Sustainable Asset Management system

Besides the investment cost of a cleanroom, the 'running-cost' is especially important. Especially from a sustainability perspective. Every cleanroom designed and built from 2022 onwards is equipped with DAMS. Our sustainable asset management programme includes the following components.CleanConnect energy monitoring provides a clear overview of consumption at any point in time in the cleanroom. A smart algorithm calculates whether the current energy performance matches the theoretically calculated values. Deviations enable effective and energy-efficient energy management in a proactive way. Energy monitoring is more than just measuring and tracking consumption. It is primarily a tool to gain insight into the underlying system in order to use energy more (cost-)efficiently.Prediction about possible failure of underlying components prevents effective failure. By integrating smart algorithms into the continuous monitoring system over the capped data stream, the asset condition is mapped at any time. It is our vision that these smart predictions have a positive sustainable impact, in addition to increasing operational uptime. Preventing failure of costly components prevents unnecessary use of resources.Risk-based spare parts management enables unnecessary relocation and transport costs in addition to a positive economic impact (very low MTTR and high uptime). Using a scientific methodology from "reliability engineering", the cleanroom is mapped as a system with associated subsystems to store each critical component. The methodology used is mainly based on FTA (Fault Tree Analysis) based on the IEC 61025 standard.An integrated maintenance plan carried out by internal ABN service engineers based on the NEN2767 standard should ensure a validated maintenance approach. This methodology makes it possible to obtain a guaranteed asset condition during the life cycle of the cleanroom. During the life cycle, ABN will ensure that the entire cleanroom as a system is always brought to a minimum score of condition 2.