mohammed; Jose L. Martinez Lastra; Alberto Villalonga; Gerardo Beruvides; Fernando Castano; Rodolfo E. Haber. 2018. "Towards the Adoption of Cyber-Physical Systems of Systems Paradigm in Smart Manufacturing Environments." 2018 IEEE 16th International Conference on Industrial Informatics (INDIN) , no. : 792-799.

Conference paper
Published: 01 July 2018 in 2018 IEEE 16th International Conference on Industrial Informatics (INDIN)
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Data collection requires homogenization of the data prior to processing it. This can create a challenge to the companies since data have varicose formats and schemas. This paper discusses the implementation of data collection framework using the PLANTCockpit open source platform, which is an integration platform for business processes. The framework is extended to fetch data from heterogeneous sources and then, allow the user to select the relevant data that matches his/her needs. In addition to this, the extendable framework also makes it possible to select the output data structure based on the user's requirements. Defining such a framework can reduce company's efforts for reshaping and modifying their architectures to handle new challenges posed by the ever-changing data. The framework not only restricts one to collection and transformation, but also provides an option to perform available processing techniques on the transformed data structure. The proposed framework has been tested on a cloud-based platform provided by the Cloud Collaborative Manufacturing Networks (C2NET) project.

ACS Style

Umer Iftikhar; Wael M. Mohammed; Borja Ramis Ferrer; Jose L. Martinez Lastra. A Framework for Data Collection, Transformation and Processing in Industrial Systems. 2018 IEEE 16th International Conference on Industrial Informatics (INDIN) 2018, 707 -712.

AMA Style

Umer Iftikhar, Wael M. Mohammed, Borja Ramis Ferrer, Jose L. Martinez Lastra. A Framework for Data Collection, Transformation and Processing in Industrial Systems. 2018 IEEE 16th International Conference on Industrial Informatics (INDIN). 2018; ():707-712.

Chicago/Turabian Style

Umer Iftikhar; Wael M. Mohammed; Borja Ramis Ferrer; Jose L. Martinez Lastra. 2018. "A Framework for Data Collection, Transformation and Processing in Industrial Systems." 2018 IEEE 16th International Conference on Industrial Informatics (INDIN) , no. : 707-712.

Conference paper
Published: 01 July 2018 in 2018 IEEE 16th International Conference on Industrial Informatics (INDIN)
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Industry 4.0 is about the interconnectivity and digitalisation of industrial systems that need to be integrated in order to improve the efficiency of resources and, in turn, processes. Both research and commercial sectors are working towards addressing specific challenges, such as data modelling, collection and processing. A correct manipulation and interpretation of data is critical and, now, more difficult than ever due to the dramatic increment of the amount of data generated at different levels of enterprises. Ultimately, this research work presents a solution, integrated with an existing cloud-based platform, for collecting and processing real-time factory shop floor streams of data. Such solution is an IoT-based development, which consist on both IoT hub and gateway that permit the consumption and communication of device information. The required message exchange is done within state of the art technologies and protocols e.g., MQTT protocol and REST-based interface. The implementation of the solution is demonstrated through an industrial-based scenario.

ACS Style

Wael M. Mohammed; Borja Ramis Ferrer; Umer Iftikhar; Jose L. Martinez Lastra; Javier Hitado Simarro. Supporting a Cloud Platform with Streams of Factory Shop Floor Data in the Context of the Intustry 4.0. 2018 IEEE 16th International Conference on Industrial Informatics (INDIN) 2018, 786 -791.

AMA Style

Wael M. Mohammed, Borja Ramis Ferrer, Umer Iftikhar, Jose L. Martinez Lastra, Javier Hitado Simarro. Supporting a Cloud Platform with Streams of Factory Shop Floor Data in the Context of the Intustry 4.0. 2018 IEEE 16th International Conference on Industrial Informatics (INDIN). 2018; ():786-791.

Chicago/Turabian Style

Wael M. Mohammed; Borja Ramis Ferrer; Umer Iftikhar; Jose L. Martinez Lastra; Javier Hitado Simarro. 2018. "Supporting a Cloud Platform with Streams of Factory Shop Floor Data in the Context of the Intustry 4.0." 2018 IEEE 16th International Conference on Industrial Informatics (INDIN) , no. : 786-791.

