Evolvable assembly systems: coping with variations through evolution

Semere, Daniel; Onori, Mauro; Maffei, Antonio; Adamietz, R.

doi:10.1108/01445150810863707

Cited by 24 publications

(13 citation statements)

References 5 publications

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“…1b. Each product belongs to a certain product class (Semere et al 2008), where a production process means a coherent suite of assembly operations which lead to the finished product by assembling a set of parts. Production processes, the product design and the assembly system are intimately linked.…”

Section: Evolvable and Self-organising Assembly Systemsmentioning

confidence: 99%

Ambient intelligence in self-organising assembly systems using the chemical reaction model

Frei

Serugendo

Şerbănuţă

2010

J Ambient Intell Human Comput

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This article discusses self-organising assembly systems (SOAS), a type of assembly systems that (1) participate in their own design by spontaneously organising themselves in response to the arrival of a product order and (2) manage themselves during production. SOAS address the industry's need for agile manufacturing systems to be highly responsive to market dynamics. Manufacturing systems need to be easily and rapidly changeable, but system re-engineering/reconfiguration and especially their (re-)programming are manual, work-intensive and errorprone procedures. With SOAS, we try to facilitate this by giving the systems gradually more self-* capabilities. SOAS eases the work of the SOAS designer and engineer when designing such as system for a specific product, and supports the work of the SOAS operator when supervising the system during production. SOAS represent an application domain of ambient intelligence and humanised computing which is not frequently considered, but therefore none the less important. This article explains how an SOAS produces its own design as the result of a self-organising process following the Chemical Abstract Machine (CHAM) paradigm: industrial robots self-assemble according to specific chemical rules in response to a product order. This paper reports on SOAS in general, the specification of the chemical reactions and their simulation in Maude.

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Section: Evolvable and Self-organising Assembly Systemsmentioning

confidence: 99%

Ambient intelligence in self-organising assembly systems using the chemical reaction model

Frei

Serugendo

Şerbănuţă

2010

J Ambient Intell Human Comput

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“…The basic ideas behind EPS are: the wish to run multi-product lines; to re-use the equipment and modules when building new lines or changing the existing line for new products; and to do it in short time, in order to quicker follow the market demands. The characteristics of EPS concept are the focus on process and production perspective during the system design together with objectives of optimised functionality, optimised orchestration, adaptability and robustness [4]. This means that one should not only focus on designing and building a manufacturing or assembly system for a product, but should also be able to reconfigure and re-use the parts of the system quickly and easily according to the new demands and changed conditions.…”

Section: Introductionmentioning

confidence: 98%

Evolvable Micro Production Systems: Specific needs and differences to macro

Hofmann

Bretthauer

Siltala

et al. 2011

2011 IEEE International Symposium on Assembly and Manufacturing (ISAM)

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There exist a need for more cost effective and adaptable production solutions for miniaturised products. One promising approach to meet the market demands bases on so called desktop factories. They inherently offer a sustainable and energy efficient solution for the assembly of meso-and microsized parts. The realisation of adaptable automation solutions based on desktop factories under the paradigm of Evolvable Production Systems leads to the question of downscaling the implementation following the EPS guidelines. This paper describes some of the requirements and boundary conditions which occur in that process. The obligation to have an in-depth knowledge and understanding of all aspects along the production process is shown.

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“…In order to support new paradigm, manufacturing systems are expected to be flexible, agile and reconfigurable. Several objectives s h o u l d b e a d d r e s s e d i n o r d e r t o r e a c h t h e w a n t e d qualities of manufacturing systems: adaptability, robustness, optimized functionality and orchestration [1], reusability, integrability, convertibility, interoperability, and scalability [2]. Knowledge-based approach (KA) was found efficient to address objectives of mass customization trend, since KA makes it possible · to express engineering knowledge to provide semantic descriptions for physical manufacturing environment [2];…”

Section: Introductionmentioning

confidence: 99%

Edwards-Venn Diagrams for knowledge representation and reasoning in industrial systems

Dvoryanchikova

Lobov

Capanji

et al. 2010

2010 IEEE 15th Conference on Emerging Technologies &Amp; Factory Automation (ETFA 2010)

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Edwards-Venn Diagrams (EVD) were introduced to facilitate knowledge representation and reasoning in connectionistic approach for modeling industrial systems. Semantic descriptions are seen helpful in solving the challenges of mass customization due to capability to capture knowledge interpretable both for humans and machines. However modern knowledge technologies could not provide required flexibility in expressing the semantics of dynamical nature of events and processes which are essential for industrial systems. This motivates further research for flexible yet formal tools for knowledge representation and reasoning. In order to provide flexible semantic descriptions to dynamic qualities of industrial systems, a connectionistic knowledge model -connectionistic concept grid (CCG) -was introduced, which was inspired by natural knowledge structure derived from connectionism approach to natural cognition. EVD were found useful to represent relations among different sets of concepts in CCG and to provide structural reasoning in the models.

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Evolvable assembly systems: coping with variations through evolution

Cited by 24 publications

References 5 publications

Ambient intelligence in self-organising assembly systems using the chemical reaction model

Ambient intelligence in self-organising assembly systems using the chemical reaction model

Evolvable Micro Production Systems: Specific needs and differences to macro

Edwards-Venn Diagrams for knowledge representation and reasoning in industrial systems

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