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. 

Using Minitab’s Predictive Analytics with Auto ML in manufacturing enables quality improvement and warranty prediction, practically in real-time.

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. 

A global leader in the food and beverage industry faced a complex challenge in their process of refining corn sugars.

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.

Real-Time SPC provides data collection, monitoring, alerts, and analysis that allow organizations to identify actionable insights immediately.

Applying Statistical Process Control (SPC) methodologies to the right data will help you proactively control processes and prevent manufacturing quality problems before they occur.

It has been said that one of the greatest attributes of humankind is the want and need to bring order to and better understand the universe and our place in it. To do this, we have qualified, quantified, and categorized just about everything around us and analyzed and ranked the relationships among just about all things. 

By considering the pattern of all accidents, including those near misses, a predictive model can be created, isolating the cultural root causes of workplace injury and larger scale disasters.