3 Ways Engineers Can Drive Business Value with Manufacturing Data Analytics

Author: Tom Lin

As an engineer, you have the opportunity to design and develop superior products using data that covers the entire product lifecycle.

 

But extracting value can be difficult when you face common data problems, including:

 

• Siloed data that does not give you the complete view of the product lifecycle or other business areas
• Inaccurate or incomplete data
• Legacy platforms and technologies that are not equipped to process the massive amounts of data products create

 

How real-time data analytics improve engineering

Advances in data analytics allow you to improve and accelerate design, identify problems earlier, and gain insights into customer behavior. Forward-looking manufacturing companies are incorporating data analytics strategies to expedite decision-making, bring products to market faster, and develop innovative designs that resonate with customers.

 

Here are a few ways robust, collaborative analytics can help you overcome challenges in your engineering department.

 

1. Quality analytics

When it comes to quality assurance, data analytics can help to accelerate product development, reduce manufacturing costs, and improve your approach to quality management. By enlisting data analytics throughout the design and manufacturing processes, you can develop a course of action to produce higher-quality products and avoid manufacturability problems. All of these will help to deliver value to the bottom line.

 

Here are the benefits of quality analytics in product development:

 

• Gain competitive edge: Stand out from the competition by improving product quality, reducing time to market, and minimizing the risks of innovation
• Reduce costs: Identify potential design flaws early on, so you can avoid costly rework and redesign
• Produce quality products: Attract more customers by producing products that meet the highest quality standards
• Promote sustainability: Eliminate waste by reducing redesigns, errors, and prototyping to create more sustainable products, which has become an important purchase criterion for customers

 

2. Digital twins

In smart manufacturing, the benefits of digital twins and applications for data from digital twins are unlimited. From foreseeing maintenance issues to testing product upgrades, this conjunction gives engineers insights to make the right decisions.

 

Here are the benefits of digital twins and the data they create:

 

• Decrease time to market: Identify anomalous behavior, predict future states, and optimize production so you can take action and get products to market faster
• Optimize product performance: Ensure consistency is maintained across production so the end product will always match the specifications
• Conduct simulations and experiments: Access real-time data to conduct what-if analysis and identify performance problems

 

3. Product lifecycle feedback

Another area where data analytics can help you is with 360-degree product lifecycle feedback. You can study the product data and use it to strengthen product design, performance, and customer experience. It can help intelligently position your brand in the market and align your team to address the needs of your customers.

 

Here are some ways in which product lifecycle can improve your engineering processes:

 

• Accurate product insights: Gain valuable product insights about longevity, failure points, maintenance, and end-of-life to better optimize product design
• Make product improvements: Get data from various sources like maintenance reports, machines, spare part inventory, and sales to make the right design choices for products
• Meet customer expectations: Build better products that solve customer issues by leveraging product lifecycle analytics

How to get started with data-driven engineering

As straightforward as it may sound, creating the right data and analytics strategy can be tricky. You need to break down data silos and integrate disparate data sources into a central data storage system to gain access to real-time data. Integrating different data sources and analytics processes also requires different skill sets, tools, and techniques.

 

To handle large data volumes and fuel real-time analytics, you need to invest in the right Industry 4.0 technologies. This is where Wavicle’s data and analytics consultants can help. The combination of our manufacturing domain expertise and data analytics skills will help to unlock the true potential of your data. We can transform your manufacturing process by implementing the right tech stack that will effectively integrate analytics into your organization.

 

If you would like to better utilize data and analytics within your organization, contact our experts to learn more.