Low-Code as Enabler of Digital Transformation in Manufacturing Industry

[EN] Currently, enterprises have to make quick and resilient responses to changing market requirements. In light of this, low-code development platforms provide the technology mechanisms to facilitate and automate the development of software applications to support current enterprise needs and promote digital transformation. Based on a theory-building research methodology through the literature and other information sources review, the main contribution of this paper is the current characterisation of the emerging low-code domain following the foundations of the computer-aided software engineering field. A context analysis, focused on the current status of research related to the low-code development platforms, is performed. Moreover, benchmarking among the existing low-code development platforms addressed to manufacturing industry is analysed to identify the current lacking features. As an illustrative example of the emerging low-code paradigm and respond to the identified uncovered features, the virtual factory open operating system (vf-OS) platform is described as an open multi-sided low-code framework able to manage the overall network of a collaborative manufacturing and logistics environment that enables humans, applications, and Internet of Things (IoT) devices to seamlessly communicate and interoperate in the interconnected environment, promoting resilient digital transformation.This work was supported in part by the European Commission under the Grant Agreements No. 723710 and 825631.Sanchis, R.; Garcia-Perales, O.; Fraile Gil, F.; Poler, R. (2020). Low-Code as Enabler of Digital Transformation in Manufacturing Industry. Applied Sciences. 10(1):1-17. https://doi.org/10.3390/app10010012S117101Sanchis, R., & Poler, R. (2019). Enterprise Resilience Assessment—A Quantitative Approach. Sustainability, 11(16), 4327. doi:10.3390/su11164327Lowcomote: Training the Next Generation of Experts in Scalable Low-Code Engineering Platformshttps://www.se.jku.at/lowcomote-training-the-next-generation-of-experts-in-scalable-low-code-engineering-platforms/Waszkowski, R. (2019). Low-code platform for automating business processes in manufacturing. IFAC-PapersOnLine, 52(10), 376-381. doi:10.1016/j.ifacol.2019.10.060Lundell, B., & Lings, B. (2004). Changing perceptions of CASE technology. Journal of Systems and Software, 72(2), 271-280. doi:10.1016/s0164-1212(03)00087-6Fuggetta, A. (1993). A classification of CASE technology. Computer, 26(12), 25-38. doi:10.1109/2.247645Troy, D., & McQueen, R. (1997). An approach for developing domain specific CASE tools and its application to manufacturing process control. Journal of Systems and Software, 38(2), 165-192. doi:10.1016/s0164-1212(96)00120-3Huff, C. C. (1992). Elements of a realistic CASE tool adoption budget. Communications of the ACM, 35(4), 45-54. doi:10.1145/129852.129856Orlikowski, W. J. (1993). CASE Tools as Organizational Change: Investigating Incremental and Radical Changes in Systems Development. MIS Quarterly, 17(3), 309. doi:10.2307/249774Iivari, J. (1996). Why are CASE tools not used? Communications of the ACM, 39(10), 94-103. doi:10.1145/236156.236183Zolotas, C., Chatzidimitriou, K. C., & Symeonidis, A. L. (2018). RESTsec: a low-code platform for generating secure by design enterprise services. Enterprise Information Systems, 12(8-9), 1007-1033. doi:10.1080/17517575.2018.1462403GAVRILĂ, V., BĂJENARU, L., & DOBRE, C. (2019). Modern Single Page Application Architecture: A Case Study. Studies in Informatics and Control, 28(2). doi:10.24846/v28i2y201911Wu, Y., Wang, S., Bezemer, C.-P., & Inoue, K. (2018). How do developers utilize source code from stack overflow? Empirical Software Engineering, 24(2), 637-673. doi:10.1007/s10664-018-9634-5Hamming, R. W. (1950). Error Detecting and Error Correcting Codes. Bell System Technical Journal, 29(2), 147-160. doi:10.1002/j.1538-7305.1950.tb00463.xForresterhttps://go.forrester.com/The Maturity of Visual Programming. Режим дoступуhttp://www. craft. ai/blog/the-maturity-of-visualprogrammingVirtual Factory Operating Systemwww.vf-OS.euvf-OS D1.1: Vision Consensushttps://www.vf-os.eu/resultsvf-OS Wikihttps://cigipsrv1.cigip.upv.es:4430/mediawiki/index.php/Wiki_Homevf-OS D2.1: Global Architecture Definitionhttps://www.vf-os.eu/resultsSiemens MindSpherehttps://new.siemens.com/vn/en/products/software/mindsphere.htmlPTC ThingWorx Platformhttps://www.ptc.com/en/resources/iiot/product-brief/thingworx-platformGE Predixhttps://www.ge.com/digital/iiot-platformIBM Cloudhttps://www.ibm.com/cloudMicrosoft Azure IOT Suitehttps://azure.microsoft.com/es-es/blog/microsoft-azure-iot-suite-connecting-your-things-to-the-cloud/Software AG ADAMOShttps://www.softwareag.com/corporate/company/adamos/default.htm

