Excerpt: The Printed Circuit Assembler’s Guide to… Smart Data, Chapter 2

Reading time ( words)

The following excerpt is from The Printed Circuit Assembler's Guide to...™ Smart Data: Using Data to Improve Manufacturing book.

Chapter 2: The Difference Between Data and Analytics
Companies have been collecting data in large volumes. Highly varied data from manufacturing operations comes in quickly that needs to be validated, and its value prioritized so that it can be turned into something useful—transformed from big data to smart data. The amount of data available has grown exponentially into big data. Twenty years ago, a PCB work order resulted in 100 data records, megabytes of data; today, it is 10 billion records, terabytes of data. The investment in collecting this data and storing it is high. However, without a way to analyze the data, without analytics, it will not result in ROI.

Using analytics provides the best results with high-quality data. However, with bad or non-validated, and inappropriately prioritized data, the most advanced analytics still can be misleading and a waste of time. What is high-quality data? It is data that has been normalized, formatted, and validated so that it can be translated and read to provide insights and foresight. It is data that can be understood at the point of consumption and be immediately acted on.

Data analytics is the process of examining data sets to draw conclusions about the information they contain. Manufacturing intelligence means taking big data, applying advanced analytics, and putting it back into manufacturing processes.

Analytics for manufacturing can be used in:
• Asset management for accurate, real-time utilization, and OEE
• Traceability for capturing and investigating complete material and process traceability data for individual PCBs, as well as full system assemblies, using high-availability big-data storage
• Operation and labor management to measure and analyze how resources are spent and track WIP in real-time
• Quality control to identify and analyze process and material failures and drive continuous improvement
• Design-to-manufacturing flow to detect factors affecting yield and point out areas for improvement

To download this free eBook, published by I-Connect007, click here.

To view the entire I-Connect007 eBook library, click here.

Other related content

I-Connect007 Column: Lean Digital Thread, from Sagi Reuven, Siemens Digital Industries Software



Suggested Items

Excerpt: The Printed Circuit Assembler’s Guide to… Smart Data

04/07/2021 | Sagi Reuven and Zac Elliott, Siemens Digital Industries Software
Whenever we discuss data, keep in mind that people have been collecting data, verifying it, and translating it into reports for a long time. And if data is collected and processes are changed automatically, people still will be interpreting and verifying the accuracy of the data, creating reports, making recommendations, solving problems, tweaking, improving, and innovating. Whatever data collection system is used, any effort to digitalize needs to engage and empower the production team at the factory. Their role is to attend to the manufacturing process but also to act as the front line of communications and control.

What Makes a Great Supply Chain Manager?

04/05/2021 | Timothy McLean, TXM Lean Solutions
Building a competitive and reliable supply chain is a critical success factor for any manufacturing business. This is especially true today, where we face constant volatility and disruption across global supply chains. In this environment, effective supply chain leadership is more critical than ever. So, what makes a great supply chain manager?

What Makes a Good Process Engineer?

03/03/2021 | Nolan Johnson, I-Connect007
Nolan Johnson recently spoke with Tuan Tran, director of customer solutions at Green Circuits, about what makes a successful process engineer. They also discuss a typical day in the life of a process engineer—from pre-manufacturing through post-DFM, for process improvement. As Tuan points out, there are a variety of paths to becoming a great process engineer.

Copyright © 2022 I-Connect007. All rights reserved.