The growing demand for improved reactivity to market trends faces manufacturing systems with new changeability requirements under increasing complexity constraints. Sensors are the ears and eyes of systems controlling automated production processes. Additionally, they provide necessary information to monitoring and maintenance applications which are also forced to be adaptable to system evolution. Semantic technologies are key enabler to foster integration and interoperability of large-scale, heterogeneous data sources. In this paper, we discuss approaches to integrate semantic technology with the upcoming standard OPC-UA and present a solution to taps the full potential of both through semantic-based sensor discovery and automatic sensor data provisioning with OPC-UA.

Nowadays, RFID is used to identify a wide range of work pieces or individual products for tracking their movements during the product life cycle. For future purposes the idea of storing only a single ID must be extended to a “Digital Product Memory”. A Digital Product Memory provides a digital diary of the complete product life cycle and is embedded in the product itself. It records all relevant ambient parameters in digital form. Sensors note where and when an interaction with a product takes place. People can access these digital product diaries at any time. The autonomous behavior of the product memory makes it additionally possible to monitor and control the production and logistics of the product. In this paper we describe a flexible approach for product-driven manufacturing using a digital product memory to achieve minimum lot sizes and a reduced time to market.