Material-integrated Intelligent Systems: A Review on State of the Art, Challenges and Trends

As a concept, material-integrated intelligent systems represent the vision of embedding not only sensors, but full sensor networks with smart sensors in technical materials, irrespective of their application being dominated by functional or structural properties. In this sense, the term full sensor networks encompasses the sensors, the associated signal and data processing, the data evaluation and information retrieval, provisions for communication within the network and beyond it, and an energy supply system. The concept as such can be applied to any type or class of host material, ranging from organic materials to composites, metals and ceramics. The result are materials that are, in a manner of speaking, able to “feel” in the broader sense associated with this term. Applications which would profit from such materials are diverse and range from structural health monitoring and control to fly by feel, robotics, human machine interaction to new types of user interfaces. Similarly, the fields of use differ widely from aerospace and other transport applications via advanced manufacturing systems to consumer products. Of specific interest for economic reasons are semi-finished materials that can be processed into several different products.

Needless to say, systems integrated into rather than externally attached to a host material or structure face several unique challenges, among them the need for

• reliability and fault tolerance
• autonomy in terms of energy supply and information processing
• mechanical and thermal stability sufficient to survive production
• mechanical and thermal stability sufficient to survive service life
• compatibility of mechanical and thermal properties with the host material
• scalability regarding network size on hard- and software level
• adaptability w.r.t. changes in environment and inner state

The present works discusses current approaches towards realizing material-integrated intelligent systems. In doing so, addressing the conceptual level is just one side of our work; besides, we attempt to provide a matrix that matches the challenges listed above with technological approaches that show the necessary potential for providing solutions. In this, the focus is clearly not limited to a hardware perspective, but includes software-based methods, too, e. g. in terms of guaranteeing reliability and fault tolerance in data evaluation and communication, or in making best use of available energetic resources, to name but a few examples: Material-embedded sensor networks must operate under low-resource, low-energy, and technical failure constraints, requiring new concepts in information processing.

Based on this analysis of fundamental technologies and already-realised concepts, we identify knowledge gaps that currently still hamper the broader implementation of material-integrated intelligent systems and derive suggestions for future research paths from it.

A special section is dedicated to the advent of additive manufacturing techniques adapted to facilitate sensor integration: The present growth in this field is expected to extend into the field of sensor-integrated materials and structures. First approaches in this direction will be discussed in the present work.