Hakan Akillioglu

Hakan Akillioglu

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Hakan Akillioglu

Royal Institute of Technology, Production Engineering Department, KTH Brinellvägen 68, 100 44, Stockholm, Sweden

Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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10 September 2016 in Journal of Intelligent Manufacturing
Verified
Journal Article
Open access
PDF file
JDJoão Dias-Ferreira
João Dias-Ferreira
Luis RibeiroLuis Ribeiro
Luis Ribeiro
HAHakan Akillioglu
Hakan Akillioglu
PNPedro Neves
Pedro Neves
MOMauro Onori
Mauro Onori
Biological collective systems have been an important source of inspiration for the design of production systems, due to their intrinsic characteristics. In this sense, several high level engineering design principles have been distilled and proposed on a wide number of reference system architectures for production systems. However, the application of bio-inspired concepts is often lost due to design and implementation choices or are simply used as heuristic approaches that solve specific hard optimization problems. This paper proposes a bio-inspired reference architecture for production systems, focused on highly dynamic environments, denominated BIO-inspired Self-Organising Architecture for Manufacturing (BIOSOARM). BIOSOARM aims to strictly adhere to bio-inspired principles. For this purpose, both shopfloor components and product parts are individualized and extended into the virtual environment as fully decoupled autonomous entities, where they interact and cooperate towards the emergence of a self-organising behaviour that leads to the emergence of the necessary production flows. BIOSOARM therefore introduces a fundamentally novel approach to production that decouples the system’s operation from eventual changes, uncertainty or even critical failures, while simultaneously ensures the performance levels and simplifies the deployment and reconfiguration procedures. BIOSOARM was tested into both flow-line and “job shop”-like scenarios to prove its applicability, robustness and performance, both under normal and highly dynamic conditions.

1 December 2016 in Computers & Industrial Engineering
Verified
Journal Article
Closed access
HAHakan Akillioglu
Hakan Akillioglu
JDJoao Dias-Ferreira
Joao Dias-Ferreira
MOMauro Onori
Mauro Onori