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Manufacturing & Industry 4.0

Classiq’s scalable quantum software enables predictive maintenance, supply‑chain optimization, and advanced materials design. Classiq's high-level development environment delivers automatically optimized implementations and effortlessly scalable quantum programs you can run on any quantum hardware.
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Our Clients

Our clients trust Classiq to enable their quantum initiatives, upskill their workforce, and deploy efficient quantum programs

Case Studies

Shop‑Floor Scheduling

Shop-floor scheduling assigns jobs to machines across time under resource, sequence, and delivery constraints. This is a classic manufacturing optimization problem. As production lines grow more complex and just-in-time expectations increase, traditional scheduling methods may struggle with scale and flexibility.
A quantum computing use-case in this domain investigates how quantum optimization algorithms, such as the Quantum Approximate Optimization Algorithm (QAOA) can improve scheduling efficiency on the factory floor. Typical objectives include minimizing makespan, reducing idle time, and handling real-time disruptions or rework dynamically.

Real-world or simulated production scenarios are formulated as Quadratic Unconstrained Binary Optimization (QUBO) problems, capturing constraints like machine availability, task dependencies, and shift patterns. Quantum solvers are then applied to find high-quality scheduling solutions and benchmarked against classical heuristics.

For manufacturers, this explores and highlights how quantum computing can support more agile, efficient, and resilient production planning, especially in high-mix, high-variability environments.

 

Predictive Maintenance Classifier

Predictive maintenance relies on analyzing sensor data to anticipate equipment failures before they occur. Classification models are central to this process, helping to identify patterns that signal degradation or malfunction. As datasets grow in complexity and volume, classical methods can struggle with scalability and feature interaction.

A quantum computing application in predictive maintenance explores the use of quantum machine learning algorithms, such as quantum support vector machines (QSVM) or variational classifiers, to improve fault detection accuracy and efficiency. These models may offer advantages in processing high-dimensional, nonlinear data commonly found in industrial IoT systems.

The application typically involves training quantum classifiers on labeled maintenance datasets, comparing their performance to classical benchmarks in terms of prediction accuracy, false positives, and training time.
Enhanced predictive maintenance capabilities can lead to reduced downtime, lower operational costs, and improved asset reliability, making this a high-impact application area for early quantum exploration affecting the manufacturing, energy, and transportation sectors.

Quantum Applications for Industry 4.0

Supply Chain Optimization
  • Route and inventory optimization across global networks
  • Quantum software applications reduce cost and emissions
  • What‑if analysis for disruption scenarios
Materials Design
  • Simulate alloys, polymers, and composites faster
  • Optimized quantum circuits target near‑term devices
  • Reduce prototyping iterations
Robotics Control
  • Quantum reinforcement learning for adaptive robots
  • Improve path planning and energy usage
  • Compatible with ROS and real‑time systems

Enable Your Quantum Initiatives

Quantum Team Building

If you and your team are getting started with quantum computer programming, Classiq’s hands-on quantum training program is built for technical professionals. You’ll begin with a focused introduction to quantum computing fundamentals: qubits, quantum gates, and circuit models. Next, you’ll explore key quantum algorithms such as QAOA, VQE, and Grover’s, with an emphasis on practical implementation. The core of the training is onboarding to the Classiq platform, where you’ll learn high-level quantum algorithm development, resource-aware quantum circuit design, and hardware-aware optimization. This program equips developers, engineers, and researchers with the skills to build scalable quantum applications from day one.

Quantum Use-Case Implementation

Classiq’s Use-Case Scoping and Implementation Program is designed to guide teams through the full lifecycle of quantum application development. Whether you're exploring quantum for the first time or scaling an R&D initiative, our experts work closely with you to identify high-impact quantum use cases, define algorithmic approaches, and map requirements to current hardware capabilities. From initial use-case selection to algorithm synthesis and execution on quantum processors, the program is tailored to your project’s complexity and your team’s quantum maturity. It's a practical, results-driven pathway to developing and deploying real-world quantum solutions with clarity, speed, and technical confidence.

Advanced Quantum Application Development

Classiq’s Advanced Quantum Application Development offering is designed for teams looking to elevate their quantum work into scalable, future-ready solutions. This offering supports the development of complex quantum circuits using Classiq’s high-level synthesis platform, enabling modular, optimized, and hardware-agnostic quantum algorithm design. It’s ideal for organizations aiming to turn their quantum initiatives into long-term assets, reusable components, or proprietary IP. Whether refining advanced algorithms like QAOA or VQE, or preparing applications for next-gen quantum hardware, this offering helps teams industrialize their quantum development and ensure their work is robust, efficient, and strategically aligned with long-term R&D goals.

Explore Quantum Finance Applications