Conference paper
Published: 01 July 2018 in 2018 IEEE 16th International Conference on Industrial Informatics (INDIN)
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There is a trend about the adoption of Knowledge Representation and Reasoning formalisms, such as ontologies, for industrial automation. For example, semantic models are used as knowledge bases that encapsulate different type of information of manufacturing systems, e.g., statuses and capabilities of their cyber and physical resources. Moreover, these models can be updated and accessed during runtime. In this context, models are becoming a critical part of the system infrastructure for both controlling and monitoring activities. However, models tend to be designed for specific purposes and not standardized. This is an issue because the employed formalisms, such as ontologies, emerged in order to bring an engineering tool for commonly classifying, defining, and sharing information. This article proposes the development of modular ontologies based on different parts of the ISA-95 standard for describing the product, process, and resource information of manufacturing systems. In addition, this research work demonstrates a set of semantic rules that may be used for inferring implicit knowledge of the ontology that permits the automatic checking of the required machines to manufacture different product variants.

ACS Style

Ahmadi Seyedamir; Borja Ramis Ferrer; Jose Luis Martinez Lastra. An ISA-95 based Ontology for Manufacturing Systems Knowledge Description Extended with Semantic Rules. 2018 IEEE 16th International Conference on Industrial Informatics (INDIN) 2018, 374 -380.

AMA Style

Ahmadi Seyedamir, Borja Ramis Ferrer, Jose Luis Martinez Lastra. An ISA-95 based Ontology for Manufacturing Systems Knowledge Description Extended with Semantic Rules. 2018 IEEE 16th International Conference on Industrial Informatics (INDIN). 2018; ():374-380.

Chicago/Turabian Style

Ahmadi Seyedamir; Borja Ramis Ferrer; Jose Luis Martinez Lastra. 2018. "An ISA-95 based Ontology for Manufacturing Systems Knowledge Description Extended with Semantic Rules." 2018 IEEE 16th International Conference on Industrial Informatics (INDIN) , no. : 374-380.

Review
Published: 04 May 2018 in International Journal of Environmental Health Research
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The monitoring of ambient conditions in indoor spaces is very essential owing to the amount of time spent indoors. Specifically, the monitoring of air quality is significant because contaminated air affects the health, comfort and productivity of occupants. This research work presents a technology review of prototyping platforms for monitoring ambient conditions in indoor spaces. It involves the research on sensors (for CO2, air quality and ambient conditions), IoT platforms, and novel and commercial prototyping platforms. The ultimate objective of this review is to enable the easy identification, selection and utilisation of the technologies best suited for monitoring ambient conditions in indoor spaces. Following the review, it is recommended to use metal oxide sensors, optical sensors and electrochemical sensors for IAQ monitoring (including NDIR sensors for CO2 monitoring), Raspberry Pi for data processing, ZigBee and Wi-Fi for data communication, and ThingSpeak IoT platform for data storage, analysis and visualisation.

ACS Style

Samuel Olaiya Afolaranmi; Borja Ramis Ferrer; Jose Luis Martinez Lastra. Technology review: prototyping platforms for monitoring ambient conditions. International Journal of Environmental Health Research 2018, 28, 253 -279.

AMA Style

Samuel Olaiya Afolaranmi, Borja Ramis Ferrer, Jose Luis Martinez Lastra. Technology review: prototyping platforms for monitoring ambient conditions. International Journal of Environmental Health Research. 2018; 28 (3):253-279.

Chicago/Turabian Style

Samuel Olaiya Afolaranmi; Borja Ramis Ferrer; Jose Luis Martinez Lastra. 2018. "Technology review: prototyping platforms for monitoring ambient conditions." International Journal of Environmental Health Research 28, no. 3: 253-279.

Journal article
Published: 01 May 2018 in CIRP Journal of Manufacturing Science and Technology
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The paradigm shift from mass production to mass customisation and reduced product lifecycles requires continuous re-engineering/configuration of modern manufacturing systems. Although efforts are being made to design and build manufacturing systems based on the paradigms of changeability, reconfigurability, and flexibility, the knowledge of the system's capability remains unstructured and isolated from product design and engineering tools. As a result, introducing product design changes are costly, time-consuming and error-prone. To address this problem, this research utilises a Product, Process, and Resource (PPR) ontology with a view to supporting changes through information integration and knowledge generation. The approach moves away from product-centric tools such as Product Lifecycle Management (PLM) and thus a heterarchical model of the system is created. The contribution of this work is to demonstrate how modular ontologies can be utilised in a practical and industrially relevant manner by integrating the data structure of a set of component-based virtual engineering tools into the Resource domain. The research presents a proof-of-concept of the proposed approach using an automated engine assembly station as a case study. Inferences are made from explicit knowledge through rules and mapping as to whether both Product and Process requirements are met by Resource domain capabilities. The approach used in this work has the potential to significantly improve the workflow as and when new products are introduced or modifications need to be made as the scope of change can be assessed rapidly resulting in more focused engineering and design work.

