Canary in the mineshaft – the role of process control

09 April 2009

The canary’s untimely death in a mineshaft indicates a dangerous situation, much like HACCP alerts a plant manager of a potential hazard. How did Butterball Turkey Company apply this lesson?

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The most effective way to avoid product hazard is to control the process properly rather than relying on final product inspection. For example, a good HACCP programme cannot depend on microbiological tests as the means to prevent a hazard because they’re too slow to provide the realtime information needed to maintain process control properly.

The problem, however, is most HACCP monitoring systems take an attribute approach to analysing data. Even if variable data are collected to monitor a critical control point the data is typically categorised as “good” (not exceeding the critical limit) or “bad” (exceeding the critical limit). This approach can limit the effective use of variable data by failing to detect process changes over time, where the process control may be deteriorating before a problem manifests itself.

One way to think about the role of process control is to consider the example of the canary in the mineshaft. The canary’s untimely death indicates a dangerous situation in the mineshaft, much like HACCP alerts a plant manager of a potential hazard. Just as ventilating the mineshaft and monitoring the process ensures dangerous conditions can’t arise, so can statistical process control (SPC) in a food processing plant prevent dangerous conditions from happening in the first place.

Food processors can strengthen their HACCP programmes by incorporating concepts of statistical thinking. Statistical thinking is based on the following assumptions – all work occurs in a system of interconnected processes; variation exists in all processes; and understanding and reducing variation are the keys to success.

Recognising the first assumption, conceptualising all work in terms of interconnected processes, ensures a thorough and detailed understanding of the processing system. Next, understanding that every process displays variation as an accepted fact of life prompts analysis of variation. Quality professionals need to know the extent and predictability of process variation.

The final aspect of statistical thinking is the realisation that variation is the enemy and must be reduced or eliminated if a company wants to increase productivity and decrease waste. Quality improvement theory states that the first step of quality improvement is to remove causes of variation by determining and eliminating the root cause of the problem. If only common causes of variation are affecting the process, then the process is operating at the most efficient point for the currently defined system.

An alternative method to analyse HACCP data is to use a two-step evaluation process. During the first step, data taken from the critical control point would be compared to the critical limits to determine whether a potential for a food safety hazard exists.

Next, the data would be analysed using an individual moving range control chart. The control chart allows for a graphical interpretation of the type and extent of variation that affects the process. If a process is capable of meeting critical limits, then it is or could be possible to make adjustments in the process prior to producing unsafe food. In addition, the analysis can provide the means to identify potential opportunities for improvements and increase the capability of the HACCP programme, thus reducing the risk of making unsafe food.

A HACCP programme must be linked to, rather than combined with, other quality systems. Each quality system is designed to accomplish specific objectives; it is important to keep those objectives separate. First and foremost, food processors must provide a safe supply of food. Still, a sound approach to increase the efficacy of the HACCP system is to combine the traditional analysis of data with the use of statistical quality techniques.

Case in point Butterball Turkey Company from Downers Grove, Illinois, has applied this statistical methodology to continually expand and improve its new turkey inspection system. As part of the control system, the company routinely analyses data using control charts. Its process control charts and procedures are designed to identify trends and adjust the process to reduce the risks that defective products are generated.

One example involves selecting carcasses and inspecting them for generic E. coli. This is done to determine whether the birds contain unacceptable levels of E. coli or other bacteria. Carcasses are aseptically sampled at the end of the chill system.

At the end of January, a major manufacturing change was made in a Butterball plant that inadvertently resulted in a slight increase of the E. coli levels of the birds. The level was still below the critical level.

Fortunately, because the process was capable, the problems were identified and a corrective action team comprising plant operations, quality assurance, and maintenance and procurement personnel was formed to identify and remove the problem’s root cause.

As part of the solution, procurement personnel worked closely with the producers to maintain and improve the conditions of the birds coming into the plant. In addition, new chlorinated spray cabinets were added to the processing line after the pickers. Also, the first and final wash cabinets were improved to include a new chlorinating system and higher water pressures. Checks were implemented to control and verify chlorine levels and water pressures. Additionally inspectors were added to the line after the final wash and before the birds entered the chill system.

As a result of these changes E. coli levels dropped rapidly. The average level was lower than the level achieved between 2-21 January and the processes returned to a stable and capable state. This resulted in stabilising the process and regaining statistical process control. Any other time the control chart indicated that the process changed or the data were out of statistical control the causes of the problem were investigated and the problems eliminated.

Butterball has successfully linked the monitoring of control points to statistical process control and the quality improvement processes. This linkage has permitted the development of a highly capable manufacturing process.

As a result, if a change or other factor affects the system, a quality improvement team can identify the root cause of the problem and take corrective and preventive action. This strategy has additional benefits to the company: it increases employee involvement, awareness, attention to detail and motivation, while improving quality and productivity.

Any HACCP programme should be directed to food safety issues. The process is not designed to identify quality enhancement areas, even though well-designed HACCP programmes can enhance the quality of products. Likewise, quality improvement processes can provide a HACCP benefit by reducing the risk of having a food safety hazard.

A process/product improvement project could, for example, centre on reducing the amount of rework. This project may be implemented to increase the productivity and decrease the rework. Specific quality enhancement issues should be addressed through a quality management system such as described in the ISO 9000 standards.