Cannabis Gummy Recipe Management
While working with a company on their Tanis Gummy Candy production line to track OEE and implement production scheduling, we also learned they were having problems with operator-entered setpoints resulting in wildly incorrect product formulations. One particular instance involved an ingredient addition which was three orders of magnitude larger than intended. The operator meant to enter a number that was less than 10 grams, and instead entered the number in kilograms, causing 10,000x more of that ingredient to be added. This single mistake caused hundreds of thousands of dollars in lost revenue.
As part of our overall Ignition integration, we decided to implement the Sepasoft Recipe Module to create and manage recipes on a per product basis. It would also monitor for deviations in real-time to alert operators to any mis-entered setpoints.
Recipe Management Solution
Sepasoft Recipe Management Module
PostgreSQL Database
Implementation Summary
We have successfully implemented the Sepasoft Recipe Module many times in the past, including for food and beverage companies like Blommer Chocolate. We feel that the benefits of the Sepasoft Recipe Module far outweigh its cost as a robust, production-tested module.
We performed a fairly straightforward implementation of the Sepasoft Recipe Module. We set up the Tanis production line in the production model, added every piece of equipment, created tags for the various setpoints, and created a recipe template for the line. Then, we reviewed the client’s product database and imported all of their existing recipes into a PostgreSQL database. Next, we rolled out our standard Sepasoft Recipe Management screens. These screens provide users with the ability to view, edit, and manage recipes. We have designed a built-in screen to scan or enter a work order number, select the appropriate product and recipe, then load everything to the system to start the batch. Once the recipe is loaded into the system, all of the setpoints are automatically set to the correct values. If the operators make any changes while the batch is running, a variance alert is generated. We configured the variance alerts as alarms which are sent out as notifications to the operator and the shift supervisor.
Results
Adding the Sepasoft Recipe Module to this project removed a lot of potential for operator error. It also completely removed the potential for unseen operator error. If there was a deviance from the recipe, ESPECIALLY if it was on the order of 10,000x out of bounds, then everyone would know immediately. Before, they would only know about the error after waiting for quality control to test the product.
While this was a relatively simple integration without a lot of moving pieces, it provided peace of mind for the client. It is also saving them from scrapping batches due to operator error now and in the future.
