The Argument for Adaptive Production Rather Than Just Flexible Manufacturing
In an interview with Automation World, Annemarie Breu, the senior director of automation software deployment and incubation at Siemens AG, discussed the company's innovative approach to manufacturing: adaptive production.
Adaptive production is a game-changer in the industry, focusing on intelligent, responsive, and resilient systems. It extends beyond traditional flexible manufacturing by optimizing the entire production process ecosystem rather than just switching product types.
At the heart of adaptive production lies edge computing, a key technology that processes data locally in real time and integrates with existing legacy systems via protocol connectors. This enables real-time functions like visual inspection, anomaly detection, and predictive maintenance.
Artificial Intelligence (AI) and Machine Learning (ML) are also integral to adaptive production. They enable dynamic optimization, predictive analytics, quality control, and real-time decision-making, allowing systems to automatically react and adjust to variability in demand, equipment, supply, and environmental conditions.
Intelligent sensors, such as cameras, microphones, environmental monitors, and AI-powered computer vision, capture rich, real-time insights for continuous monitoring and quality assurance. Digital twins and simulation platforms model production lines and run “what-if” scenario analyses for optimizing scheduling, maintenance, and resource allocation.
Manufacturing Execution Systems (MES) with integrated electronic work instructions and voice assistants streamline shop floor operations, reducing downtime and improving productivity. Cloud and edge computing integration ensures that edge devices handle immediate machine-level responses, while the cloud supports overarching strategic analytics and coordination across the manufacturing ecosystem.
Modular and reconfigurable hardware/software architectures (Reconfigurable Manufacturing Systems) allow for rapid adjustments in structure, capacity, and function to meet changing product mixes or market demands. Augmented Reality (AR) training solutions help upskill operators efficiently, supporting adaptive systems where human-machine collaboration is optimized.
Together, these technologies create manufacturing environments that are intelligent, responsive, and resilient. They continuously improve themselves by adapting production parameters in real time to operational disruptions, demand shifts, or supply chain changes.
Adaptive production does not replace workers but supports them by tailoring systems to operators, engineers, and managers. It enables real-time reactions to disruptions in demand, supply, or operations, and optimizes production and resource allocation using AI, predictive analytics, and automation.
The goal of these systems is to continuously improve themselves, striving for a manufacturing future that is more efficient, adaptable, and resilient. Adaptive production applies across all manufacturing scales, from small businesses to global enterprises, making it a promising solution for the future of the industry.
- Edge computing, a fundamental technology in adaptive production, processes data locally in real-time and integrates with existing systems, enabling predictive maintenance and real-time functions.
- In the adaptive manufacturing of the future, finance and business sectors stand to benefit significantly from technologies like artificial intelligence (AI) and machine learning (ML), which aid in dynamic optimization, predictive analytics, and real-time decision-making.
- As the manufacturing industry moves towards adaptive production, it will increasingly leverage technology like edge computing, AI, and machine learning to create intelligent, responsive, and resilient systems that can continuously improve themselves to meet the demands of various scales, from small businesses to global enterprises.
