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10 ST/Industrial Sensing Solutions IMP34DT05 Omnidirectional MEMS Microphone • AOP = 122.5dBSPL and 64dB signal-to-noise ratio • Omnidirectional and with –26dBFS ±3dB sensitivity • top-port, SMD-compliant, EMI-shielded package, and is guaranteed to operate over an extended temperature range from -40°C to +85°C LEARN MOREu MP34DT06J MEMS Microphone • AOP = 122.5dBSPL with 64dB signal-to- noise ratio • Omnidirectional with –26dBFS ± 1dB sensitivity • PDM output, Top-port design, SMD- compliant, and EMI-shielded LEARN MOREu MEMS sensors have already found numerous applica- tions in consumer products, automotive, healthcare, and medical devices. However, the demands of these sensors to monitor industrial equipment and machines, perishable goods, leased goods, asset locations, structural health monitoring of bridges, buildings, shock detection, and ship- ping and transportation have gained a lot of attraction in recent years. Applications such as anti-tampering have become standard. Anti-tampering is critical in determining if there has been any unauthorized or inappropriate use of a machine, a tool, or a device. It requires only a cost-effec- tive accelerometer. MEMS technology has become an essential building blocks of the productive industry. It is industrial sensors that are making them a reality. Sensors provide a massive volume of data that can be used to develop a model that can then predict the time to failure of a machine. The key message here is that a successful implementation of a predictive maintenance model is to utilize the proper sensors to determine machine conditions. In other words, we first need to understand the potential failure modes of a machine and the warning signs associated with these modes to be able to select the right sensors, To summarize our discussion, PdM is the ability to foresee issues and proactively plan rather than react to main- tenance needs. According to the data in the industry, predictive maintenance reduces the maintenance costs about 30% and helps cut the production line downtime caused by equipment breakdowns up to 70%.