Industry 4.0 – The Smart Factory Revolution

Manufacturing industry is awash with data. Instrumentation, sensors, machinery, automation systems, production and operation, maintenance records, and health and safety applications collectively produce a constant flow of data. Industrial products manufacturing enterprises need technology that supports the vertical delivery of insightful data throughout the organization, both to meet consumer needs and to aim for continuous process improvement.

To address operating and market concerns and deliver on the promise of Industry 4.0 artificial intelligence (AI)/cognitive computing is being heralded as the future of intelligent manufacturing.

Artificial intelligence/cognitive

Cognitive computing refers to next-generation information systems that understand, reason, learn and interact. These systems do this by continually building knowledge and learning, understanding natural language, and reasoning and interacting more naturally with human beings than traditional programmable systems.

The IBM Institute of Business Value has recently issued a report titled ‘The artificial intelligence effect on industrial products’ – Profiting from an abundance of data. 

Manufacturing organizations face significant challenges: cost pressures, increased regulations, disruptive technologies and the increasingly costly delivery of raw material resources. Processes, workflows and the understanding of performance are dramatically changing. Operations can no longer work in linear execution, or in isolation of other functional work streams such as engineering, maintenance and planning. Instead, the value chain needs to perform as an integrated whole to support the fluctuating demand cycles and higher cost supply activities. New AI technologies have the capacity to make sense of the abundance of data through systems that can adapt and learn. By expanding digital intelligence adoption, AI technologies can help executives translate data into insights to drive greater innovation, and better operational and financial decisions.

A single hour of production downtime is very expensive. Using cognitive technologies ─ a combination of artificial intelligence (AI), Industrial Internet of Things (IIoT) data, advanced analytics and more ─ users can extract insights from data to move from reactive to predictive maintenance, pinpoint improvements, reduce waste and increase yield.

Nikon Strategic Focus on Quality 4.0

Improve product quality

Fine-tuning quality management can prevent costly rework. One of the world’s largest automakers uses IBM’s predictive modeling tools to optimize manufacturing processes and turn data into real results — 25% increase in productivity, 50% reduction in optimization implementation, and minimized waste.

To help understand the potential of Industry 4.0 IBM has created an interactive demo showing how a shoe manufacturer uses IoT, analytics, machine learning and AI to double productivity without doubling equipment and asset expenses.

Put on your safety glasses and take the interactive virtual tour by clicking on the image below.

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