February 27, 2017

Improving Quality with Manufacturing Analytics

Production quality product is core to what manufacturers do. Producing a product with quality issues will result in additional costs, rework and possibly unhappy customers. Most customers rate their suppliers on a number of different quality metrics and will only award contracts to those who consistently deliver a product that meets their specifications.

oee quality

OEE: Improve Quality

We talk a lot about Overall Equipment Effectiveness, the benefits of measuring OEE and using it in process improvement projects. As you know OEE is made up of 3 basic components

  • Quality
  • Availability
  • Performance

Quality measures the amount of good parts produced vs total parts produced. To calculate Quality of a part, SensrTrx collects part counts and reject reason codes directly from the PLCs or other sensors. SensrTrx can also augment this information with 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 from the equipment.

In another post, we discussed what manufacturing analytics is and how it can help look at many different data points across the entire company. Here we will focus on using SensrTrx to reduce scrap and improve quality in manufacturing.

Pareto Charts for Manufacturing Quality

SensrTrx offers Pareto Charts out of the box to help determine the most common causes of scrap. Pareto charts come from Vilfredo Pareto who identified the 80/20 rule and created the chart that bears his name.

Our example Pareto chart shows number of rejected parts group by reason code. We can see that 80% of our scrap is caused by 2 reasons:

  • Scratch
  • Tool Break

With Scratches causing most of our quality issues reducing this would help improve our overall production. But is this the right thing to focus on? We have to clean after every shift and it is unlikely that we can eliminate this step. So let’s look at some additional detail.

Scrap Details by Reason

In this table we can see 3 things:

  1. Number of times a scrap reason occurred
  2. Average number of scrapped parts per entry
  3. Total number of scrapped parts by reason code.

We can also see the trend of each reason code, are we producing more scrap or less over time.

Scrap by Shift

We can also look at scrap by shift and reason code to determine if one shift has more scrap than another. From the graph you can see that 3rd shift has more rejected parts that 2nd or 1st. There may be a training opportunity to improve quality.

Scrap Trends

SensrTrx allows you to track trends in your data allowing you to see over time how your plant is running. Using trends, you can easily see the effect of process or system changes over the long term. You can also notice when scrap is increasing or decreasing and quickly take action to resolve the issues.

Scrap Alerts

Using SensrTrx users can easily setup alerts when scrap is higher than normal. These alerts can notify any employee that can benefit from this information, maintenance, supervisors or the operator of a line.

SensrTrx Improves Manufacturing Quality

SensrTrx allows manufacturing companies to collect and analyze data in a way that was not possible a few years ago. Companies no longer have to rely on paper, Microsoft Excel or clunky ERP systems to analyze data from the plant floor.

Schedule or view a Live Demo Today and see how SensrTrx can help you.