A “must-have” packing weight variation control technique

Imagine you are buying a few bags of potato chips to snack on. One bag has fewer chips than expected; the chips do not match the weight mentioned on the package. You will be disappointed. You will either complain to the manufacturer or simply stop trusting the brand. Worse, you could take to social media to express your anger, affecting the broader reputation of the brand. If there are a few extra chips in the bag, you will not mind it. But those extra chips can quickly add up to massive losses for the manufacturer. Either way, not controlling the grammage of products leads to unwelcome outcomes. This is not a new problem for the F&B industry. But new solutions are now available to contain and practically eliminate-the problem.

Variances in packaged food products is expected. The manufacturer of a 78 g bag of potato chips can perhaps tolerate a variance of +/- 2 grams. But by identifying the actual variance and tracking trends, upstream and downstream systems can be improved, costs can be lowered, compliance norms can be met, waste reduced and customers kept happy by offering a more consistent product. However, usually individual checkweigher or multi head weighers and baggers are used at the packaging stage to accept/reject products for the market—when it can be too late. To overcome this, the science of Extra Grammage (EGA) Optimization needs to be mastered.

The weight of packaged food products is a tricky affair. Something as simple as extra moisture in the chips or extra oil can increase the weight. The thickness of input materials (for example, potato slices, masala or salt deposition etc. ) or even the temperature of the cooking oil or frying time can cause higher or lower weights, or the vibratory nature of the manufacturing equipment can lead to variances.   

Often the selling price of a product cannot be changed. In such cases the manufacturer must resort to controlling the weight.

EGA optimization is a latest Industry 4.0 solution integrates all weigher “Machine Data” & “Process Parameters” and where continuously monitors the trend of Underweight & Overweight Rejections and Extra Give Away of Materials.  Then Auto-Insights are generated basis factual data at frequent intervals, minute level & KPIs are measured EGA%, rejections% etc. and any deviations beyond acceptable limits are alerted to respective operators to fix the production parameters causing the variance immediately, minimizing the volume of rejected products at the end of the line. The solution works for both linear and vertical manufacturing and packaging processes. 

Vertical manufacturing and packaging processes need to be dealt with a little differently from linear processes (example: potato chips versus cookies). In a vertical process, the product drop happens to multiple buckets during production. The weight may vary because of product breakage or due to residual recipe material, accumulated in the assembly line, sticking to the product.

In current practice, many CPG companies have not integrated their Machine data. Right set of Analytics not used to create meaningful alerts for operators and to improve output quality. Our implementation of this solution in a large food production plant has shown significant results, that even a 1% impact is saving thousands of dollars. But this is what production plant managers will like to hear the most: ROI in our implementation was less than six months. This is a high-impact, quick-return intervention that every manufacturer must consider.