Self-Aware Smart Products: Systematic Literature Review, Conceptual Design and Prototype Implementation

Filho, None Marcelo; Liao, Yongxin; Loures, Eduardo Rocha; Canciglieri, Osíris

doi:10.1016/j.promfg.2017.07.278

Cited by 32 publications

(12 citation statements)

References 48 publications

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“…There is evidence in the analyzed examples that smartness has to replace complexity first in the first generation CPSs. It is not realistic to check all options and combinations in a complex CPS, and to consider all circumstances because of disturbances in environment (Filho, 2017). The context aware system with a certain level of intelligence can adapt to new circumstances much better than a deterministic hierarchical system.…”

Section: Discussionmentioning

confidence: 99%

From Validation of Medical Devices towards Validation of Adaptive Cyber-Physical Systems

Tavčar

Duhovnik

Horváth

2020

JID

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Conventionally, designing of a technical system is completed in the product development phase in terms of all details and aspects. This can be done if the expected behavior and the conditions of operation are known in advance and can be validated before the product is launched on the market. Validation is typically based on a predictive analysis or simulation of the designed operation. However, this contradicts with the case of smart systems, such as smart cyber-physical systems (CPSs), which self-manage their operation or at least a part of it. Being able to adapt at run-time and evolve over time, smart CPSs cannot be validated using conventional deterministic approaches. This is especially true for smart CPSs used as instrumentation in the medical field. This gave the stimulation of our background research, the results of which are concisely summarized and critically concluded in this paper. The literature has been found fairly narrow in terms of novel validation approaches for self-managing smart systems. The main finding is that the tasks of operational and behavioral validation should be shared among the system designers and the designed systems. Designers need prognostic approaches, while systems need to construct validation plans and execute them at run-time. This needs validation-specific functionalities and context dependent mechanisms such as run-time validation frameworks or meta-models, objective-sensitive self-monitoring mechanisms, self-constraining and self-supporting mechanisms, and other enablers. Extensive foundational research and system prototype testing are deemed to be indispensable. To make the first small step in this direction, this paper proposes a concept for validation of smart medical CPSs. This relies on the following hypothesis: If a system has freedom for self-adaptation, then it should also be equipped with selfcontrol mechanism, meta-knowledge and a supervisory controller. It all together enables a purpose-and context dependent semantic reasoning about the operational and behavioral objectives. The paper suggests a number of topics for future research towards a run-time validation engine.

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Section: Discussionmentioning

confidence: 99%

From Validation of Medical Devices towards Validation of Adaptive Cyber-Physical Systems

Tavčar

Duhovnik

Horváth

2020

JID

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“…Kassner et al believe that the social factory is to connect people, machines, and data in the production environment through corporate social networks and use ChatBots to achieve human-machine interaction and collaboration [37]. Leng [42]. In addition, many scholars use swarm intelligence [43] and artificial multi-agent system (MAS) [44] to enable autonomous production interaction.…”

Section: Autonomous Collaboration In Manufacturingmentioning

confidence: 99%

Social Production System: A Three-Layer Smart Framework for Implementing Autonomous Human-Machine Collaborations in a Shop Floor

2021

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The continuous fast-changing of production requirements and the development of advanced information technology have promoted the development of the production system in a more knowledgeintensive, resources-decentralized, and autonomous collaborative manner. In order to provide guidelines for the smart transformation of the production shop floor, this paper proposes a smart production system with a three-layer framework defined as the social production system (Social-PS) by integrating cyber-physical system (CPS), knowledge graph technology, and production-event driven model. The concept of smart resources (include smart operator, smart machine, smart workpiece, and smart gateway), social sensor, the unified information model is clarified to construct the physical carrier of Social-PS. The unified knowledge repository's overall construction method based on the knowledge graph is elaborated to provide taskresource-associated heterogeneous production data sharing and management for human-machine collaboration. Subsequently, to support the production dynamic monitoring and interaction, a productionevent and active knowledge indexing model is proposed. Furthermore, to validate the proposed Social-PS framework, a software and hardware integrated prototype system is implemented to demonstrate the knowledge-driven human-machine collaboration of the production process, which provides a basis for realizing smart and autonomous production collaboration.

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“…There are several initiatives that accommodate CPS development, including the "Advanced Manufacturing Partnership 2.0 (AMP, 2014)" and "Industrial Internet (IIC, 2014)" in the USA, "Industry 4.0" [9] in Germany, "Factories of the Future" in the EU, the "Made in China 2025" strategy alongside "Internet Plus" in China, and several others [11]. Industry 4.0 is focused on creating smart products, procedures, and processes [12], [13]. By connecting people, things, and data, new ways of organizing and conducting industrial processes emerge.…”

Section: B Smart Cpss and Industry 40mentioning

confidence: 99%

“…Subagdja and Tan [84] presented a framework for developing an application based on smart autonomous components that collaborate with the developer or user to realize the entire system. Filho et al [12] presented importance and criteria for a self-aware smart product in the context of smart 4.0 production environment.…”

Section: E Building Blocks Level (Complexity and Self-awareness)mentioning

confidence: 99%

A Review of the Principles of Designing Smart Cyber-Physical Systems for Run-Time Adaptation: Learned Lessons and Open Issues

Tavčar

Horváth

2019

IEEE Trans. Syst. Man Cybern, Syst.

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Smart cyber-physical systems (S-CPSs) are complex engineered systems empowered by cyber-physical computing and equipped with the capability of reasoning, learning, adapting, and evolving. As an outcome of data-driven dynamic computing, reasoning capabilities, and the run-time obtained own knowledge, nonlinear and emergent behavior of S-CPSs whilst in operation is an open issue, not experienced in the case of conventional technical systems. This paper analyzes the technical issues of run-time operation and emergent behavior of S-CPSs, reviews the current understanding and state of advancement in designing S-CPSs for run-time, explores the paradox, and issues of designing for runtime adaptation, and synthesizes some general principles that can be taken into consideration when addressing the challenges, first of all, in the context of advanced manufacturing systems. This paper introduces four levels of CPSs according to reasoning capabilities and adaptation freedom of systems, and recognizes the paradox that a system with a higher level of freedom requires a higher level of self-control and resource management according to the overall objective of operation. Specific and common design principles are presented and critically assessed for each advancement level of CPSs. The principles synthesized by the authors provide only a partial fulfillment of the generic need. The planned future research addresses these issues and proposes (largely implementation and application independent) genuine principles for system developers.

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Self-Aware Smart Products: Systematic Literature Review, Conceptual Design and Prototype Implementation

Cited by 32 publications

References 48 publications

From Validation of Medical Devices towards Validation of Adaptive Cyber-Physical Systems

From Validation of Medical Devices towards Validation of Adaptive Cyber-Physical Systems

Social Production System: A Three-Layer Smart Framework for Implementing Autonomous Human-Machine Collaborations in a Shop Floor

A Review of the Principles of Designing Smart Cyber-Physical Systems for Run-Time Adaptation: Learned Lessons and Open Issues

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