Cloudlet architecture for dashboard in cloud and ubiquitous manufacturing

The aim of this paper is to present a cloudlet architecture for dashboard in Cloud and Ubiquitous Manufacturing. In practice means that, with Cloud Computing adoption, Manufacturing requires management applications where ubiquity and effectiveness are enabled. If ubiquity and resources scalability, availability and capacity can be well supported by cloud, pragmatics instruments are required to support effectiveness. The architecture here presented shows the integration of enriched existing (cloud) services, as instances of resources, with layers of new services towards direct and synchronous communication between users. These Rich Internet Application (RIA) components, here named cloudlets, integration, follow dashboards organization patterns and will be supported by emergent web3.0 interaction technologies. In fact, the paper proposes a new Presentation Layer to be used in UMS and (that may be used) in any multi-layer cloud-based web application. (C) 2013 Authors. Published by Elsevier B. V.The authors wish to acknowledge the support of: 1) The national Foundation for Science and Technology - FCT (Fundacao para a Ciencia e a Tecnologia) scholarship, reference number SFRH/BD/49540/2009, 2) The Foundation for Science and Technology - FCT, Project PTDC/EME-GIN/102143/2008, 'Ubiquitous oriented embedded systems for globally distributed factories of manufacturing enterprises', 3) EUREKA, Project E! 4177-Pro-Factory UE

A Cloud-Based Architecture with embedded Pragmatics Renderer for Ubiquitous and Cloud Manufacturing

The paper presents a Cloud-based architecture for Ubiquitous and Cloud Manufacturing as a multilayer communicational architecture designated as the Communicational Architecture. It is characterised as (a) rich client interfaces (Rich Internet Application) with sufficient interaction to allow user agility and competence, (b) multimodal, for multiple client device classes support and (c) communicational to allow pragmatics, where human-to-human real interaction is completely supported. The main innovative part of this architecture is sustained by a semiotic framework organised on three main logical levels: (a) device level, which allows the user `to use' pragmatics with the system, (b) application level which results for a set of tools which allows users pragmatics-based interaction and (c) application server level that implements the Pragmatics renderer,a pragmatics supporting engine that supports all pragmatics services. The Pragmatics renderer works as a communication enabler, and consists of a set of integrated collaboration technology that makes the bridge between the user/devices and the `system'. A federated or community cloud is developed using a particular cloud REST ful Application Programming Interface that supports (cloud) services registration, composition and governance (pragmatics services behaves as SaaS in the cloud).The work is supported by the Portuguese National Funding Agency for science, research and technology (FCT), (1) Grant No. UID/CEC/00319/2013, and (2) `Ph.D. Scholarship Grant' reference SFRH/BD/85672/2012.info:eu-repo/semantics/publishedVersio

Machine Learning in Cyber-Physical Systems and manufacturing singularity – it does not mean total automation, human is still in the centre: Part II – In-CPS and a view from community on Industry 4.0 impact on society

