Do you collect quality data to catch problems on the production floor—but then never look at that data again? If so, you could be missing an opportunity to reap big rewards from your quality-improvement efforts. A large beverage manufacturing organization discovered that taking their quality data analysis one step further resulted in a top-shelf ROI.
Problem: Seeking the Next Step in Continuous Improvement
Like all beverage makers in today’s competitive marketplace, this world-class spirits manufacturer and bottler needed to save money. The problem was that the distillery had already made extensive cost-cutting efforts—and everything on the production line was running smoothly. From bottle washing to palletizing, all processes were in compliance, product met all the necessary regulations, and customers were happy.
That doesn’t sound like a problem. But as a global leader in their space, the company was interested in continuous improvement
and optimizing processes to stay ahead of the competition. Where could they find a way to improve further on operations that already seemed to be working just fine?
Proposed Solution: Eliminate Waste by Identifying Process Variation
The company decided to install an InfinityQS®
quality intelligence solution, powered by our powerful statistical process control (SPC)
engine, to provide a scientific way to evaluate potential areas for improvement. One of the plant’s many production lines was designated as a pilot.
The line involved multiple processes, so quality data collections were configured at each step:
- Bottle washing: Checked breakage, sanitation, foreign matter, cleanliness, flow rate, and temperature
- Filling (via one rotary filler with 30+ heads): Checked net contents, temperature, foreign matter, and HACCP
- Capping: Checked cap torque and leakage
- Labeling: Checked condition and location
- Packaging: Checked case count and carton verification
- Palletizing: Checked cleanliness and case condition
As expected, all measurements fell within quality control specifications. However, the decision was made to take a closer look at net contents
—a natural focal point for ROI in the food and beverage industries.
In the Filling stage, the quality team pulled and weighed five bottles, at random and from multiple product codes, every half hour. They entered the data into the InfinityQS system and set out to analyze the results.
Result: Quality Data Reveals a Spectacular Opportunity
With the extensive analytic and visual charting capabilities of InfinityQS ProFicient™
, the distillery team was able to dive into the filling process in a way that they could never do using control charts alone. From within one chart, they easily compared:
- Head performance differences
- Shift-to-shift differences
- Product-to-product differences
With this end-to-end vantage point, the team was able to see that although the fill process was measuring within spec, consistent and constant overfilling was causing massive amounts of product waste.
Further research uncovered the systemic issues contributing to this waste. The rotary heads were each filling bottles differently. Because operators had no insight into the reasons for these differences, and because underfilling can lead to severe consequences for beverage manufacturers, the operators were tweaking up the settings a bit—just to be sure that bottles exceeded the lower fill limits.
With this knowledge, the manufacturing engineers were able to perform maintenance on the heads so that they filled more uniformly. The company was also able to conduct team training to help operators optimize procedures and operational consistency across shifts.
The result? Once the distillery reduced in-spec variations
to make fills as uniform, consistent, and identical as possible, they were able to realize savings in excess of $800,000
—on just 1 line of 27
“We had no idea how much we were overfilling,” exclaimed one quality pro. “We just never looked at the data that was in-spec.”
With the help of InfinityQS quality intelligence solutions
, this beverage manufacturer realized that “good enough” simply isn’t good enough. Successful quality management doesn’t stop at quality issues, and just collecting quality data won’t get you where you need to be in the face of today’s extraordinary levels of competition and cost pressures. But when you approach quality as a differentiator, you can find ways to reduce costs and outpace the competition.