Abstract
Today’s economy, driven by aggressive marketing campaigns, shows an appetite for new, on demand products and services. The life span of a given product type becomes in these conditions shorter and shorter. To remain competitive, manufacturing enterprises need to keep up with these dynamic market variations, by always adjusting the offer according to competition. On top of this, the poor economic conditions add additional pressure on optimization and efficiency in order to cut costs and maximize profit. Enterprises have understood that "time to market" becomes a decisive factor that separates successful enterprises from lagers. This time to market can be shortened only by increasing flexibility in the manufacturing process. The purpose of this paper is to present a framework for manufacturing integration, which matches plant floor solutions with business systems and suppliers. This solution focuses on achieving flexibility by enabling a low coupling design of the entire enterprise system through leveraging of Service Oriented Architecture (SOA) and Manufacturing Service Bus (MSB) as best practices. The paper presents the integration between an upper layer ESB-based business system with a distributed HMES system based on MSB, built using JADE multi agent platform, event triggered communication and dynamic business rules. The combination of ESB at business layer and MSB at HMES layer forms a solid yet agile architecture for loose coupled, standard based manufacturing systems. Experimental results show the distribution of messages transmitted through the ESB and MSB for a certain product batch size and number of resources, proving that two-layered bus architectures offer several advantages in structuring the information flow through the buses.
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Morariu, C., Morariu, O., Borangiu, T., Raileanu, S. (2013). Manufacturing Service Bus Integration Model for Highly Flexible and Scalable Manufacturing Systems. In: Borangiu, T., Thomas, A., Trentesaux, D. (eds) Service Orientation in Holonic and Multi Agent Manufacturing and Robotics. Studies in Computational Intelligence, vol 472. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35852-4_2
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DOI: https://doi.org/10.1007/978-3-642-35852-4_2
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