In recent decades, it has become a significant tendency for industrial manufacturers to adopt decentralization as a new manufacturing paradigm. This enables more efficient operations and facilitates the shift from mass to customized production. At the same time, advances in data analytics give more insights into the production lines, thus improving its overall productivity. The primary objective of this paper is to apply a decentralized architecture to address new challenges in industrial analytics. The main contributions of this work are therefore two-fold: (1) an assessment of the microservices’ feasibility in industrial environments, and (2) a microservices-based architecture for industrial data analytics. Also, a prototype has been developed, analyzed, and evaluated, to provide further practical insights. Initial evaluation results of this prototype underpin the adoption of microservices in industrial analytics with less than 20ms end-to-end processing latency for predicting movement paths for 100 autonomous robots on a commodity hardware server. However, it also identifies several drawbacks of the approach, which is, among others, the complexity in structure, leading to higher resource consumption.
@cite_19 propose a simulation-based architecture for ) Cyber-Physical systems are systems with the seamless, real-time interaction between computing elements and physical assets using intelligent data management, analytics and computational capability @cite_7 . at shop-floor level, providing an environment for Digital Twins are representations of real-world assets (including the assets in designing building stage) created with the ability to collect and synthesize data from various sources including physical data, manufacturing data, operational data and insights from analytics software @cite_2 . along the whole plant life-cycle. The proposed platform implements a microservice IoT-Big Data architecture supporting the publication of multidisciplinary simulation models and managing streams of data coming from the shop-floor for real-digital synchronization. Microservices architecture is applied in their support infrastructure, in order to manage the DTs. In our proposal, we extend this work by employing microservices also for simulating physical assets to decentralize the whole system. Rather than storing all digital copies of physical assets in one place, building them as microservices allows more flexibility in deployment strategies. For each service, a best physical location to deploy could be determined based on various criteria. This is an important foundation to enable automated and QoS-aware deployment strategies.
@cite_19 @cite_7 @cite_2
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Abstract In recent years a considerable effort has been spent by research and industrial communities in the digitalization of production environments with the main objective of achieving a new automation paradigm, more flexible, responsive to changes, and safe. This paper presents the architecture, and discusses the benefits, of a distributed middleware prototype supporting a new generation of smart-factory-enabled applications with special attention paid to simulation tools. Devised within the scope of MAYA EU project, the proposed platform aims at being the first solution capable of empowering shop-floor Cyber-Physical-Systems (CPSs), providing an environment for their Digital Twin along the whole plant life-cycle. The platform implements a microservice IoT-Big Data architecture supporting the distributed publication of multidisciplinary simulation models, managing in an optimized way streams of data coming from the shop-floor for real-digital synchronization, ensuring security and confidentiality of sensible data. Abstract Recent advances in manufacturing industry has paved way for a systematical deployment of Cyber-Physical Systems (CPS), within which information from all related perspectives is closely monitored and synchronized between the physical factory floor and the cyber computational space. Moreover, by utilizing advanced information analytics, networked machines will be able to perform more efficiently, collaboratively and resiliently. Such trend is transforming manufacturing industry to the next generation, namely Industry 4.0. At this early development phase, there is an urgent need for a clear definition of CPS. In this paper, a unified 5-level architecture is proposed as a guideline for implementation of CPS.