ACS Style

Mussawar Ahmad; Borja Ramis Ferrer; Bilal Ahmad; Daniel Vera; Jose L. Martinez Lastra; Robert Harrison. Knowledge-based PPR modelling for assembly automation. CIRP Journal of Manufacturing Science and Technology 2018, 21, 33 -46.

AMA Style

Mussawar Ahmad, Borja Ramis Ferrer, Bilal Ahmad, Daniel Vera, Jose L. Martinez Lastra, Robert Harrison. Knowledge-based PPR modelling for assembly automation. CIRP Journal of Manufacturing Science and Technology. 2018; 21 ():33-46.

Chicago/Turabian Style

Mussawar Ahmad; Borja Ramis Ferrer; Bilal Ahmad; Daniel Vera; Jose L. Martinez Lastra; Robert Harrison. 2018. "Knowledge-based PPR modelling for assembly automation." CIRP Journal of Manufacturing Science and Technology 21, no. : 33-46.

Conference paper
Published: 01 May 2018 in 2018 IEEE Industrial Cyber-Physical Systems (ICPS)
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The evolution of industries and their needs towards the implementation of Industry 4.0 based systems has brought both new technological challenges and opportunities. This article proposes the adoption and deployment of cloud robotics at factories to enhance the control and monitoring of processes, such as handling materials multiple assemblies in single cells. The ultimate research objective of this research is the offloading computation and integrating cloud robotics into an industrial scenario. However, the investigation of state of the art techniques, tools and technologies, and the development of functional prototypes is beforehand required. Then, this article presents a small-scale system as a prototype that employs the Google cloud vision API as a resource that, in turn, is used by networked agents for supporting the decision-making in the process of handling material commodities at factory shop floor. The overall concept as well as the interaction between the main actors of the prototype is detailed. Finally, further research directions are discussed.

ACS Style

Ali Hussnain; Borja Ramis Ferrer; Jose Luis Martinez Lastra. Towards the deployment of cloud robotics at factory shop floors: A prototype for smart material handling. 2018 IEEE Industrial Cyber-Physical Systems (ICPS) 2018, 44 -50.

AMA Style

Ali Hussnain, Borja Ramis Ferrer, Jose Luis Martinez Lastra. Towards the deployment of cloud robotics at factory shop floors: A prototype for smart material handling. 2018 IEEE Industrial Cyber-Physical Systems (ICPS). 2018; ():44-50.

Chicago/Turabian Style

Ali Hussnain; Borja Ramis Ferrer; Jose Luis Martinez Lastra. 2018. "Towards the deployment of cloud robotics at factory shop floors: A prototype for smart material handling." 2018 IEEE Industrial Cyber-Physical Systems (ICPS) , no. : 44-50.

Proceedings article
Published: 01 May 2018 in 2018 IEEE Industrial Cyber-Physical Systems (ICPS)
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Performance measurement tools and techniques have become very significant in today's industries for increasing the efficiency of their processes in order to face the competitive market. The first step towards performance measurement is the real-time monitoring and gathering of the data from the manufacturing system. Applying these performance measurement techniques on real-world industry in a way that is more general and efficient is the next challenge. This paper presents a methodology for implementing the key performance indicators defined in the ISO 22400 standard-Automation systems and integration, Key performance indicators (KPIs) for manufacturing operations management. The proposed methodology is implemented on a multi robot line simulator for measuring its performance at runtime. The approach implements a knowledge-based system within an ontology model which describes the environment, the system and the KPIs. In fact, the KPIs semantic descriptions are based on the data models presented in the Key Performance Indicators Markup Language (KPIML), which is an XML implementation of models developed by the Manufacturing Enterprise Solutions Association (MESA) international organization.

ACS Style

Usman Muhammad; Borja Ramis Ferrer; Wael M. Mohammed; Jose L. Martinez Lastra. An approach for implementing key performance indicators of a discrete manufacturing simulator based on the ISO 22400 standard. 2018 IEEE Industrial Cyber-Physical Systems (ICPS) 2018, 629 -636.

AMA Style

Usman Muhammad, Borja Ramis Ferrer, Wael M. Mohammed, Jose L. Martinez Lastra. An approach for implementing key performance indicators of a discrete manufacturing simulator based on the ISO 22400 standard. 2018 IEEE Industrial Cyber-Physical Systems (ICPS). 2018; ():629-636.

Chicago/Turabian Style

Usman Muhammad; Borja Ramis Ferrer; Wael M. Mohammed; Jose L. Martinez Lastra. 2018. "An approach for implementing key performance indicators of a discrete manufacturing simulator based on the ISO 22400 standard." 2018 IEEE Industrial Cyber-Physical Systems (ICPS) , no. : 629-636.