IBM: The Value of Quantum Computing in Manufacturing
What is Quantum Computing?
Harnessing the phenomena of quantum mechanics to solve complex problems that today’s powerful supercomputers can’t handle, quantum computing is expected to have enormous potential to develop breakthrough products and services.
Redefining manufacturing, quantum computing technology is expected to provide many business advantages and innovations in the way of chemical discovery, product development, and process optimisation.
IBM states that “early adopters have the opportunity to lock in advantages that will be enormously difficult to challenge.”
How Can Manufacturers Get Started With Quantum Computing?
Set to become a key instrument to transform manufacturing, IBM identifies three ways manufacturers can get ahead of the curve.
1. Challenge quantum champions: experiment with quantum computers, and explore the potential of quantum computing for specific industry applications.
“To help focus on your highest-value problems, have your quantum champions report to a quantum steering committee that includes line-of-business executives and market strategists,” comments IBM.
2. Prioritise use cases for business advantage: depending on an organisations business strategy, customer value propositions, and future growth plans, priorities potential quantum computing use case applications that benefit the business.
“Keep an eye on progress in quantum application development to stay in the vanguard of which use cases might be commercialized sooner rather than later,” adds IBM.
3.Partnerships: consider partnering with quantum ecosystems, like-minded research labs, technology providers, application developers/coders, and startups with supporting technologies.
“Include organisations with similar challenges to gain immediate access to an entire quantum computing stack capable of developing and running quantum algorithms specific to your business needs. Look for breakthroughs in quantum technology that might necessitate a change in ecosystem partners,” says IBM.
Four Use Cases of Quantum Computing in Manufacturing
With quantum computing’s exponentially large state space, manufacturers of materials and drugs stand to benefit from comprehensive modelling of sophisticated molecules.
“Today, there are about 15 million known chemical structures and 300,000 materials. Many more beneficial substances wait to be discovered. Every day, nature produces materials with astonishing properties that industrial manufacturing processes can’t duplicate,” says IBM.
Manufacturers in automotive, aerospace and electronics harnessing quantum computing’s predictive capabilities stand to someday benefit from:
- Materials with an ‘advantageous strength-to-weight ratio’
- Batteries with significantly higher energy densities
- More efficient synthetic and catalytic processes for energy generation and carbon capture
While many products today are designed and pre-tested using computer simulation, quantum computing is expected to provide manufacturers with the ability to simulate component interactions in complex hardware systems, more precisely and comprehensively calculate system loads, load paths, noise, and vibration. In doing so Manufacturers would have the ability to optimise the manufacturing of individual components.
When it comes to control processes, applying quantum computing stands to help manufacturers find new correlations in data, enhance pattern recognition, and advance classification beyond the capabilities of classic computing.
By combining quantum computing with machine learning, IBM expects the technology to have a significant impact in semiconductor chip fabrication, production flows and robotics scheduling, and quality control.
As supply chains ramp up the shift from a linear model to a more responsive organic model based on evolving real-time market demands, and up-to-the-minute availability of key components, quantum computing could accelerate decision making and enhance risk management.
“Enhancing competitive agility, quantum computing might completely transform the supply chain over time, adaptively redesigning it to optimise vendor orders and accompanying logistics using dynamic near-real-time decision-making based on changing market demands,” says IBM.