The New Frontier of Silence: How to Develop the Washing Machine of the Future

Marco Cugnetto, WHIRLPOOL

"The team combined LabVIEW Real-Time, FPGA, and CompactRIO to design and develop a whole system that helps the company quickly deliver the innovation to production and increases quality targets and reduces cost."

- Marco Cugnetto, WHIRLPOOL

The Challenge:

Creating the most silent washing machine so customers can use it over convenient time bands for ecological and economical advantages. Among technologies for noise reduction, optimal unbalance management has been identified as one of the key solution to achieve this goal. Improving high-speed unbalance calculation and implementing a system to calculate unbalance mass, mass position, and bending moment the control board can decide when and how to modify the washing machine cycle.

The Solution:

Developing a stand-alone smart system to manage washing machine cycles, get information from accelerometers, communicate with the washing machine control board, and automatically test smart algorithms by using a CompactRIOenhancing testing capabilities.


Marco Cugnetto - WHIRLPOOL
Gaetano Paviglianiti - WHIRLPOOL


For years, the Whirlpool Corporation has focused on customer satisfaction. The company’s 6th Sense technology assures performance and reliability converting customer needs to useful and smart features.


The company developed the 6th Sense  smart control algorithms using rapid control prototyping systems based on the LabVIEW Real-Time Module and the LabVIEW Simulation Interface Toolkit. The wide use of these systems helped to test new concepts developed with different simulation tools, directly on a real washing machine.



According to the development process, it is needed to validate engineered control algorithms firmware on the production control board. In addition, algorithm complexity is growing exponentially due to high quality and new challenging cost targets (energy label, washing performances, low noise, advanced features, and more).


A washing machine mathematical model has been developed  to evaluate low-speed unbalance. At higher speeds this algorithm is  no longer valid because of not modelized mechanical behaviour. Currently, the structure is oversized with a certain cost increase and without the real unbalance in control. This may still cause noise. By adding sensors to the system noise has been reduced implementing a high-speed unbalance detection algorithm and a suitable cycle supervisor.

A stand-alone prototype has been built integrating signals from sensors and performing automatic testing without human  intervention. Over the ten months of development, critical points and difficulties such as hardware cost versus effective benefits have been faced off. In the short time frame available, the team carried out a feasibility study, a physical phenoma study, model integration and optimization, and  hardware and software pre-engineering activities. Due to the very tight algorithm requirements, a never attempted brand new solution has been developed: the CompactRIO system with an FPGA core that can acquire signals from sensors and supervise the cycle’s steps by means of the washing machine control board. Team main challenge was using the standard control board firmware to quickly deliver the innovation to the customers. In particular, CompactRIO has been used to build a stand-alone prototype that integrates the standard washing machine with the new sensors.



The team used LabVIEW software to design a system that can  acquire signals from sensors, compute algorithm flow, make decisions for washing cycle, and communicate with the production control board. Furthermore, the provided solution  can manage a predefined test plan automatically making use of the washing machine user interface. By means of the test plan, the user can perform what is requested allowing testing of the system by official test centers as a standard washing machine. The prototype can be used for several scoping activities, modular studies, or component tests.


Team chose accelerometers to learn acceleration and displacement in some points of the tub. Precise measures are needed to implement an algorithm for high-speed unbalance detection. At high speeds the physics of the system are quite different than at low-speed operating points. The cRIO-9076 has been equipped with:
• An NI 9411 digital input module to acquire encoder signals and learn the drum speed
• An NI 9401 high-speed digital I/O module to acquire signals from the washing machine control board
• two NI 9234 4-channel analog input modules to acquire signals from two triaxial and two monoaxial accelerometers


In addition the Compact RIO onboard port have been used: RS232 to acquire feedback and control the washing machine and the USB to connect a memory stick for storing configuration files and logging data. The team designed the architecture over three macro blocks: The FPGA aquires signals from accelerometers at high speeds and generates data to pass to the second block. The second block, developed with the LabVIEW Real-Time Module,  contains the algorithm that evaluates signals from the FPGA and the control boards decides when, how, and which steps the washing machine cycle must take. In addition, it logs binary data on the memory stick and streams the data to the next block, which is the host. This block feature is to   monitor the washing machine cycle status log data in various formats, decide what to log, and change configuration files present on the memory stick connected to the CompactRIO system. The user can control the host front panel through a web server over the same LAN. Once the stand-alone prototype is ready to start, the core software remains in a listening state until the correct program has been selected trough the washing machine knob. Then the system starts the test plan loaded and performs the required cycles without external operation, providing test data on the memory stick.  



The team combined LabVIEW Real-Time, FPGA, and CompactRIO to design and develop a whole system that helps the company quickly deliver the innovation to production and increases quality targets and reduces cost.


Author Information:

Marco Cugnetto

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