A Comparative Analysis of Space Efficiency, Power Consumption, Labor Efficiency, Running Costs, and Carbon Emission

Manual ultra-low temperature freezers pose challenges for sample storage and retrieval. Manual freezers have low energy efficiency, and frequent door openings lead to temperature fluctuations and increased energy consumption as the freezer works harder to maintain the required temperature. This, coupled with the use of refrigerant gases, contributes to a high carbon footprint. Moreover, space within the freezer is often not optimally utilized due to the need for access aisles and the constant rearrangement of samples, leading to wasted space. The manual retrieval process is time-consuming and labor-intensive, requiring researchers to physically locate and remove samples, further slowing down research workflows.

Our model simulates the impact of replacing a large manual ULT freezer collection with an Azenta Life Sciences automated storage and retrieval system. By modeling time, power, space, carbon emissions, and running costs, we demonstrate significant improvements can be obtained in operational efficiency, cost savings, and environmental sustainability by replacing manual sample storage with automation.