Improve Quality

Without real quality measurements, scrap is just money going down the drain.

A quality product is core to what manufacturers do. How can you reduce scrap and ensure quality?

With manufacturing analytics, you can calculate the quality of a part from data gathered and stop problems as they happen, reducing your scrap rate stimulatenously.


Measure & Calculate Quality

Automatically collect part counts and reject reason codes from sensors, PLCs, or operators to calculate the quality of a part. 

Determine Common Causes & Get Alerts

Get real-time alerts, via mobile app or email to stop problems as they happen. Consistent, accurate data can drastically help to reduce scrap and increase quality.

Understand Trends

Track trends in your data to see how your plant is running. See how continuous improvement projects affect the scrap rate over time.

Measuring & Calculating Quality

Correctly calculating quality is essential to a reliable, realistic OEE.  To calculate quality of a part, SensrTrx collects part counts and reject reason codes directly from the PLCs or sensors as well as from input from operators or supervisors.

This includes data taken from specialized testing equipment and data beyond reason codes such as temperature, pressure, speeds, vision systems, and any other data points accessible.

Determine the Most Common Causes of Scrap and Get Alerts

Get alerts directly to your mobile phone or via manufacturing insights emails when scrap is higher than normal, giving you the ability to prevent issues from becoming worse.

Use Pareto Charts to help determine the most common causes of scrap. When you know common causes, you can use trend analysis to determine how the plant is running.

Understand Scrap Trends

Track trends in your data to see how your plant is running, both in real-time and over an extended period of time. 

Look at scrap by the number of times a scrap reason occurred, average number of scrapped parts per entry, total number of scrapped parts by reason code, or even by shift to determine if one shift has more scrap than another. 

Using trends, you can easily see the effect of process or system changes over the long term. You can see when scrap is increasing or decreasing and quickly take action to resolve the issues.

99.8% Reduction in Scrap Rate

Oral BioTech experienced excess downtime and high scrap rates. Using manufacturing analytics, the manufacturer was able to get the visibility needed to see what was going wrong and why. Using that data, they were able to correct significant problems, and in turn, greatly improve the quality of their products.

"You can’t really manage what you’re not measuring. [With SensrTrx and Banner sensors] it’s amplified when you’re measuring in real-time. People are able to make improvements, based on the data, right then and there."

– John Bowers, VP of Operations at Oral BioTech

Common Challenges in Manufacturing 

Lack of Visibility and No Accountability

Without visibility into the plant, it’s hard to know if you’re winning the day. How can you see what’s happening in real-time?

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Excess Downtime

Every minute a machine is not running represents lost opportunity. How can you reduce downtime on the floor?

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Manual Processes

Traditional, manual data collection is not timely or accurate. How do you ensure automatic data collection that helps to provide insight into what’s happening in the plant?

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Low Capacity, Throughput

Throughput is extremely important to a manufacturer’s ability to meet schedules and deliver on time. How can you increase capacity and ensure goals are met?

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Poor On-Time Delivery

How do you ensure on-time delivery? Knowing if you’re winning the day can help you achieve that goal.

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Too Much Unplanned Overtime, High Costs

Unplanned overtime causes significantly higher costs, decreasing the bottom line. How do you eliminate unplanned overtime to reduce costs?

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Watch the case study

Learn how you can improve quality with SensrTrx.