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Statistical quality control is a necessary part of modern food processing. The software chosen to satisfy basic food processing SQC needs will determine whether SQC is an awkward, intrusive task or a smoothly operating part of the process. It must not only collect quality data and produce control charts, but also provide those additional capabilities which make it the core of a well run and effective quality system.

The successful implementation of Statistical Quality Control (SQC) begins with the selection of the tools and methods best suited to the company’s quality goals. Because manual charting can be burdensome and time-consuming, PC-based SQC using specialised software is preferable for routine charting and essential for process improvement studies.

Numerous PC-based SQC software packages are readily available. Most, however, were created for discrete manufacturing such as auto parts machining, and consequently are limited in their application for other manufacturers. Food processors evaluating SQC software need to be aware of these shortcomings when making their selection. They need to ask themselves:

Q: Can the software handle both process and laboratory data? Will I be able to select one package to meet the needs of all users?
Q: Can descriptive, measurement, and defect data be viewed in and analysed from the same data file?
Q: Can routine charting tasks be automated to reduce training time?
Q: Is unattended operation possible?
Q: Can charts be configured to precisely meet internal QC needs and still meet customer and regulatory reporting requirements?
Q: Can the software easily collect process data?
Q: Can it accept instrument data?
Q: Can it share or exchange data with corporate or plantwide information systems?
Q: Are the software developers knowledgeable about the issues and special requirements of the food processing industry?

Northwest Analytical, Inc. (NWA) made the needs of the food processing industry a special focus. Because NWA’s development staff understands the needs and challenges faced in implementing SQC in the industry, NWA Quality Analyst is now a world leader in SQC software for food processors. Today, NWA Quality Analyst is used by small independents as well as major multinationals. Their applications range from internal QC and process improvement to vendor certification and regulatory compliance.

Our feature case study looks at a large regional food processor that uses NWA Quality Analyst to monitor quality in their dill pickle packing line. Finished jars of pickles are pulled from the production line for routine data collection and charting. Samples are then drained, weighed, and inspected for defects. Description variables and data as shown below are entered into a Quality Analyst data file. The description variables are used to label routine SQC charts and provide easy reference points for later process improvement studies.

Description variables are as follows: sampling date, stock pickle size being packed and Lot code. Measurement variables are: weight and drained weight of pickles. Defects and counts include: number of pickles per jar,  nubs, crooks, misshapen, broken, mechanical damage, rot, shrivelled, dirty, scarred, incorrect sizing, and hollow.

Note that all the above information is collected at the same time and entered into a single Quality Analyst data set. Charting can then be launched from the data entry screen with push-button ease. In fact, those abilities were significant factors in the processor’s selection of NWA Quality Analyst.

NWA Quality Analyst lets you enter any combination of variable and attribute data into a single file. Charts can be launched from the data editor with a single mouse click.

The full value of Quality Analyst became apparent when the company considered alternate solutions to a potential supply shortage. The company’s SOP (Standard Operating Procedure) for its 46-ounce (filled weight) jar required a “3A” pickle size (1-1/8 in. to 1-1/4 in.) When supplies ran low, the limitation forced a choice between buying more expensive 3A pickles on the open market or changing the SOP to allow use of another stock size, “3B,” 1-1/4 in. to 1-3/8 in. If the weight specification could be maintained, the alternate size would be acceptable. To find out, the company made a trial run using 3Bs. Once again, all data needed to analyse 3A and 3B stock could be entered into a single data file.

The apparent success or failure of using 3B stock would be indicated in a process capability histogram, a chart showing the distribution of pickle weights and their relationship to specifications. First, however, the weights must be analysed using a control chart to verify the packing process was in statistical control.

Labelling regulations allow up to 20 percent variation from the target. The Cpk index, a commonly used numeric representation of the capability of a process, shows both stocks meet production requirements. However, process capability doesn’t always tell the whole story. Another view of the data suggests further analysis is in order. NWA Quality Analyst allows users to easily examine their processes from a variety of perspectives. A routine review of defects using Pareto analysis finds that the defect “broken” had increased during the test run.

For further analysis, the lab produces a p-chart (percent defective SQC chart) and finds two points above the upper control limit. Pattern rule violations, shown on the chart by asterisks, provide further warning. The operator then clicks on each suspect data point to “drill down” for more information. The results pointed to the 3B stock. Using Quality Analyst’s unique Data Filter, separate p-charts for each stock type quickly confirm 3B stock as the source of the unacceptable levels of breakage.

A p-chart (percent defective) revealed significant control problems indicated by out-of-control points and many pattern-rule violations. “Drill down” detail on the out-of-control points identified the offending samples. Shifts in the control limit are automatic adjustments due to changes in the sample size.

Quality Analyst’s Data Filter and multiple chart display demonstrate the contrast in breakage between pickle stocks. Although the 3B stock has a significantly higher breakage rate, it is still in perfect statistical control.

Further study reveals that 3B pickles frequently must be forced into the jar, causing breakage. However, the p-chart shows the process itself to be in statistical control – breakage is a natural part of the process. The processors conclude that while the 3B stock could be used to remain in label weight compliance, breakage may be excessive.

The SQC analysis leads the processors to three key conclusions about their process: 1) They can maintain statistical control and process capability while using either or both pickle stocks. 2) Excessive broken pickles result when using the larger 3B stock. 3) SQC analysis of broken pickles for the 3B stock shows it to be in perfect statistical control; this means the higher breakage rate is characteristic of the process and not due to any “special cause.”

By having a clear understanding of their packing process, the company recognises three distinct choices: 1) Live with the breakage and risk customer displeasure. 2) Continue to study the process to determine if the process can be modified to reduce 3B breakage in a cost-effective manner. 3) Meet shortages by continuing to purchasing 3A stock on the open market.

Quality Analyst software is supplied and supported in the UK and Ireland by Adept Scientific plc, Amor Way, Letchworth, Herts. SG6 1ZA; telephone (01462) 480055, fax (01462) 480213, email quality@adeptscience.co.uk; or see Adept’s World Wide Web site http://www.adeptscience.co.uk/. Adept Scientific is one of the world’s leading suppliers of software and hardware products for research, scientific, engineering and technical applications on desktop computers.

With offices in the UK, USA, Germany and throughout the Nordic region, Adept Scientific is one of the world’s leading suppliers of software and hardware products for research, scientific, engineering and technical applications on desktop computers.