The focus of every industrial revolution has been increasing the productivity of production systems. The fourth industrial revolution is here, and it’s seeking to improve both production and management systems. Digital transformation driven by smart manufacturing (also known as Industry 4.0) is the basis of this latest one – creating opportunities to achieve levels of productivity and specialization not previously possible.
Combining data generated through the Industrial Internet of Things (IIoT) and analytics creates a new set of capabilities known as predictive maintenance and quality. Fueled by smart manufacturing, these new capabilities are changing the way we do and see business, helping recognizing patterns and predicting failures or product quality issues before they happen.
Introducing the new industrial IoT platform
Most factories are composed of operation technology (OT) assets such as machines, equipment lines and robotic devices that aren’t always connected. The current trend is leaning toward smart manufacturing with a more IT-based factory floor to help save time, labor, cost and maintenance and upkeep. With OT and IT converging, the IIoT platform is emerging as a new, innovative concept for smart manufacturing with artificial intelligence (AI)-based technologies, including analytics, big data and cognitive manufacturing.
Smart manufacturing can spur a new surge of manufacturing productivity.
Targeting the pain points for key manufacturing personnel
In order to understand the impact of Industry 4.0 solutions, we must examine the key people involved in all aspects of a factory. True transformation happens when all unique challenges and each pain point is targeted.
Transforming your factory with a three-tiered architecture solution from IBM
Keeping the needs of different types of workers in mind and using our extensive manufacturing experience, IBM developed a three-tiered distributed architecture to implement smart manufacturing more efficiently. The model addresses the autonomy and self-sufficiency requirements of each production site and balances the workload between the three tiers.
- Edge level. The most physical part of the factory where product-related activities are performed.
- Plant or factory level. Where plant and local activities are orchestrated and connected.
- Enterprise level. Where analysis of all levels of information happens, and information storage for visualization and analytics is provided.
Leveraging the three architecture tiers to drive performance
IBM offers a suite of enterprise asset management (EAM) solutions to help drive cost savings and operational efficiency across the factory value chain. The portfolio of EAM solutions from IBM analyzes a variety of information from workflows, context and the environment to drive quality and enhance operations and decision making. The portfolio of EAM solutions from IBM helps deliver a smart manufacturing transformation.
Production quality insights use IoT and cognitive capabilities to sense, communicate and self- diagnose issues to optimize each factory’s performance and reduce unnecessary downtime. Insights help reduce unplanned downtime.
