Model-based Development of Modular Complex Systems for Accomplishing System Integration for Industry 4.0

Suri, Kunal; Cuccuru, Arnaud; Cadavid, Juan; Gérard, Sébastien; Gaaloul, Walid; Tata, Samir

doi:10.5220/0006210504870495

Cited by 26 publications

(17 citation statements)

References 7 publications

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“…Yatay entegrasyon; şirketler arası entegrasyondur ve birçok şirket arasında yakın ve yüksek seviyeli bir işbirliğinin temelini oluşturmaktadır [22]. Dikey entegrasyon ağa bağlı bir üretim sistemi ile şirket içi entegrasyon, kurumsal planlama, üretim öncesi zamanlama veya yönetim gibi hiyerarşinin farklı seviyeleri arasında bilgi alışverişinin ve işbirliğinin temelini oluşturur [30]. Uçtan uca dijital entegrasyonun kapsamı ise ürün tasarımı, üretim, lojistik ve müşteri arasındaki boşlukları kapatarak kalıcı ve etkileşimli bir dijital modelin akışını sağlamaktadır [31].…”

Section: Endüstri̇ 40 (Industry 40)unclassified

Endüstri 4.0’ın Proje Yönetim Etmenlerine Etkisi

Taner

Biçer

2021

Politeknik Dergisi

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Yönetim, modern bilimsel anlayışına ulaşana kadar pek çok aşamadan geçmiş ve her zaman pratikte var olmuştur. Dünya nüfusunun artması ve kentleşmeye bağlı olarak çevresel, sosyal ve ekonomik faaliyetler için endüstrileşmeye duyulan ihtiyaçlar artmıştır. Gelişen teknoloji sayesinde endüstriyel ürünlerin daha hızlı ve esnek üretilebilmesi yönündeki beklentilerin iyi bir yönetimle karşılanması; çevresel, sosyal ve ekonomik sorunların azalması için elzemdir. Yapı endüstrisindeki her projenin kendi özgün olmasından dolayı proje yönetiminin önemi gün geçtikçe artmıştır. Bu doğrultuda günümüzde birçok alanda çığır açan teknolojik uygulamalarla dolu bir çağı yansıtan Endüstri 4.0'ın proje yönetimine etkisi önemli bir araştırma konusudur. Bu çalışmada öncelikle Endüstri 4.0'ın beraberinde getirdiği dönüşümler hakkında literatür araştırması yapılmıştır. Sonrasında bu dönüşümlerin proje yönetim etmenleri üzerinde etkisinin ortaya koyulması için yönetim etmenleri açıklanmış ve endüstri 4.0'ın getirileri üzerine analiz gerçekleştirilmiştir. Endüstri 4.0 teknolojilerinin proje yönetim etmenlerinde kullanılması ile sorunlara gerçek zamanlı çözüm önerileri getirerek başarılı proje yönetiminin sağlanacağı öngörülmüştür. Elde edilen verilerin proje paydaşlarına yol gösterici olması ve alana katkı sağlaması amaçlanmaktadır.

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Section: Endüstri̇ 40 (Industry 40)unclassified

Endüstri 4.0’ın Proje Yönetim Etmenlerine Etkisi

Taner

Biçer

2021

Politeknik Dergisi

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“…This last issue is derived from the fact that complex system design involves several viewpoints from different technical domains, therefore several heterogeneous models developed by different teams. Model driven approaches are used in industry to interconnect these models and represent the consistency links between them (Zhao et al, 2017,Suri et al, 2017,Andrén et al, 2017. These approaches mainly aim to facilitate the final system realisation, but only few of them include the simulation in the design process (Paris et al, 2017).…”

Section: State Of the Artmentioning

confidence: 99%

A Model based Toolchain for the Cosimulation of Cyber-physical Systems with FMI

Oudart

Cantenot

Boulanger

et al. 2020

Proceedings of the 8th International Conference on Model-Driven Engineering and Software Development

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Smart Grids are cyber-physical systems that interface power grids with information and communication technologies in order to monitor them, automate decision making and balance production and consumption. Cosimulation with the Functional Mock-up Interface standard allows the exploration of the behavior of such complex systems by coordinating simulation units that correspond to the grid part, the communication network and the information system. However, FMI has limitations when it comes to cyber-physical system simulation, particularly because discrete-event signals exchanged by cyber components are not well supported. In addition, industrial projects involve several teams with different skills and methods that work in parallel to produce all the models required by the simulation, which increases the risk of inconsistency between models. This article presents a way to exchange discrete-event signals between FMI artifacts, which complies with the current 2.0 version of the standard. We developed a DSL and a model-based toolchain to generate the artifacts that are necessary to run the cosimulation of the whole system, and to detect potential inconsistencies between models. The approach is illustrated by the use case of an islanded grid implementing diesel and renewable sources, battery storage and intelligent control of the production.

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“…In industrial domain applications, Suri et al [24] proposed a model-based approach for complex systems development by separating the behavior model and execution logic of the system. Moreover, they used UML based languages to model system behavior and connected the behavior models to external physical API of CPS.…”

Section: Related Workmentioning

confidence: 99%

A Model-Based Combination Language for Scheduling Verification

Zhao

Apvrille

Mallet

2020

Communications in Computer and Information Science

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Cyber-Physical Systems (CPSs) are built upon discrete software and hardware components, as well as continuous physical components. Such heterogeneous systems involve numerous domains with competencies and expertise that go far beyond traditional software engineering: systems engineering. In this paper, we explore a model-based approach for systems engineering that advocates the composition of several heterogeneous artifacts (called views) into a sound and consistent system model. A model combination Language is proposed for this purpose. Thus, rather than trying to build the universal language able to capture all possible aspects of systems, the proposed language proposes to relate small subsets of languages in order to offer specific analysis capabilities while keeping a global consistency between all joined models. We demonstrate the interest of our approach through an industrial process based on Capella, which provides (among others) a large support for functional analysis from requirements to components deployment. Even though Capella is already quite expressive, it lacks support for schedulability analysis. AADL is also a language dedicated to system analysis. If it is backed with advanced schedulability tools, it lacks support for functional analysis. Thus, instead of proposing ways to add missing aspects in either Capella or AADL, we rather extract a relevant subset of both languages to build a view adequate for conducting schedulability analysis of Capella functional models. Finally, our combination language is generic enough to extract pertinent subsets of languages and combine them to build views for different experts. It also helps maintaining a global consistency between different modeling views.

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Model-based Development of Modular Complex Systems for Accomplishing System Integration for Industry 4.0

Cited by 26 publications

References 7 publications

Endüstri 4.0’ın Proje Yönetim Etmenlerine Etkisi

Endüstri 4.0’ın Proje Yönetim Etmenlerine Etkisi

A Model based Toolchain for the Cosimulation of Cyber-physical Systems with FMI

A Model-Based Combination Language for Scheduling Verification

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