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Prognostics and Health Management (PHM) refers to using robust sensing, monitoring, and control to detect, assess, and track system health degradation and failure modes, allowing for enhanced management and operational decisions. The need for PHM within a manufacturing facility has increased due to a variety of reasons, such as the increasing complexity of manufacturing equipment. A lack of readiness for digital implementations is linked to failure. The literature highlights certain barriers and enablers that can signal whether a technology implementation will be successful, such as management and maintenance employees’ desire to change the existing process, an understanding and willingness to take risks with technology, and having employees with the right competencies and motivations. This thesis identifies barriers and enablers related a successful PHM implementation and develops an assessment tool to identify a company’s readiness level as well as recommendations for increasing the probability of success.

This work explores the use of a commodity ultra-wideband (UWB) radar based device to detect breathing rate for health monitoring applications. Health monitoring devices observe physiological signals to detect medical conditions. We focus on capturing the small mechanical movements caused by breathing. This is traditionally done via a strain gauge worn around the chest or stomach, but these systems limit user movement. Contactless systems provide a unique design that allows free user movement by eliminating all direct contact with the user. Additionally, these systems have the potential to support full health monitoring in a Smart Built Environment (SBE). In this work, a comparative evaluation is performed on a commodity UWB radar based device, the Walabot, to determine the accuracy and possible health monitoring applications. Based on results from a systematic review, six research challenges were identified: (1) high cost, functional limitations based on the user's (2) location, (3) orientation, and (4) movement, (5) dependency on system hardware placement, and (6) vulnerabilities in signal processing methods. A comparative evaluation was designed to test the Walabot against a medical grade wearable system in the context of these research challenges. The data was processed using two breathing rate derivation techniques: Fast Fourier Transformation (FFT) and Peak Detection. Results suggest great potential for the Walabot coupled with the FFT technique. However, the system requires further testing to address all of the research challenges. Overall, this work provides important steps toward using the Walabot in health monitoring applications. / Master of Science / The goal of research in the field of health monitoring is to gather medical information about a user by constantly collecting physiological signals emitted by their body. Four physiological signals are deemed the "vital signs" because they provide information about the overall health of the patient. These vital signs are heart rate, breathing rate, temperature and blood pressure. Breathing rate is an important vital sign that, when monitored closely, can indicate the oncoming of dangerous health conditions and events. The act of breathing causes the chest to expand and contract. This movement can be captured by placing a strain gauge around a user's chest and analyzing fluctuation in strain readings. However, this is not practical for health monitoring applications because this system is uncomfortable to wear and the accuracy of the system is heavily dependent on the user's ability to wear the chest band constantly and correctly. Capturing this signal without any direct user contact would eliminate the user's discomfort and provide better reliability. This can be done by several methods, but the focus of this work is on systems that capture chest movements using ultra-wideband (UWB) radar. In this work, a specific UWB radar based device, called the Walabot, is tested against a standard strain gauge system to determine if it has health monitoring applications. Other radar based devices that aim to detect breathing rate are limited by their high cost and inaccuracies in signal processing techniques. The functionality of the devices are also dependent on the user's location and body orientation relative to the system, any user movement and the placement of the system itself. The study in this work was designed to determine the Walabot accuracy when the data is processed by two common breathing rate derivation methods. Results showed that the Walabot is cost effective and flexible in terms of user location and system placement. Overall, this work demonstrates the potential of the Walabot as a breathing rate monitor.

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