Fuzzy Logic In Washing Machine: What Does It Mean?

Washing machines were invented to unburden your workload of cleaning laundry. But as time passed, they became advanced to have numerous features and functions in order to provide superior cleaning performance and reduce water and energy consumption.

One such feature is fuzzy logic or fuzzy control. Let’s take a deep dive to know what fuzzy logic is.

What Is Fuzzy Logic?

Fuzzy logic is an approach that computes multiple possible truth values by processing through the same single variable. In simple words, fuzzy logic considers a spectrum of possibly useful data to come into a range of accurate conclusions. It bypasses the standard binary Boolean logic of 0 and 1 and proposes an array of options between truth and false instead. 

The concept was first approached by Lotfi Zadeh of the University of California in 1960. He was working on the issues and problems of computing with understanding natural languages. 

As human beings, we use natural language to assess anything beyond truth and false. So, fuzzy logic takes the same route of analyzing certain situations beyond the binary boundary of absolute truth and false. 

Here’s a diagram to understand how binary boolean logic differs from fuzzy logic.

Fuzzy Logic in Washing Machines

In washing machines, fuzzy logic essentially means a group of sensors and controls that constantly monitor the conditions inside the drum to optimize the wash performance, energy, detergent and water consumption.

Advanced machines weigh the load and alert you when you overload the washing machine, suggests the quantity of detergent needed, assesses the fabrics, water hardness and many such factors. Some washing machines with AI even use their past experiences and usage patterns to optimize their performance.

For fuzzy logic to work properly, it needs various sensors and control mechanisms.

Related reading: LG vs Bosch Washing Machine Comparison

Sensors And Control Mechanisms In Washing Machines

Load Sensor: Determines the weight of the load and adds an appropriate quantity of water to the drum.

Automatic Temperature Control: Adjusts the correct temperature for the cycle you are using.

Automatic Dispensers: Dispenses detergent, bleach and softener at the right time in the cycle.

Fuzzy Control: Contains load sensors that indicate water and detergent amount required.

Neuro- Fuzzy Control: Features sensors that detect fabric type and dirt levels to determine the quantity of detergent and water needed.

But note that not all washing machines have all these sensors and controls. In fact, some of them use this term just as a marketing gimmick. You will notice that in certain models, irrespective of whether you put a full load or a half load, the washing machine takes the same time and consumes the same quantity of water for washing.

Related reading: All You Need to Know About Power Consumption of Washing Machines

Fuzzy Logic In Indian Washing Machine Brands

The fact to be told, most of the washing machines in India do not have advanced fuzzy controls to detect dirt levels or fabric type. However, it is not all doom and gloom.

In IFB, for example, you find a feature called Foam control. If an excess level of foam is detected, the washing machine incorporates an additional rinsing cycle to clear it off and resumes the wash program. Sometimes, LG and IFB washing machines increase their wash duration mid-cycle. While they may be frustrating for some, it is actually fuzzy logic at play.

Let us look at what other brands have to offer. Note that all models do not have fuzzy logic. Check the product description of each model to understand what it really offers.

Related reading: Detergent Powder vs Liquid- Which is Better?

Samsung

Samsung does not have fuzzy logic in its entry-level models. But, in higher-end ones, like the 8 Kg WW80T504DAN/TL, it has AI controls that suggest cycles and displaying timely information. The 9 kg WW90TP84DSB has an automatic detergent dispenser that uses the right amount of detergent after analysing the fabric and dirt levels.

LG

In LG top-loaders with fuzzy logic, it weighs the load of clothes to determine the quantity of water and duration.

IFB

As mentioned earlier, the foam control feature is an application of fuzzy control. In addition, IFB washing machines with fuzzy logic detects the load quantity and optimizes water consumption accordingly. It also has a load balance correction feature that balances the load to minimize vibration and damage to the washing machine.

Haier

Haier washing machines with fuzzy load detects the load level and adjusts the duration accordingly.

The Next Level of Fuzzy Control- Neuro-Fuzzy Control

Neuro fuzzy control takes fuzzy control to the next level. It comes with a few sensors that detect the fabric type and dirt level to advise the quantity of detergent and water needed to wash the specific fabric is also determined safely.

An optical sensor measures a light beam and translates the light’s visibility into an electronic response. The sensor consists of two parts – a light-emitting part and a light-receiving part.

This sensor analyses the light that is coming through the water and measures the density of water. The dirtier the water, the higher the density will be. Plus, the transparency will be lower. On the other hand, the less dirty the water, the more transparent the water will be.

So, the sensor can easily measure the level of dirtiness of the water. It can stimulate other sensors to determine the amount of water, detergent, and power needed to clean the dirty laundry!

The washing machine can accurately measure the dirtiness and load by applying the fuzzy logic using the input and output relation. This way, it can give you a proper idea of how much time it will need to complete the wash cycle.

Cost

As you can obviously expect, washing machines with fuzzy logic are expensive than the ones without them. But on the positive side, its optimizes water and energy consumption. Further, it enhances the durability of the washing machine too.

Overall, it absolutely justifies the cost.