The development of nanotechnologies, biotechnology, and the technologies of communication and information, pushed back the limits of information of the product, which forces to reformulate the problem of extraction of information on the health condition of the product over the life cycle. Thus, a product's performance should not be limited to the evaluation of macroscopic measurements, as the state of the components can now be evaluated, starting from intrinsic data at the level nanometric. Thus, it will be possible to characterize a product component by the information of DNA type (Deoxyribonucleic Acid) that will enable the following, for example, the degradations of involved materials. This prospect can help to reinforce the quality of the collected data to feed the information extraction models. Decision support requires data and information of high quantity at all levels in the product decomposition. This need led today the human society to becoming increasingly voracious to information on products or systems lifecycle. Data quality has forced improving the reliability of the data collection systems for product life cycle management. Unfortunately, there are not yet well-established models of the data collection process, enabling strengthening their effectiveness. On the other hand, the advances in information technologies and the increasing power of computer systems enable us to consider products and production systems with value-added support services. Thus, today, it is a challenge to design quite intelligent and self-healing products by using nanotechnologies and intelligent embedded information devices. This presentation will describe the product’s health condition information extraction approach for decision support in maintenance and risk assessment. A modeling approach of data and information collection processes, based on the product identification technologies and nanotechnology, will be presented with the associated data processing tools. It will also point out the emerging scientific problems, of which solutions will enable efficient information systems supporting the product lifecycle and health condition monitoring.