An Intelligent model for supporting Edge Migration for Virtual Function Chains in Next Generation Internet of Things

The developments on next generation IoT sensing devices, with the advances on their low power computational capabilities and high speed networking has led to the introduction of the edge computing paradigm. Within an edge cloud environment, services may generate and consume data locally, without involving cloud computing infrastructures. Aiming to tackle the low computational resources of the IoT nodes, Virtual-Function-Chain has been proposed as an intelligent distribution model for exploiting the maximum of the computational power at the edge, thus enabling the support of demanding services. An intelligent migration model with the capacity to support Virtual-Function-Chains is introduced in this work. According to this model, migration at the edge can support individual features of a Virtual-Function-Chain. First, auto-healing can be implemented with cold migrations, if a Virtual Function fails unexpectedly. Second, a Quality of Service monitoring model can trigger live migrations, aiming to avoid edge devices overload. The evaluation studies of the proposed model revealed that it has the capacity to increase the robustness of an edge-based service on low-powered IoT devices. Finally, comparison with similar frameworks, like Kubernetes, showed that the migration model can effectively react on edge network fluctuations

Framework for IoT Service Oriented Systems

The forth industrial revolution is here, and with it Industry 4.0, which translates in many changes to the industry. With the introduction of paradigms like Internet of Things, Cyber Physical Systems or Cloud Computing, the so called Smart Factories are becoming a main part of today’s manufacturing systems. The vf-OS Project, where this thesis falls, intends to be an Open Operating System for Virtual Factories where the overall network of a collaborative manufacturing and logistics environment can be managed and thus enabling humans, applications and devices to communicate and interoperate in an interconnected operative environment. This thesis intends to contribute to the vision that any kind of sensor or actuator plugged to the virtual factory network, becomes promptly accessible in the operative environment and the services that it provides can be accessed and used by any API composing the system. Finally, it also aims to prove that an IoT Service Oriented Sys-tem constituted of open software components can be of great assistance and provide numerous contributions to the emerging Industry 4.0 and consequently to the Factories of the Future. With that aim, this thesis will focus on the development of two out of five inter-connected applications that answer not only to different use case scenarios presented in the vf-OS but also provide solutions to answer a practical agriculture scenario, which uses mainly IoT devices and other cutting-edge technologies like cloud compu-ting and FIWARE

A Framework for Service-Oriented Architecture (SOA)-Based IoT Application Development

Funding: This research was partially supported by funds provided by the European Commission in the scope of FoF/H2020-723710 vf-OS, ICT/H2020-825631 ZDMP projects, and by the FCT— Fundação para a Ciência e a Tecnologia in the scope of UIDB/00066/2020 related to CTS—Centro de Tecnologia e Sistemas research unit.In the last decades, the increasing complexity of industrial information technology has led to the emergence of new trends in manufacturing. Factories are using multiple Internet of Things (IoT) platforms to harvest sensor information to improve production. Such a transformation contributes to efficiency growth and reduced production costs. To deal with the heterogeneity of the services within an IoT system, Service-Oriented Architecture (SOA) is referred to in the literature as being advantageous for the design and development of software to support IoT-based production processes.The aim of SOA-based design is to provide the leverage to use and reuse loosely coupled IoT services at the middleware layer to minimise system integration problems. We propose a system architecture that follows the SOA architectural pattern and enables developers and business process designers to dynamically add, query or use instances of existing modular software in the IoT context. Furthermore, an analysis of utilization of modular software that presents some challenges and limitations of this approach is also in the scope of this workpublishersversionpublishe

