Line-less Production System Using Self-Organization: A Case Study for BMS

Ueda, Kanji; Hatono, Itsuo; Fujii, Nobutada; Vaario, Jari

doi:10.1016/s0007-8506(07)62130-1

Cited by 43 publications

(12 citation statements)

References 5 publications

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“…The main focus of this concept is to deal autonomously with dynamic and unpredictable changes in internal and external production environments by changing a system's configuration. In order to implement the concept of a BMS, methods of evolutionary computation, self-organization, and reinforcement learning were developed [17], [18], [20].…”

Section: B Evolution Of Planning Systems 1) Biological Manufacturingmentioning

confidence: 99%

Artificial Cognition in Production Systems

Bannat¹,

Bautze²,

Beetz³

et al. 2011

IEEE Trans. Automat. Sci. Eng.

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Abstract-Today's manufacturing and assembly systems have to be flexible to adapt quickly to an increasing number and variety of products, and changing market volumes. To manage these dynamics, several production concepts (e.g., flexible, reconfigurable, changeable or autonomous manufacturing and assembly systems) were proposed and partly realized in the past years. This paper presents the general principles of autonomy and the proposed concepts, methods and technologies to realize cognitive planning, cognitive control and cognitive operation of production systems. Starting with an introduction on the historical context of different paradigms of production (e.g., evolution of production and planning systems), different approaches for the design, planning, and operation of production systems are lined out and future trends towards fully autonomous components of an production system as well as autonomous parts and products are discussed. In flexible production systems with manual and automatic assembly tasks, human-robot cooperation is an opportunity for an ergonomic and economic manufacturing system especially for low lot sizes. The state-of-the-art and a cognitive approach in this area are outlined. Furthermore, introducing self-optimizing and self-learning control systems is a crucial factor for cognitive systems. This principles are demonstrated by a quality assurance and process control in laser welding that is used to perform improved quality monitoring. Finally, as the integration of human workers into the workflow of a production system is of the highest priority for an efficient production, worker guidance systems for manual assembly with environmentally-and situationally dependent triggered paths on state-based graphs are described in this paper.Note to Practitioners-Today's manufacturing enterprises have to face a number of challenges in a turbulent environment that originates amongst other from saturated markets, unprecedented and abrupt changes in market demands, an ever increasing number of product variants and smaller lot sizes. A recent research trend in Germany is the so called Cognitive Factory, where artificial cognitive capabilities are introduced to the control of production systems. The applications range from production planning and control, human-robot-cooperation, automatic robot programming to intuitive worker guidance systems.The concept of fully automated production systems is no longer a viable vision, as it has been shown, that the conventional automa- tion is not able to deal with the ever-rising complexity of modern production systems. Especially, a high reactivity, agility and adaptivity that is required by modern production systems, can only be reached by human operators with their immense cognitive capabilities, which enable them to react to unpredictable situations, to plan their further actions, to learn and to gain experience and to communicate with others. Thus, new concepts are required, that apply these cognitive principles to the planning processes and control systems of pr...

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Section: B Evolution Of Planning Systems 1) Biological Manufacturingmentioning

confidence: 99%

Artificial Cognition in Production Systems

Bannat¹,

Bautze²,

Beetz³

et al. 2011

IEEE Trans. Automat. Sci. Eng.

View full text Add to dashboard Cite

show abstract

“…Typically, members of the systems are individually able to achieve simple tasks, but their interactions lead to the emergence of complex collective behavior [28] [52]. In self-organizing systems, agents also communicate with each other indirectly: they use stigmergy (following ant communities) [45] [47] [53] or attraction-repulsion fields [54] [55]. Though, currently there is no generic coordination method that could be applied in engineering self-organizing systems [1].…”

Section: Organizationmentioning

confidence: 99%

Agent-Based Systems for Manufacturing

2006

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The emerging paradigm of agent-based computation has revolutionized the building of intelligent and decentralized systems. The new technologies met well the requirements in all domains of manufacturing where problems of uncertainty and temporal dynamics, information sharing and distributed operation, or coordination and cooperation of autonomous entities had to be tackled. In the paper software agents and multi-agent systems are introduced and through a comprehensive survey, their potential manufacturing applications are outlined. Special emphasis is laid on methodological issues and deployed industrial systems. After discussing open issues and strategic research directions, we conclude that the evolution of agent technologies and manufacturing will probably proceed hand in hand. The former can receive real challenges from the latter, which, in turn, will have more and more benefits in applying agent technologies, presumably together with well-established or emerging approaches of other disciplines.

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“…In this system, all production elements can move freely on the production floor using self-organization in order to adapt to fluctuations such as the diversity of product demands and the malfunction of machines. The effectiveness and feasibility of this system is demonstrated by computer simulations and by a prototypical mini-factory consisting of small autonomous robots [100], [101], [102]. Simulation results demonstrated that the proposed model can achieve global objectives such as "maximise the throughput" and "minimise the due date deviation".…”

Section: Layout Designmentioning

confidence: 97%

Autonomous Processes in Assembly Systems

2007

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Today's assembly systems have to be flexible to adapt quickly to an increasing number and variety of products and changing demand volume. To manage these dynamics, flexible, reconfigurable, and autonomous assembly systems were proposed and partly realised in the last two decades. The flexibility and adaptability is realised by clustering the assembly system into subsystems and modules which get a certain degree of autonomy and control themselves in a decentralised way. This keynote paper will present the general principles of autonomy and the proposed concepts, methods and technologies to realise autonomous processes in assembly systems. Different approaches for design and autonomous operation of assembly will be explained and future trends towards fully autonomous components of an assembly system as well as autonomous parts and products will be discussed.

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Line-less Production System Using Self-Organization: A Case Study for BMS

Cited by 43 publications

References 5 publications

Artificial Cognition in Production Systems

Artificial Cognition in Production Systems

Agent-Based Systems for Manufacturing

Autonomous Processes in Assembly Systems

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