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Enabling distributed manufacturing resources through SOA

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The Service Oriented Architecture (SOA) is quite established in enterprise environments as a pattern for software integration. However, traditional industrial architecture based on a vertical hierarchy is still used in… Click to show full abstract

The Service Oriented Architecture (SOA) is quite established in enterprise environments as a pattern for software integration. However, traditional industrial architecture based on a vertical hierarchy is still used in old manufacturing organizations, making it difficult to reach the new requirements in industrial automation. There are works related with the use of SOA WS-* stack based frameworks, but this paradigm is not optimal due to the overhead in communication protocols. From this point of view, we propose a lightweight SOA architectural model based on the use of RESTful style for design and modeling of industrial processes. The aim is to explore a low developed research area to improve interoperability and flexibility in certain demanding manufacturing scenarios while similar performance of current industrial control standard is achieved. Theoretical advantages are presented and experimentally evaluated. In the evaluation, a prototype of the lightweight RESTful Framework and several scenarios of industrial devices are presented and response times are measured using two different RESTful protocols: HTTP and CoAP. From the results obtained it can be concluded that the performance of SOA with REST in industrial environments is suitable for current needs. A lightweight SOA model for a manufacturing context is proposed.Unlike related works, our model presents high capabilities in interoperability and performance.The high interoperability and performance capacities have been got integrating different techniques and technologies.The response times from the implementation of the model come to terms with the needed times in a manufacturing context.

Keywords: distributed manufacturing; enabling distributed; manufacturing; manufacturing resources; performance; resources soa

Journal Title: Robotics and Computer-integrated Manufacturing
Year Published: 2017

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