System diagnostics and prognostics: A review

Industry is a vital pillar of a country's economic development. In today's global economy, industries in developed countries face numerous challenges, such as, the continuous technological advancements, strict government regulations, higher labor cost as compared to less developed countries, to name a few. The industrial sector of developed countries must continue to innovate to survive and remain relevant in the everevolving global economy. Furthermore, they must find creative ways to reduce production cost, foster a creative working environment, insure staff has the most robust tools available, and maintain a good reputation by respecting government legislation. Most importantly, they must offset the higher labor costs by improving the production systems performances to insure not only the survival of the manufacturing site but also the survival of the nation [27]. Production systems performance has always been key performance indicator of the health of an enterprises. However, as of late, the evaluation of an enterprise's health has shifted from a one-criterion-evaluation to a multi-criteria-evaluation, that can extend to the products complete life cycle. The evaluation is not only a function of productivity but also of flexibility, cost, time, quality, security, social performance, environmental performances, etc.… At the corner stone of each of these criteria lies one common element known as maintenance. In fact, maintenance provides the possibility of exploiting enterprise resources in order to improve their performances by optimizing the utilization of human and material means. Maintenance is thus a strategic element of cooperation's competitiveness and ultimately its success. Hence, maintenance has seen a spectacular upswing in terms of investment and research. Since its conception, maintenance has not ceased to progress and improve due to the emergence of Information and Communication Technologies (ICT) as well as due to the requirements and exigency imposed by the worldwide economic context. Maintenance has become a true discipline with its own methodologies and concepts. Prognostic, an emerging discipline, is a key sub-process of proactive maintenance [55] for Maintaining systems in Operational Condition (MOC). The integration of a prognostic function in a proactive maintenance process allows a guaranteed proactive response to the numerous subsystems that make up a complex system, and prevents a functioning breakdown as well as expensive maintenance interventions. Let us take for example a ship making journeys for many weeks; it is better to change out equipment or to perform maintenance on all the equipment before making the journey, than to perform maintenance on the other side of the planet. In this example, it would be helpful to understand the remaining useful lifetime (RUL) of the piece equipment as this would help determine if the voyage could continue with the current equipment or is new equipment required. A maintenance strategy that includes a prognostic function of the equipment and the remaining useful lifetime (RUL) is known as Prognostics and Health Management (PHM). This maintenance strategy has quickly grown in populiarity and has led to the emergence of the "PHM society." In today's day and age, most systems are extremely complex and contain multiple subsystems involving numerous domains. For example if we consider a vehicle as system. This system contains electrical, chemical, and mechanical systems and within each system there are sub-systems that all work together to propel the vehicle. Such systems contain a large number of variables having complex relations; hence, we have called them complex systems. Unlike the diagnostic domain, which is heavily equipped with analytical tools, the domain of prognostic disposes few tools or very specific tools. Most of the domain publications present prognostic in the framework of an elementary system. The objective of diagnostic is to detect and to explain the occurrence of a system failure or breakdown whereas the objective of prognostic is to predict the future state of degradation of a system extrapolated from its current state. In the case of diagnostic, we walk backward in time, whereas in the case of prognostic, we walk forward in time, or in other words, we anticipate the future state. A prognostic consists to predict the future evolution of degradation by taking into consideration the factors that modify the degradation dynamics. These factors can be subdivided into two categories: the factors linked to the solicitation of the system and those linked to the environment in which the system evolves. Usually, The influence of these two components on degradation is not fully understood and thus and sometimes, they totally ignored. Nowadays, we rarely find publications that explicitly deal with this domain. This chapter is dedicated to the diagnostic and prognostic of dynamic systems. We present rapidly the evolution of maintenance in order to introduce the concept of intelligent maintenance and the role of Prognostics and Health Management during the system life cycle. It examines numerous the state of the art of prognostic approaches: model-based prognostic, databased prognostic, and experience-based prognostic. These state of the art techniques paves the way for the present work and future contribution to this field.