Sounce: AI-driven SaaS Solution For Quality Assessments Based on Acoustics
Sounce is now part of MHP: Sounce | MHP — A Porsche Company
Sound provides essential information about our environment, affects how we engage with each other, and — maybe surprisingly — tells us a lot about the products and technology we’re using. In fact, sound is one of the most original indicators for the functionality and quality of mechanic systems.
Sophie Schwandt, Solution Owner of Sounce, and Simon Weiß, Product Owner of Sounce, explain how artificial intelligence (AI) differentiates good sound from unwanted noise and how it takes the strain off engineers; for example in the automotive industry. Thanks to this new technology and its ability to learn, the power of sound can be leveraged to a new extension.
At Porsche Digital, we have been working relentlessly to revolutionize failure detection through sound
The control and elimination of unwanted sound is an important part of quality assurance. However, the design of effective testing systems to identify the great variety of potential noises is laborious, difficult and complex.
With the increasing complexity of the underlying mechanical systems, engineers need effective and time-saving tools to identify anomalies, defects and their sources. To that end, Porsche Digital has developed an AI system called Sounce, which precisely detects unwanted sounds and supports its root cause analysis through a deep learning approach.
Meet Sounce, the AI-powered sound detector
Sounce enables automatic detection of unwanted noise in real-time. It has been mainly designed for production and development processes: exemplary use cases are component endurance runs or end-of-line test benches for drive systems, closing systems or imbalance testing. We developed the so-called Software-as-a-Service (SaaS) solution together with our colleagues from the development department of Porsche AG. Sounce is an AI system that automatically detects noise and acoustical properties and helps engineers make sure that parts and products sound the way they should: nice and pleasant.
The challenge: noise analysis is a subjective and laborious process
Why do we need an AI to detect sound? Whether in quality assurance or in component qualification, sound and noises provide essential information about product and process quality.
However, detecting and analyzing noise and its sources can be complex and challenging. Therefore, it is sometimes omitted as a source of information. In other cases, it is the work of highly specialized engineers. However sound changes and if the monitoring system does not detect that change, defects can be overseen, and quality suffers. With deep learning, the system learns to adapt and offers an intelligent long-term perspective to quality assurance. Besides its transferability, the reduced effort of the setup is also an advantage of deep learning-based noise detection.
Our solution: AI-powered automatic failure detection
Based on a deep learning approach, Sounce reliably detects failures and unwanted sound. The results are documented, visualized and summarized in detail in a web application. Besides the classic test bench monitoring, the web application allows novel deep learning analysis for an improved root cause analysis.
There are five steps to its AI-based noise detection:
1. Listen & record: The test bench or station is equipped with minimally invasive sensor technology. The data acquisition is started. This process is done in a minimum of time to quickly come to the interesting part: the AI model training.
2. Evaluate: The engineer uses the software to document relevant quality criteria of the noise detection and thus creates the basis for the AI model training.
3. Train: Based on the available data a deep learning algorithm is trained and provided in the cloud.
4. Monitor & Detect: The test bench is continuously monitored, and noise anomalies are detected automatically in real-time. The noises can be visualized, evaluated, and compared.
5. Verify: Through easy interaction with the web application, the engineer provides feedback on the accuracy of the noise detection and optimizes the algorithm in the long term.
Good sound is good business
With Sounce, we want to improve the development and production of components in the automotive industry and beyond. It is an AI project that we have implemented as productive software and, needless to say, we are very excited about it. Our flexible Software-as-a-Service solution comes with a number of benefits, including objective noise evaluation, 24/7 monitoring (even in single-shift operation), remote test bench control, and seamless documentation of detected sounds.
Sophie Schwandt works as Solution Owner for Sounce at Porsche Digital
Simon Weiß works as Product Owner for Sounce at Porsche Digital
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