On average, maintenance costs make up a substantial amount of the expenses of companies. To reduce the overall maintenance costs, future maintenance actions should be avoided and predicted ahead of time.

In the ideal situation where audits are cheap, an expert would conduct a full building audit after which an AI solution would predict the expected future maintenance costs. The maintenance cost prediction for a business property can be based on the current and future costs related to maintenance, the expected frequency of maintenance actions, and information on the assets in the building.

However, in reality, a full audit is very costly, especially for smaller companies. The short-term objective was to improve the current maintenance cost calculations. The long-term objective is to predict the expected maintenance costs for the business property of SMEs without the need for a full audit. 

Omina Technologies reviewed and suggested improvements for the company’s software product that calculates the maintenance cost for a given business property over a horizon of x years based on existing full audit information.

As a next step, an AI predictive maintenance solution could be developed that predicts the business property’s maintenance costs based on the AI-selected number of building characteristics. This would enable SMEs to have an accurate prediction of the maintenance costs even with a partial building audit.

• Correct calculation of the maintenance costs based on full audit information
• Enabling to reduce the building audit costs for SMEs

Having enough full audit data.