Quality 4.0.
Industry 4.0.
XYZ 4.0.
Put 4.0 after any term and what you finally get is a heady cocktail.
Like all other domains, Quality also seems to be undergoing this transformation.
What is Quality 4.0?
What does the 4.0 after Quality really signify?
4.0 as a concept, in a simple sense, means the use of systems that learn on their own using artificial intelligence (AI) and machine learning (ML) at its foundation.
AI and ML are the hot buzzwords these days.
Talk to any and every Tom, Dick and Harry in the corporate world and after some time into the conversation you will hear AI and ML.
Talk to any school or college student and after some time into the conversation you will hear AI and ML.
What is AI?
What is ML?
Let us first understand these two in simple terms and in a layman’s language.
AI or Artificial Intelligence
- The purpose of AI is to initially replicate and eventually replace the human intelligence being used for decision making while running a process.
- For example, a train can be made to start and stop based on the same criteria a human driver will typically use before making such a decision.
- AI is meant to go beyond the realm of routine decision making to "intelligently" figure out the right decision even if something in the process or environment changes and that too suddenly.
- Suppose the train in the example above is ready to start since all doors are closed, green signal is on and all those standing on the platform are at a safe distance from the train. Also suppose, at that instant and suddenly one of the persons standing on the platform jumps on the tracks right in front of the engine. So how will you make sure the train doesn't get started?
- The way the above will be ensured is where AI can supposedly play a role. The supposedly here is a big SUPPOSEDLY because there are possibly infinitely many possible scenarios like this one.
ML or Machine Learning
- The purpose of ML is to make a system behave "intelligently" without relying upon human intelligence which may be getting used otherwise for decision making while running a process.
- For example, historical data on all train starts can be used to identify patterns, trends, decision trees and heuristics in conjunction with relevant real-time data and information to aid a train system to decide whether it is right and safe to start the train at a given point in time.
- ML sits at the back end of AI and is the thing that makes the system behave "intelligently" and figure out the right decision even if something in the process or environment changes and that too suddenly.
- Suppose the train in the example above is ready to start. Also suppose, at that instant and suddenly one of the persons standing on the platform jumps on the tracks right in front of the engine. ML will use historical data to indicate that the train can get started. It will, however, use real-time data to cause an interruption so that the final decision is right and safe. But what will that take?
- The way the above will be ensured is where ML can play a role and direct the AI module built into a system to make it behave "intelligently".
Note:
- It is fine to say that a system becomes intelligent with AI/ML
- However, a system does not "become intelligent", rather it starts to "behave "intelligently"
- So, it is better to say that ML induces AI in a system which makes it behave "intelligently".
With that backdrop, let us come back to Quality 4.0.
Quality 4.0
In fact, after having understood AI/ML above, there is nothing left to explain what Quality 4.0 is.
Take Quality.
Inject AI/ML.
What you get is Quality 4.0.
So why so much hype?
Why so much of brouhaha?
There is nothing new here.
In fact, there is nothing new in AI/ML too.
The terms AI/ML and their foundational concepts have been around for decades.
With the advent of computers, automation or digital enablement of systems and processes in all walks of life and business became possible.
And it has been going on since several decades.
The methodologies and technologies to digitally enable or automate a process have evolved and AI/ML is an advanced stage in that journey.
The same applies to the field of Quality.
Processes used or influenced by Quality can be digitally enabled like any other process.
There is no big deal with that.
In some sense, when the automation or digital enablement or digital transformation journey evolves to a very advanced stage and it starts leveraging AI/ML concepts, what you get to is the 4.0.
If what you do is called Quality, then the above would result in Quality 4.0.
That's right.
At the most fundamental level, that’s all there is to Quality 4.0.
