To quality professionals, the challenge “So prove it!” is far more than a school yard taunt, since their organizations must continually demonstrate to customers, board members, suppliers, associations, regulatory bodies, and others that their products or services indeed meet the quality standards that they espouse. In the food industry, this ability may be especially elusive, since recalls, bacterial intrusions, package weights, storage, and other issues represent such a broad range of possibilities for failure in quality as reported to consumers, who are especially alert to safety and quality issues in the food they eat.
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So how does a food producer—even one that is following strict standards for its products—manage to show that it is indeed doing so? In an age when every advertisement and TV commercial touts product quality, the word has lost its meaning to many. Nonetheless, being able to demonstrate the meaning of quality in food products is not only important, but often required.
This is where tools come in. Among those that are useful in offering proof of quality performance are:
- Process behavior, Shewhart, or control charts;
- Statistical process control;
- Measurement systems analysis;
- Gage calibration management; and
- Process capability analysis.
Of course the specific tools that are important vary by industry and customer needs. Hospitals, for example, might want to analyze wait times in the Emergency Department, while an ice cream manufacturer may measure the number of chocolate chips in its mint chocolate chip flavor. Each process may be different, but all demand attention to stable systems that produce quality products and services. Food production and distribution depends on unique and diverse processes, from measurement of ingredients to production, labeling, and packaging.
The type of proof that is required also depends upon the consumer of the information. If you manufacture automotive parts, your customer might require a Cpk with the part you ship. A quality auditor might require a calibration history for a gage, and an expectant mother might want to see how C-section rates at a local hospital compare to those nationwide. Food producers serve customers at both wholesale and retail levels, and require a number of diverse metrics to show that their products are safe and represent quality.
Regulations or standards set by FDA and the Food Safety Modernization Act, or FSMA, may require information about the condition of a measurement system. Calibration records for gages and other measurement devices demand the use of different tools from that of training records for employees.
Among available tools, in brief, are the following.
Control charts, known as process behavior charts or Shewhart charts, demonstrate the predictability of a process by charting data to indicate its stability. Packages of chocolate candy will have normal distribution in the number of pieces per package, but data that falls outside control limits signals an issue that must be addressed in order to maintain consistency.
Statistical process control is used to analyze and interpret data so that areas to improve become apparent. It may involve collecting data on fill rates in food packaging, for example, or incidents of food-borne pathogens in output. Any process can be measured, analyzed, and improved.
Measurement systems analysis is a method for determining if a measurement system is capable of measuring differences among the units produced by a process. If scales are used to measure packaging units, these scales demand accuracy and consistency in their calibration. Gage calibration management is fundamental to doing good business in any organization that uses physical equipment to measure its product or service.
Capability analysis is a set of calculations used to assess whether a system is statistically able to meet a set of specifications or requirements. This simple statistical tool will eliminate headaches when processes fail to meet unrealistic expectations.