Finding the best weigh forward

A common regulatory requirement with consumer products is that the amount of product in the container, on average, should be at least as much as the label on the package states. Since under-filling the container puts the producer at risk with government agencies or customers, producers tend to avoid problems by over-filling. Yet, over-filling can create significant cost problems.

By using statistical process control (SPC) analysis in a continuous monitoring and improvement programme, a company can however reduce over-fill situations and create savings while still meeting the regulations.

Another potential problem with product fill-weight results is when manufacturers use materials pre-measured by their supplier. If the supplier has under or over-filled the container, the buyer may not be using the correct amount of raw material resulting in an end product that does not meet specifications. Again, using SPC a company can optimise its product fill to meet its customer requirements predictably.

Balancing cost and regulations

A large commercial bakery uses three dough-mixing machines for its dinner roll line. When each mixer has prepared its 1,200 pounds of dough, it dumps its batch into a pouring machine, which then pours dough onto baking sheets. Dough for six rolls is poured onto a baking sheet lane with each sheet holding four lanes of rolls. The entire sheet is then baked after which the rolls are cut and packaged in twelve-roll packs.

The pouring machine dispensing dough onto baking sheets until it is empty. It then receives another 1,200 pounds of dough from the next mixing machine in a fixed rotation and begins the pouring process again. Since the bakery labels the package as weighing 454g, all packages are required by to weigh at least 454g.

The bakery’s process engineers conducted a study using SPC with NWA Quality Analyst. The first step was to determine if the dinner roll production process was predictable (this is called ‘in control’). To do this, samples of baked dinner rolls from three lanes were taken every hour on both shifts and weighed. This information was then analysed using an X-Bar/Range chart. As shown in Figure 1, the process was not in control (note all of the points above and below the control limits). These results indicate external factors were influencing the process.

To understand the problem more clearly, the engineers took samples every minute which revealed a pattern – the excessive variation was occurring around every 30 minutes, the time between dough batches from one of the three mixing machines.

Since each dough batch came from a different mixing machine, the engineers analysed the dough from each of the three machines. One machine, Mixer 3, exhibited significantly higher variation in the texture of the dough it produced. Further examination of the texture revealed that the machine was not receiving flour and water in the proportions the bakery’s formula required. Adjustments were made and samples were taken. In Figure 2, the X-Bar/Range chart for the pouring/filling process indicates that the process was still not in perfect control but exhibited much less variability.

At this point, the engineers examined the ‘capability’ of the process; (how predictably the process is producing within specifications). While results showed the process was not capable of consistently producing within these specifications, it did show the process is capable of producing rolls that meet the legal weight requirement predictably as long as the overfill averages 15g.

Engineers must continue to find other external factors influencing the process to make improvements that reduce the over-fill.

Despite the process not being in control at this point, the changes the engineers were able to make during the initial parts of the study to reduce the weight variability in the dinner roll production line saved the bakery approximately $200,000 per year.