Holonic Control for Manufacturing Systems: Functional Design of a Manufacturing Robot Cell

Heikkilä, Tapio; Järviluoma, Markku; Juntunen, Timo

doi:10.3233/ica-1997-4305

Cited by 29 publications

(11 citation statements)

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“…Markus et al (1996) proposed a market model to solve dynamic order processing and scheduling problems, such as conflicts between local scheduling agents, resolved by negotiation simple terms of tasks, due dates and prices. Heikkilä et al (1997) proposed a holonic approach for manufacturing scheduling and control in a manufacturing cell. Sugimura et al (1996) modelled the manufacturing operations using an object-oriented approach and propose a real-time scheduling mechanism for assembly lines.…”

Section: Architectures and Approachesmentioning

confidence: 99%

Agent-based distributed manufacturing control: A state-of-the-art survey

Leitão

2009

Engineering Applications of Artificial Intelligence

700

349

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a b s t r a c tManufacturing has faced significant changes during the last years, namely the move from a local economy towards a global and competitive economy, with markets demanding for highly customized products of high quality at lower costs, and with short life cycles. In this environment, manufacturing enterprises, to remain competitive, must respond closely to customer demands by improving their flexibility and agility, while maintaining their productivity and quality. Dynamic response to emergence is becoming a key issue in manufacturing field because traditional manufacturing control systems are built upon rigid control architectures, which cannot respond efficiently and effectively to dynamic change. In these circumstances, the current challenge is to develop manufacturing control systems that exhibit intelligence, robustness and adaptation to the environment changes and disturbances. The introduction of multi-agent systems and holonic manufacturing systems paradigms addresses these requirements, bringing the advantages of modularity, decentralization, autonomy, scalability and reusability. This paper surveys the literature in manufacturing control systems using distributed artificial intelligence techniques, namely multi-agent systems and holonic manufacturing systems principles. The paper also discusses the reasons for the weak adoption of these approaches by industry and points out the challenges and research opportunities for the future.

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Section: Architectures and Approachesmentioning

confidence: 99%

Agent-based distributed manufacturing control: A state-of-the-art survey

Leitão

2009

Engineering Applications of Artificial Intelligence

700

349

View full text Add to dashboard Cite

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“…These related streams of research stems from the work on multi-agent control and holonic manufacturing systems started in the 1990s [25,57,6,38]. …”

Section: Product-centric Controlmentioning

confidence: 99%

Effects of combining product-centric control and direct digital manufacturing: The case of preparing customized hose assembly kits

Lyly-Yrjänäinen

Holmström

Johansson

et al. 2016

Computers in Industry

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“…Rabelo and Camarinha-Matos [13] propose a multi-agent-based dynamic scheduling, supported by negotiation techniques and the dynamic formation of consortia of manufacturing resources. Heikkila¨et al [14] propose a holonic approach for manufacturing scheduling and control in a manufacturing cell.…”

Section: Article In Pressmentioning

confidence: 99%

A holonic approach to dynamic manufacturing scheduling

Leitão

Restivo

2008

Robotics and Computer-Integrated Manufacturing

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Manufacturing scheduling is a complex combinatorial problem, particularly in distributed and dynamic environments. This paper presents a holonic approach to manufacturing scheduling, where the scheduling functions are distributed by several entities, combining their calculation power and local optimization capability. In this scheduling and control approach, the objective is to achieve fast and dynamic re-scheduling using a scheduling mechanism that evolves dynamically to combine centralized and distributed strategies, improving its responsiveness to emergence, instead of the complex and optimized scheduling algorithms found in traditional approaches. r

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Holonic Control for Manufacturing Systems: Functional Design of a Manufacturing Robot Cell

Cited by 29 publications

References 0 publications

Agent-based distributed manufacturing control: A state-of-the-art survey

Agent-based distributed manufacturing control: A state-of-the-art survey

Effects of combining product-centric control and direct digital manufacturing: The case of preparing customized hose assembly kits

A holonic approach to dynamic manufacturing scheduling

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