Optimizing Your Operations
A mantra for the cannabis extraction business has been: Faster, Better, and Cheaper. Now more than ever extractors require faster access to accurate information. But processes and technologies are becoming increasingly more complex making it difficult to accurately analyze comprehensive data efficiently. It is apparent that organizations that integrate evolving technologies can better optimize performance. And if done well, can perform processes cheaper via process optimization. How can we accomplish this?
Optimization requires blending process improvement into a strategy to identify variables, creating relevant tests, examining the details of the processes, and eliminating conditions that that don’t work and steady improve the product. The THC Safety, Inc. process optimization methodology consists of the following four phases:
Review the extractor manufacturing company literature for the use and suggested optimization of the extraction equipment. Contact the manufacturer and ask to be connected with in-house experts that you may ask for assistance. If possible collaborate with other extraction chemists and review available literature with the goal of identifying the variable that would have the most significant impact on product quality and yield.
Design experiments by selecting the important variables to modify to tune the extraction process, set up experiments for the optimization by guessing the midpoint of a variables range. From the midpoint move up or down approximately 10% – 20% and record the effect. In this manner, you should be able to quickly note whether you should be increasing or decreasing the parameters value. For example; if you believe that the plant matter should have moisture content of between 5 – 10% pick 7% as a starting point then use 6% and 9% to see the impact of the change. Once the initial single variable experiments have been completed multivariable experiments can be designed.
Implement and Document What You Have Learned
It is imperative to record the results of all experiments for present and future reference. The SOP for the process should be a living document that should be modified as new data is generated. In addition separate method of production (MOP’s) documents should be created that do not impact the safety of the operation but contain the most valuable intellectual property (IP). The IP generated is one of the most valuable assets of the operations. This information will allow the company to sustain staff changes (Extraction artist or infusion chefs walk) without losing access to valuable IP and spending months to recapture lost production arts.
Documentation is critical and the information is confidential. The results should be recorded in a method of production that is only available to a select few at the company.
In Practice Challenges
What would you do if confronted with “opportunities” like these?
Your company has just installed a carbon dioxide extraction machine in your facility, the marketing people anticipate big profits but only if a consistent high quality product can be made economically at high yields. The equipment vendor provides a very basic recipe sheet with suggested conditions. Your job is to optimize the process as quickly as possible; with your particular cannabis strains.
A competitor makes an excellent product that commands a premium price. Your sales group wants your product to be able to compete on quality and price. Your job is to fine tune the existing extraction process and get more yields with better product quality.
You probably would first try to gather fellow experts and identify all possible variables that may affect yields and product quality. An exhaustive list might include dozens of potential factors – many more than you could possibly investigate quickly. Some of these variables can’t be controlled: Be sure to record their values. Other variables won’t be given much priority: Hold these at fixed levels. Still, you’re likely to be left with five or more possible control factors.
Now what do you do?
The traditional approach to experimentation requires you to change only one factor at a time However, the approach doesn’t provide data on the interactions of factors, a likely occurrence with chemical processes. You don’t need to run three levels of every factor until you get close to the optimum. An alternative approach restricting the tests to only two levels, you minimize the number doing all combinations of every factor at three levels would produce a prohibitively large number of runs.
Let us design the strategy of experimentation! ….for maximum efficiency!
Some of the likely variables to control
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