LinePulse: predictive
quality analytics
Real-time data analysis that helps manufacturers reduce the costs of poor quality
Real-time analysis for fast decision-making
LinePulse uses machine learning, cloud computing, and advanced data analysis to give manufacturers insights that aid decision making right on the shop floor, in production real time. It goes beyond the limits of Statistical Process Control to offer advanced analysis of a manufacturing processes in real time.
Improve quality and first time through
Reduce scrap and rework
Accelerate root cause analysis
Avoid process
bottlenecks
Leverage the power of machine learning
LinePulse uses machine learning to analyze previously siloed data from the factory floor in real time.
Now, quality engineers can use their data to find the root cause of a failed inspection or test in minutes.
Manufacturing engineers get warned of an upcoming quality issue, so they can act fast to prevent scrap.
Managers can instantly generate reports and dive deeper into the data to optimize their processes.
“LinePulse is an important solution in Dana’s digital strategy and helps our manufacturing teams automate overhead, monitor and manage product quality, and optimize productivity. Due to the success of a multi-year engagement with Acerta, we are deploying the next generation of LinePulse in key driveline and e-Propulsion plants.”
Joel Scott, Vice President, Global Continuous Improvement
Dana
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How is predictive quality analytics different?
LinePulse is predictive quality — a cutting edge solution that breaks from traditional tools used to manage quality. Here’s how it differs from:
- SPC — Predictive quality looks at all data holistically and adds powerful machine learning analysis
- Business analytics tools — Predictive quality automates data ingestion and provides manufacturing-specific analysis
- Custom ML model —Predictive quality uses repeatable and scalable algorithms to solve any production problem
- QMS — LinePulse does not manage documents or workflows, it uses data to provide real time insights
- MES — A predictive quality solution provides much deep analysis on the factors that affect quality
Simplify quality with predictive quality analytics
1. Ingest all data that impacts quality
- Reduce silos to analyze machine sensor data, test and inspection results, environmental data and product details all together
- Set up data ingestion quickly with an interactive view
- Label data fields, and configure your station, signal, and limit data to help the algorithms understand how your data is related
2. Automate root cause analysis
- After setup, live data is ready for analysis at any time
- When a defect is found, machine learning algorithms generate a list of the most probable root causes in minutes
- Reduce the time it takes to find the cause of a defect from weeks and months to minutes and hours
3. Predict quality issues before they happen
- LinePulse constantly monitors data for early indicators of quality issues
- Track specific measurements, or add multiple data points to one group and see how they relate
- Set up alert thresholds to customize when you get notified
4. Generate reports and dive deeper into your data
- Generate capability metrics reports and filter by time period, model or part numbers, and result
- Drill down to view the data history for a single unit’s production
- View analysis from multiple lines and facilities from a single platform
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Predictive quality analytics in action
LinePulse FAQ
Here are some answers to the questions we often hear about LinePulse and predictive quality.
SPC is great for analyzing processes with known, fixed control limits in isolation. It wasn’t designed to analyze data from multiple sources, or explain why a failure occurred. It’s also not great at catching random anomalies and it won’t catch all defects.
The predictive quality analytics used in LinePulse provides additional value over SPC. LinePulse collects data from multiple sources and systems across the manufacturing plant and provides a consolidated view of manufacturing data, including insights on quality that you can’t get from SPC alone.
The Capability Metrics view in LinePulse provides a traditional-looking SPC dashboard which allows manufacturing teams to streamline reporting requirements and dive into data using familiar approaches. The anomaly detection functionality can catch changes in signals or drift in sensor data where traditional SPC methods would fail. LinePulse doesn’t need to replace SPC – it leverages and supplements SPC.
Some manufacturers have data science teams that work with their manufacturing data to help solve specific production and process issues, particularly to assist with root cause analysis. These teams often use custom machine learning models to analyze and solve one-off problems.
They usually determine the causes of problems and the solutions after the issues have already occurred. Unfortunately, this method of data analysis is not scalable. A new model must be built for every new issue encountered, and it can take weeks to find a solution after a problem occurs. This is time-consuming, labour-intensive, and inefficient over the long term.
LinePulse is a scalable predictive quality analytics solution that gives manufacturers real-time visibility into production. It provides the information your team needs to act on issues immediately so you can find quality problems proactively and fix them easily.
We designed our predictive quality analytics software solution to be used by experts in manufacturing, not data scientists. The machine learning algorithms and analytics capabilities are built into LinePulse and work behind the scenes to generate insights in the platform.
You don’t need data scientists to set up or troubleshoot LinePulse. For LinePulse to make an impact in your manufacturing plant, all it needs is accurate and accessible manufacturing data. Our team can assist you in determining whether your manufacturing data sources are sufficient for the predictive quality analytics that LinePulse can provide.
Every manufacturing facility is in a different stage of quality maturity and digitization. Maybe you are collecting a lot of machine signal data but you’ve never looked at it.
Maybe some of your machines have the ability to collect data, but you aren’t even storing it anywhere.
Maybe you’re interested in learning how to collect data from legacy machine in order to leverage predictive quality analytics.
By connecting with our sales team, we can give you a good idea about whether or not you can benefit from LinPulse right now, or tell you the steps needed to get your data collection where you can reap the benefits of predictive quality.
LinePulse analyzes data in real time. It is designed it to provide a constant pulse on the overall health of a manufacturing plant or line.
We designed the platform to be used on the shop floor, and for the insights it provides to be useful to the speed of manufacturing.
We harness the massive computing power of the cloud to process large amounts of manufacturing data and use machine learning algorithms to perform predictive quality analytics on that data. Storing your data on the cloud is the safest and most efficient way to run a predictive quality analytics solution. Your data will be fully secure.
And – because LinePulse is a SaaS (Software as a Service) solution – we can push continuous improvements to you through the cloud as we add new innovations to the product and you will always have the latest version of LinePulse. Cloud connectivity also gives you the ability to share your manufacturing data between different plants, regardless of their location. The cloud has a lot to offer you, the manufacturer, and us, the predictive quality analytics company. That’s a win-win in our books.
The latest release of LinePulse is version 3.0. Read the release notes here.
If you have any questions, please don’t hesitate to reach out. Our experts would love to take you through a product demo and evaluate what LinePulse can do for you.