A technology which has combined machine learning, artificial intelligence and software analytics with data to create a living digital simulation model which receive the changes and updates as per the existing physical counterpart.
A digital twin is just a virtual model of your product, service or process. By combining physical and virtual world together, this technology really helps in avoiding the glitches and problems that used to occur before. It monitors the systems, analysis the data and thus gives us the opportunity to plan for the future ahead by making use of simulations.
A key challenge for today’s manufacturing industry is not the lack of new ideas and products, but rather the ability to design and build new products efficiently. With the rise of digital technology, manufacturers can now tap into data-driven solutions that make use of computing – the cheapest and most abundant resource available to the industry today.
At the same time, IT is becoming an integral part of many products, a trend enabled by inexpensive sensors, processors and storage, purpose-built software and purpose-built clouds that allow data storage and ubiquitous connectivity.
This environment sets the stage for a digital-twin approach to product development. The process uses stochastic simulation to generate what-if scenarios that can help manufacturers avoid costly product quality issues, while speeding time to market and increasing throughput.
DIGITAL TWIN AND BUSINESS
As the physical product transmits the information, the examination of this information can truly help in planning the product right. A coherent choice can be taken about the material, execution, similarity, serviceability and other such highlights of the product. In this way, equipping the business to bring more value to customers.
In spite of the best planning and building, obstacles can come while fabricating an product. Here, digital twin aides in distinguishing the bothersome production issues like a mistake in the working of the segments or a blunder while assembling these segments. By relating this information with digital twin, defects at generation level can be disposed of rapidly.
Organisations can deliver better product benefits with digital twins. They will have the capacity to foresee the failures of the hardwares and in this manner proactively start the administration call, additionally keep the exorbitant spontaneous downtime of the customer.
One can say, from history and experience, that risk management is truly an overwhelming errand. The celebrated case of Takata airbags failure and the accompanying review of automobiles was undoubtedly an image ruining experience for the brand. Be that as it may, with digital twins now, businesses have considerably more dependable methods for separating and following up on risk parameters. Accordingly, we perceive how this brilliant innovation can deliver value to the businesses and effect the ROIs altogether.
DIGITAL TWIN AND IOT
Digital twin truly sits in the continuum of the Internet of Things (IoT). In the event that we concur that the establishment of IoT comprises of connectivity, sensors and analytics, then predictive maintenance becomes an established IoT application. Predictive maintenance is a case-based reasoning empowered by data. The digital twin approach handles this by combining product information, including maintenance history, from configuration to operation.
Genpact is guiding a “digital wind farm” idea used to inform the setup of individual wind turbines preceding acquisition and development. Once the farm is built, each virtual turbine is sustained information from its physical equivalent, and programming alters turbine-specific parameters, for example, torque of the generator and speed of the sharp blades, to optimise power production at the plant level. The expectation is to create 20 percent picks up in productivity.
PTC has created “smart connected product life-cycle management (PLM)” programming called “Windchill.” A Swiss solar panel manufacturing organization, Oerlikon, utilizes Windchill to naturally track system metrics and keep account managers notified of the state of client systems. PTC calls it a FRACAS process: a failure reporting, analysis and corrective action system.
Dassault Systèmes has created an aviation and defence-specific manufacturing operations administration product called “Build to Operate.” This can monitor, control and approve all facets of manufacturing operations, varying from replicable procedures and production sequences to the stream of expectations all through their chain of supply and on a larger scale. The system has been deployed by Airbus Helicopters for the present and future manufacturing of helicopters.
This notion of machines talking, reasoning, and making decisions with each other will be transformative for how industrial systems are operated and managed in the future. During the 2020-2030 decade, there may be over 50 billion machines connected together, with over seven billion internet consumers. With the network effect in play, the world will see another, even more sweeping internet transformation.
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