A database-centric approach for the modeling, simulation and control of cyber-physical systems in the factory of the future.

Bonci, Andrea; Pirani, Massimiliano; Longhi, Sauro

doi:10.1016/j.ifacol.2016.07.608

Cited by 33 publications

(16 citation statements)

References 17 publications

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“…In this section, the performance improvement technique is introduced with an introductory example. For a more consistent and detailed introduction to the methodology and its historical developments, from the initial developments industrial automation field, reader may refer to Pirani (2016), , and Bonci (2018a). In the following, some recalls about the technique and a simple example are discussed within the context of management problems.…”

Section: Basics On the Performance Improvement Methodologymentioning

confidence: 99%

Holonic Management Tree Technique for Performance Improvement Over Self-Similar System Structures

Bonci¹,

Longhi²,

Pirani³

2019

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This paper presents the detailed definition of technique for the automation of the management of complex business systems, whether they are constituted of services and productions. The technique has been referred here for the first time as Holonic Management Tree (HMT) and has been consistently contextualized into undergoing research on technological frameworks for the management cybernetics, in which the concept of viable system represents a fundamental stance. HMT is based on the use of recursive formulas over self-similar holonic structures for the attainment of continuous performance improvement in a complex and continuously evolving process. The problem is associated to a recursive tree of self-similar structures of which in this paper we discuss the interpretation with respect to knowledge modeling domain. The basic expressions for the computation of the 2nd degree trees are provided and explained in detail by means of an example in lean management context. Moreover, this work presents and discusses the expressions that handle the implementation of the n-th degree case as a recurrent abstraction of the basic and simple 2nd degree computation.

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Section: Basics On the Performance Improvement Methodologymentioning

confidence: 99%

Holonic Management Tree Technique for Performance Improvement Over Self-Similar System Structures

Bonci¹,

Longhi²,

Pirani³

2019

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“…Specifically tailored to the problems of the shop floor, data integration is the approach proposed by Bonci et al [26] for database-centric cyber-physical production systems (CPPS). Their idea is to use lightweight database synchronization with a distributed replication on every CPS device.…”

Section: Related Workmentioning

confidence: 99%

Applying Semantics to Reduce the Time to Analytics within Complex Heterogeneous Infrastructures

et al. 2018

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In today’s age of modern information technology, large amounts of data are generated every second to enable subsequent data aggregation and analysis. However, the IT infrastructures that have been set up over the last few decades and which should now be used for this purpose are very heterogeneous and complex. As a result, tasks for analyzing data, such as collecting, searching, understanding and processing data, become very time-consuming. This makes it difficult to realize visions, such as the Internet of Production, which pursues the goal of guaranteeing the availability of real-time information at any time and place in an industrial setting. To reduce the time to analytics in such scenarios, we present a data ingestion, integration and processing approach consisting of a flexible and configurable data ingestion pipeline as well as a semantic data platform named ESKAPE. The ingestion pipeline provides an abstraction to all tasks related to data acquisition. The main goal is, therefore, the controllable access to data and meta information contained in machines and other systems on the shop floor. Additionally, it provides the possibility to forward the collected data to a configurable endpoint, such as a data lake. ESKAPE acts as one of those endpoints enabling semantic data integration and processing. By annotating data sets with semantic models originating from the Semantic Web, data analysts are able to understand, process and discover these data sets more efficiently. ESKAPE features a three-layered information storage architecture consisting of a data layer for storing integrated raw data sets, a layer containing user-defined semantic models to describe the contextual knowledge necessary to interpret the stored data and a top layer formed by a continuously evolving knowledge graph, combining semantic information from all present semantic models. Based on this storage system, ESKAPE enables the flexible annotation as well as efficient search and processing of data sources without losing the ability of analyzing and querying the underlying raw data with analytic tools. We present and discuss our approach and its benefits and limitations based on a real-world industrial use case.

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“…From another point of view, the implementation of CPS and industry paradigm 4.0 introduces a series of constraints that are needed to fully implement this potential capability. The main involved issues seem to concern the information role, its transfer, and the complexity management [5] as inevitable problems to be treated. Another important aspect is the reliability of data that are collected through sensor networks as well as their reuse [10] [11] [12].…”

Section: Application Of Cps For Environmental Sustainabilitymentioning

confidence: 99%

“…Therefore data are associated with database that are external to the physical CPS. The databases roles include both data storing for long-term strategies and active capabilities in supporting CPS to govern the production systems operations [5]. These stored data, which are updated by a different rate in comparison to physical flow data, requires also an intermediate step for respective association in order to be referred to the same activity (e.g.…”

Section: Fig 1 Requirements For Cps Use In the Lca Frameworkmentioning

confidence: 99%

The CPS and LCA Modelling: An Integrated Approach in the Environmental Sustainability Perspective

Ballarino

Brondi

Brusaferri

et al. 2017

Collaboration in a Data-Rich World

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A database-centric approach for the modeling, simulation and control of cyber-physical systems in the factory of the future.

Cited by 33 publications

References 17 publications

Holonic Management Tree Technique for Performance Improvement Over Self-Similar System Structures

Holonic Management Tree Technique for Performance Improvement Over Self-Similar System Structures

Applying Semantics to Reduce the Time to Analytics within Complex Heterogeneous Infrastructures

The CPS and LCA Modelling: An Integrated Approach in the Environmental Sustainability Perspective

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