With the advancement of technology, we will be witnessing an increased fabrication of autonomous cars through self-determining production. Unmanned vehicle experience is the next hype in the world. But this goal will not be unanimously achieved through AI/ML or analytic companies.
It calls for Digital Twins.
Being a part of the global age and adopting the new rules of the 4.0 industry, manufacturing companies require an extra set of hands, to fast-track their adoption for digital twins.
This will result in experiencing the absolute advantage of analytics.
Through the lines of industries, it has been proven that Digital twins polish up the maintenance and asset time, optimizes the production lines, revamps the supply-chain visibility and risk-management, and further ameliorates the long-term maintenance.
Digital twins are the supreme thing that helps to attain gamesmanship.
What is a Digital Twin?
To wrap your head around the concept of digital twins, it can be termed as the analog and practical representation of an asset, procedure, and structure that defines the lines of loops across the by-product and the operational lifecycle.
Google Maps are one of the best examples of digital twins.
It has been construed by considering expansive geospatial data. It showcases our geographic location, the direction towards our destination, and helps in figuring out the end journey, and the options of getting there.
Digital Twin Vs BluePrint Vs Simulator
Blueprint can be seen as the artifact, which in turn is BOM, also available in digital representation to churn out the palpable product composition. The presence of one BOM gives rise to immense product instances.
The simulator is the product that analyses the functionality of the product along with gauging the environment in which the product will be employed. The major contribution of the stimulator is in testing. The digital twin can be termed as the replica of the physical product, which in term updates the state and the behavioral data on a timely basis. Every substantial spin-off has one digital twin.
Digital Twin for Physical Product
Designing, building, and operating can be considered as the three critical pillars of the physical product which will be seen throughout the product life span.
With the kick-off of the design phase, the research and design team look at the problems they are facing and conceptualizes the product design. The output generated out of the exhaustive research can be termed as the bill of materials also considered as the blueprint of a product.
Once the blueprint is generated, it is then archived and overseen in the PLM system, which is later on passed onto the manufacturing team.
When the phase for building kicks in, the manufacturing team starts assembling the raw materials, so that a physical form can be assigned to the BOM. Once finished, this product is then a part of the finished goods inventory.
ERP systems play a key role in orchestrating the building process by creating a digital twin for the physical product.
Next in line come the sales and service team, which contributes to generating feedback for the product once it’s handed over to the users. This, in turn, helps in providing pointers for the flawless functioning of the product and further maintenance for smooth operation.
Once the product is launched, the to-the-point analysis of the behavioral data concerning the product is quite difficult. Thus, Digital twins lend a helping hand in understanding the product usage, the context and spawn the appropriate feedback.
Digital Twin for Manufacturing Process
The process of manufacturing can be defined as a collation of various procedural steps which transform the raw materials and then assembles them, giving rise to the result, the product. To bring about the final product, certain steps are to be performed by way of machines and manually, which is known as the manufacturing assembly line. Digital twin needs to be in sync with the manufacturing assembly line, so to provide desired data.
Digital twin serves as the platform to execute ML algorithms and provide solutions for the optimal utilization, analysis of the impact, predicting such perusal, and shaping the what-if analysis.
Digital Twin for System
All the other things, that don’t fall under the mentioned categories and steps, can be denominated as a company, a factory, a city, a distribution system, etc. If we go back to the Google Maps example, it can be applied here perfectly.
A smart city can be solely managed and controlled by a digital twin. Considering the high advantages of the digital twin if it falls under the hands of people with malicious intents, it can prove to be a highly damaging technology advancement.
To gain success, it is important to make security a key component of the digital twin process.
Digital Twin and Autonomous
Considering the implementation of digital twins in such a complex system, the cost of implementation is high, yet the advantages are gigantic.
Anything, that can be considered “smart” shall mandatorily have a digital twin of the product/process/system otherwise it cannot have a “smart” prefix.
For any product/process/system to become autonomous they need to be smart. Digital twin implementation is mandatory to achieve autonomy.