Industry 4.0 Pt. 2 – Helping Manufacturers Prepare For The Future

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Manufacturers are under pressure. They need to do more with less which often means finding ways they can save money and expand margins. The options?

• Making more finished products and selling those products cheaper;
• having less costly downtime and less waste;
• and having fewer defects and higher satisfaction, all while requiring fewer raw materials, resources and energy.

Helping manufacturers prepare for the future

The real game changer is how to help manufacturers make sense of their data. It is important to understand the context of the data variables and have the right analytical tools and capabilities. Often this requires experience to help manufacturers drive outcomes.

Manufacturers are looking for tools based on machine learning and AI to integrate data from a variety of structured and unstructured sources to spot patterns. This includes orderly data in spreadsheets and ad-hoc data found in maintenance orders, etc. Increasingly, leaders are gathering visual or acoustic data and integrate this into data models. Advanced AI and cognitive technologies allows firms to process all this information and identify outcomes related to cost drivers like downtime, quality and resource optimization.

What are manufacturers missing by not riding the Wave?

Most manufacturers understand they are sitting on a gold mine of data about their operations. Equipment on the factory floor has been producing data for decades in some cases. And big data and analytics have been around for a while. What is new is the industry’s ability to process all of this data and decipher the patterns.

In failing to pursue Industry 4.0, firms are missing opportunities to use the data from their operations to better understand equipment failure, quality, and resource optimization.

Don’t wait. Start today.

The biggest challenge with Industry 4.0 is separating the concept from the execution. This concept is overwhelming to many firms.  But there are some questions to start with:

• What can you do today to start down the right path?
• What are your pain points around concepts of equipment downtime, quality, and process optimization?
• How are these pain points unique to your industry?

Reducing asset downtime: There can be a high cost of downtime for firms running capital intensive equipment. Near term projects include finding ways to incorporate equipment performance data to predict failure and build predictive maintenance plans.

Improving quality: Some firms – particularly high volume or precision manufacturers – experience high costs related to quality. The cost of scrap or rework is often extensive – and in the case of volume manufacturing a quality defect will quickly be reproduced across a large production run. These firms look for solutions that can quickly spot defects, categorize that defect, and understand the root cause.

Driving process optimization: Other firms look for opportunities to ensure operational efficiency in process intensive industries. In sophisticated process manufacturing, complexity and high operator turnover can lead to costly deviations and high raw material usage or energy consumption. These industries look for solutions that can understand variables and help plant operators optimize efficiency.

With pressures increasing for manufacturers one thing is increasingly certain: it would be a mistake to underestimate the role data and analytics plays in advanced manufacturing. Increasingly we believe the operators that growth and thrive will be those that embrace the concepts behind Industry 4.0 technologies and are able to translate these concepts to tactical projects. Start fast. Start now.