Driving Manufacturing Systems for the Fourth Industrial Revolution

It has been a long way since the aroused of the Industry 4.0 and the companies' reality is not already align with this new concept. Industry 4.0 is ongoing slowly as it was expected that its maturity level should be higher. The companies´ managers should have a different approach to the adoption of the industry 4.0 enabling technologies on their manufacturing systems to create smart nets along all production process with the connection of elements on the manu-facturing system such as machines, employees, and systems. These smart nets can control and make autonomous decisions efficiently. Moreover, in the industry 4.0 environment, companies can predict problems and failures along all production process and react sooner regarding maintenance or production changes for instance. The industry 4.0 environment is a challenging area because changes the relation between humans and machines. In this way, the scope of this thesis is to contribute to companies adopting the industry 4.0 enabling technologies in their manufacturing systems to improve their competitiveness to face the incoming future. For this purpose, this thesis integrates a research line oriented to i) the understanding of the industry 4.0 concepts, and its enabling technologies to perform the vision of the smart factory, ii) the analysis of the industry 4.0 maturity level on a regional industrial sector and to understand how companies are facing the digital transformation challenges and its barriers, iii) to analyze in deep the industry 4.0 adoption in a company and understand how this company can reach higher maturity levels, and iv) the development of strategic scenarios to help companies on the digital transition, proposing risk mitigations plans and a methodology to develop stra-tegic scenarios. This thesis highlights several barriers to industry 4.0 adoption and also brings new ones to academic and practitioner discussion. The companies' perception related to these barriers Is also discussed in this thesis. The findings of this thesis are of significant interest to companies and managers as they can position themselves along this research line and take advantage of it using all phases of this thesis to perform a better knowledge of this industrial revolution, how to perform better industry 4.0 maturity levels and they can position themselves in the proposed strategic scenarios to take the necessary actions to better face this industrial revolution. In this way, it is proposed this research line for companies to accelerate their digital transformation.Já existe um longo percurso desde o aparecimento da indústria 4.0 e a realidade das empresas ainda não está alinhada com este novo conceito. A indústria 4.0 está em andamento lento, pois era esperado que o seu nível de maturidade fosse maior. Os gestores das empresas devem ter uma abordagem diferente na adoção das tecnologias facilitadoras da indústria 4.0 nos seus sistemas produtivos para criar redes inteligentes ao longo de todo o processo produtivo com a conexão de elementos do sistema produtivo como máquinas, operários e sistemas. Estas redes inteligentes podem controlar e tomar decisões autónomas com eficiência. Além disso, no ambiente da indústria 4.0, as empresas podem prever problemas e falhas ao longo de todo o processo produtivo e reagir mais cedo em relação a manutenções ou mudanças de produção, por exemplo. O ambiente da indústria 4.0 é uma área desafiadora devido às mudanças na relação entre humanos e máquinas. Desta forma, o objetivo desta tese é contribuir para que as empresas adotem as tecnologias facilitadoras das indústria 4.0 nos seus sistemas produtivos por forma a melhorar sua competitividade para enfrentar o futuro que se aproxima. Para isso, esta tese integra uma linha de investigação orientada para i) a compreensão dos conceitos da indústria 4.0, e suas tecnologias facilitadores para realizar a visão da fábrica inteligente, ii) a análise do nível de maturidade da indústria 4.0 num setor industrial regional e entender como as empresas estão enfrentando os desafios da transformação digital e suas barreiras, iii) analisar a fundo a adoção da indústria 4.0 numa empresa e entender como essa empresa pode atingir níveis mais elevados de maturidade, e iv) o desenvolvimento de cenários estratégicos para ajudar as empresas na transição digital, propondo planos de mitigação de riscos e uma metodologia para desenvolver cenários estratégicos. Esta tese destaca várias barreiras à adoção da indústria 4.0 e também traz novas barreiras para a discussão acadêmica e profissional. A perceção das empresas em relação a essas barreiras também é discutida nesta tese. As descobertas nesta tese são de grande interesse para empresas e gestores, pois podem-se posicionar ao longo desta linha de investigação e aproveitá-la utilizando todas as fases desta tese para obter um melhor conhecimento desta revolução industrial, como obter melhores níveis de maturidade da indústria 4.0 e possam posicionar-se nos cenários estratégicos propostos por forma a tomar as ações necessárias para melhorar o envolvimento nesta revolução industrial. Desta forma, propõe-se esta linha de investigação para que as empresas acelerem a sua transformação digital

