ABSTRACT
In this chapter, we consider the recent advances in acquiring real-time data from products in the field and project these into areas in need of further development for statistical analysis of reliability data. The nature of field reliability data is rapidly changing owing to advances in technology. Modern products are increasingly equipped with sensors and smart chips to collect and transmit real-time data on hundreds of variables such as system operating parameters, use rate, load, temperature, humidity, vibration, and other environmental variables referred to as system operating environmental (or SOE) data.
In this chapter, we explore some of the opportunities to use modern reliability data for proactive product servicing. Statistical analysis of SOE data can be used to prevent in-service failures, unplanned maintenance, and system failures that could cause serious loss of property or lives. Statistical methods also play an important part in proactive product servicing. This includes guidance in data acquisition and development of algorithms to detect potential anomalies and potential reliability issues.
