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The topic of Quality 4.0 is rapidly becoming a legend due to its mysterious nature; it seemingly has no formal description. Very few people can confidently say that they have seen it or used it.
Artificial intelligence and predictive modeling still require a human element: Especially staff to capture data, manage insights, deploy the software, guarantee production quality and more.
Manufacturers use predictive maintenance software to help tie the probability of equipment breakdowns, and they can use that knowledge to schedule machine preventive maintenance and manage production.
Machine downtime can be expensive. It eats up profits, repair costs, and time that could otherwise be devoted to labor. Organizations can avoid this by proactively observing the condition and performance of their equipment, enabling them to predict and prevent machine failures.
Greg Hitachi has over 30 years of experience working with the manufacturing industry, mainly in the automotive, electronics, aerospace, and consumer goods sectors around the world. Learn about his vision for digital transformation.
In situations where resources are limited to gathering real data would be too expensive or impractical, Monte Carlo simulations can help forecast results and probabilities.
Greg Kinsey, Industry Executive at Hitachi, reveals how creative uses of the DMAIC process with digital transformation are helping factories to unlock the next level of process improvement.