Matrix :: Understanding SPC in the Food Industry to Improve OEE & FSQA

Managing a busy food manufacturing facility is a full-time juggling act of making sure the thousand micro processes going on in your plant are working in harmony. You’re constantly balancing customer demands, supplier deliveries, employee absenteeism, machine downtime and a host of other issues that can flare up and have a significant impact on your production throughput, efficiencies, and quality if (and often when) they do. Progressive producers are turning to SPC in the food industry as part of their overall OEE and FSQA strategies to help detect and correct emerging issues before they have a negative impact on production throughput, equipment effectiveness, and product quality.

What is SPC in the Food Industry?

SPC is not a new concept, nor is SPC in the food industry.

SPC was pioneered almost 100 years ago, in the early 1920’s by Walter A. Shewhart at Bell Laboratories. SPC tracks a variable process attribute and continuously monitors the data for individual exceptions as well as certain longer-term data trends.

Statistical process control data is charted on a control chart, as shown below:

Matrix :: Understanding SPC in the Food Industry to Improve OEE & FSQA

As a very high-level of overview of SPC: The center line in the green zone is the attribute’s target average value. The green zone spans two standard deviations above and below the target center line. The upper and lower yellow zones span one standard deviation each.

Statistically speaking, for a process with a normal distribution, approximately 68% of data falls within one standard deviation of the average value, 95% falls within two standard deviations (the green zone), and 99.7% falls within three standard deviations (the green + yellow zone). Specification limits are often set three standard deviations above and below the average value, on the outer extremes of the yellow zones.

Data is sampled periodically and typically in subgroups of five or more individual data points. While there are many SPC rules that data could be analyzed against, the most common SPC rules are:

  1. Any single data point or subgroup average more than three standard deviations away from the average value (i.e. in either of the red zones)
  2. Two out of three subgroup averages more than two standard deviations above or below the target value (i.e. in one of the yellow zones)
  3. Four out of five subgroup averages more than one standard deviation above or below the average value
  4. Eight consecutive subgroup averages above or below the average value

From the above sampling of rules, you can see that data can be out-of-spec (see the first rule) but a process can also be within specification limits but out of control (see the second through fourth rules). By monitoring for out-of-control data patterns, processes can be adjusted for higher consistency and better overall performance.

SPC goes much, much deeper than the above description describes and often takes years of study to master and tremendous discipline to implement successfully.

SPC in the Food Industry for OEE & FSQA

SPC is not a new concept in the food processing industry. For many years, it has been used to help improve food quality and consistency and to optimize production effectiveness.

Quality control and quality assurance experts use SPC in the food industry to improve product quality and consistency. By sampling and analyzing product attributes they can maintain a high statistical degree of food safety and consistency.

Some of our customers have used Data Navigator’s SPC module to track sliced product package weights, product piece dimensions (length, width & height), internal cooked temperature, topping coverage, and much more.

SPC can also be used to monitor and track machine performance to help improve overall equipment effectiveness (OEE). By using SPC analysis on data collected from a piece of processing equipment, throughput and performance can be optimized to produce OEE gains. Machine attributes such as run time, speed, temperature, pressure, and humidity can all be monitored and validated against SPC rules to improve equipment effectiveness.

Gains made in OEE and FSQA go together when using SPC in the food industry: by producing more consistent product from a FSQA perspective, less spoiled or downgraded product results and OEE metrics improve. By optimizing the operation of production equipment and processes, more consistent, safer, and higher quality product results and FSQA improves.

OEE and FSQA are simultaneous benefits of a focused, disciplined and carefully managed use of SPC in the food industry.

Data Navigator’s SPC Module for the Food Industry

While there are several SPC software packages, few are purpose-built for the food manufacturing industry. One such product is Data Navigator’s SPC module. Initially developed more than 20 years ago, it has adapted to meet the needs of North American food processors in the meat, poultry, dairy, bakery, and seafood industries.

Matrix :: Data Navigator SPC Module User Interface

With operator interface screens down on the plant floor where the production processes are happening, real-time monitoring and alerting, and a full suite of back-office management tools and reporting, it is a great addition to any progressive food manufacturer’s repertoire.

If you’d like to chat with one of our food industry technology experts about how you can use SPC in the food industry to improve product quality, consistency and equipment effectiveness and to learn more about Data Navigator’s SPC module, contact us to chat and let’s set up a time to demo our platform!