In many discourses, popular as well as scientific, it is suggested that the "massive" use of Artificial Intelligence (AI), including Machine Learning (ML), and reaching the point of "singularity" through so-called Artificial General Intelligence (AGI), and Artificial Super-Intelligence (ASI), will completely exclude humans from decision making, resulting in total dominance of machines over human race. Speaking in terms of manufacturing systems, it would mean that the intelligence and total automation would be achieved (once the humans are excluded). The hypothesis presented in this paper is that there is a limit of AI/ML autonomy capacity, and more concretely, the ML algorithms will be not able to become totally autonomous and, consequently, the human role will be indispensable. In the context of the question, the authors of this paper introduce the notion of the manufacturing singularity and present an intelligent machine architecture towards the manufacturing singularity, arguing that the intelligent machine will always be human dependent. In addition, concerning the manufacturing, the human will remain in the centre of Cyber-Physical Systems (CPS) and in Industry 4.0. The methodology to support this argument is inductive, similarly to the methodology applied in a number of texts found in literature, and based on computational requirements of inductive inference based machine learning. The argumentation is supported by several experiments that demonstrate the role of human within the process of machine learning. Based on the exposed considerations, a generic architecture of intelligent CPS, with embedded ML functional modules in multiple learning loops, is proposed in order to evaluate way of use of ML functionality in the context of CPS. Similar to other papers found in literature, due to the (informal) inductive methodology applied, considering that this methodology does not provide an absolute proof in favour of, or against, the hypothesis defined, the paper represents a kind of position paper. The paper is divided into two parts. In the first part a review of argumentation from literature in favour of and against the thesis on the human role in future was presented, as well as the concept of the manufacturing singularity was introduced. Furthermore, an intelligent machine architecture towards the manufacturing singularity was proposed, arguing that the intelligent machine will be always human dependent and, concerning the manufacturing, the human will remain in the centre. The argumentation is based on the phenomenon related to computational machine learning paradigm, as intrinsic feature of the AI/ML1, through the inductive inference based ML algorithms, whose effectiveness is conditioned by the human participation. In the second part, an architecture of the Cyber-Physical (Production) Systems (CPPS) with multiple learning loops is presented, together with a set of experiments demonstrating the indispensable human role. Finally, a discussion of the problem from the manufacturing community point of view on future of human role in Industry 4.0 as the environment for advanced AI/ML applications is registered

What is a Cyber-Physical System: Definitions and Models Spectrum

Each time a relevant proposal occurs, existing perspectives, concepts or fundamentals are confronted by emergent ones. The Industry 4.0 and its promoted production control systems based on Cyber-Physical Systems (CPS), made splash new potentials for the binomial human and technology (equipments and its settings). Several authors explore the envisaged required more physical and digital connection to announce interesting transformative changes, where selfconfigure and adaptive machines sustain the application of corrective decisions. This paper exposes a spectrum of existing CPS definitions and models and contributes with the fundamentals for an effective intelligent CPS (I-CPS), where a double loop learning process, allows its supporting software algorithms to be changed or reprogrammed. Instead, not only selfconfigure machines but its configuring software, too

Dashboard services for pragmatics-based interoperability in cloud and ubiquitous manufacturing

The real Cloud and Ubiquitous Manufacturing systems require effectiveness and permanent availability of resources, their capacity and scalability. One of the most important problems for applications management over cloud based platforms, which are expected to support efficient scalability and resources coordination following SaaS implementation model, is their interoperability. Even application dashboards need to easily incorporate those new applications, their interoperability still remains a big problem to override. So, the possibility to expand these dashboards with efficiently integrated communicational cloud based services (cloudlets) represents a relevant added value as well as contributes to solving the interoperability problem. Following the architecture for integration of enriched existing cloud services, as instances of manufacturing resources, this paper: a) proposes a cloud based web platform to support dashboard integrating communicational services, and b) describe an experimentation to sustain the theory that the effective and efficient interoperability, especially in dynamic environments, could be achieved only with human intervention

Effective service dynamic packages for ubiquitous manufacturing system

This paper proposes a new integrated architecture for advanced manufacturing management with a Ubiquitous Management System (UMS) and a collection of adequate features to sustain it, where pragmatics on collaboration mechanisms prevails. The Market-of-Resources repository and its advanced brokering process will enable reliable interoperability, services dynamic packages and reconfiguration, as well as the (co-) management of production process, regardless information systems and using real-time collaboration mechanisms. This article contributes for building a logical model for UMS as well as an UML formalization for its supporting architectureThe authors wish to acknowledge the support of: 1) The national Foundation for Science and Technology - FCT (Fundação para a Ciência e a Tecnologia) scholarship, reference number SFRH/BD/49540/2009, 2) The Foundation for Science and Technology - FCT, Project PTDC/EME-GIN/102143/2008, 'Ubiquitous oriented embedded systems for globally distributed factories of manufacturing enterprises', 3) EUREKA, Project E! 4177-Pro-Factory UES