Intelligent decision support for maintenance: an overview and future trends

The changing nature of manufacturing, in recent years, is evident in industry’s willingness to adopt network-connected intelligent machines in their factory development plans. A number of joint corporate/government initiatives also describe and encourage the adoption of Artificial Intelligence (AI) in the operation and management of production lines. Machine learning will have a significant role to play in the delivery of automated and intelligently supported maintenance decision-making systems. While e-maintenance practice provides aframework for internet-connected operation of maintenance practice the advent of IoT has changed the scale of internetworking and new architectures and tools are needed. While advances in sensors and sensor fusion techniques have been significant in recent years, the possibilities brought by IoT create new challenges in the scale of data and its analysis. The development of audit trail style practice for the collection of data and the provision of acomprehensive framework for its processing, analysis and use should be avaluable contribution in addressing the new data analytics challenges for maintenance created by internet connected devices. This paper proposes that further research should be conducted into audit trail collection of maintenance data, allowing future systems to enable ‘Human in the loop’ interactions

Trustworthy Industrial IoT Gateways for Interoperability Platforms and Ecosystems

[EN] The industrial Internet of Things (IIoT) is having a significant impact in the manufacturing industry, especially in the context of horizontal integration of operational systems in factories as part of information systems in supply chains. Manufacturing companies can use this technology to create data streams along the supply chain that monitor and control manufacturing and logistic processes, to in the end make these data streams interoperable with other software systems and to enable smart interactions among supply chain processes. However, the provision of these data streams may expose manufacturing operational systems to cyber-attacks. Therefore, cybersecurity is a critical aspect to design trustworthy gateways, which are system components that implement interoperability mechanisms between operational systems and information systems. Gateways must provide security mechanisms at different system layers to minimize threats. This paper presents the Device Drivers security architecture: trustworthy gateways between operational technology and information technology used in the virtual factory open operating system (vf-OS) platform, which is a multisided platform orientated to manufacturing and logistics companies to enable collaboration among supply chains in all sectors. The main contribution of this paper is the evaluation of fallback mechanisms to improve resilience. In situations when the system may be under attack, the proposed mechanisms provide means to quickly recover component availability, by applying alternative security measures to minimize the threat at the same time. Other significant contributions are: a description of the threat model for Device Drivers, a presentation of the security countermeasures implemented in the vf-OS system, the mapping of the vf-OS response objectives to the different characteristics of a trustworthy system: security, privacy, reliability, safety, and resilience and how the proposed countermeasures complement this response.This work was supported by the European Commission under the Grant 723710. (Corresponding author: Francisco Fraile.)Fraile Gil, F.; Tagawa, T.; Poler, R.; Ortiz Bas, Á. (2018). Trustworthy Industrial IoT Gateways for Interoperability Platforms and Ecosystems. IEEE Internet of Things. 5(6):4506-4514. https://doi.org/10.1109/JIOT.2018.2832041S450645145

IoT data processing pipeline in FoF perspective

With the development in the contemporary industry, the concepts of ICT and IoT are gaining more importance, as they are the foundation for the systems of the future. Most of the current solutions converge into transforming the traditional industry in new smart interconnected factories, aware of its context, adaptable to different environments and capable of fully using its resources. However, the full potential for ICT manufacturing has not been achieved, since there is not a universal or standard architecture or model that can be applied to all the existing systems, to tackle the heterogeneity of the existing devices. In a common factory, exists a large amount of information that needs to be processed into the system in order to define event rules accordingly to the related contextual knowledge, to later execute the needed actions. However, this information is sometimes heterogeneous, meaning that it cannot be accessed or understood by the components of the system. This dissertation analyses the existing theories and models that may lead to seamless and homogeneous data exchange and contextual interpretation. A framework based on these theories is proposed in this dissertation, that aims to explore the situational context formalization in order to adequately provide appropriate actions

An intelligent model for supporting edge migration for virtual function chains in next generation internet of things

The developments on next generation IoT sensing devices, with the advances on their low power computational capabilities and high speed networking has led to the introduction of the edge computing paradigm. Within an edge cloud environment, services may generate and consume data locally, without involving cloud computing infrastructures. Aiming to tackle the low computational resources of the IoT nodes, Virtual-Function-Chain has been proposed as an intelligent distribution model for exploiting the maximum of the computational power at the edge, thus enabling the support of demanding services. An intelligent migration model with the capacity to support Virtual-Function-Chains is introduced in this work. According to this model, migration at the edge can support individual features of a Virtual-Function-Chain. First, auto-healing can be implemented with cold migrations, if a Virtual Function fails unexpectedly. Second, a Quality of Service monitoring model can trigger live migrations, aiming to avoid edge devices overload. The evaluation studies of the proposed model revealed that it has the capacity to increase the robustness of an edge-based service on low-powered IoT devices. Finally, comparison with similar frameworks, like Kubernetes, showed that the migration model can effectively react on edge network fluctuations