Tool Development for Life Cycle Cost (LCC) of Wooden Building Envelope


  • Roja Modaresi Senior Researcher
  • Magnus Olai Landaas Consultant



life-cycle-cost; service life, decay, above the ground, moisture, species, detailing, orientation, UV effect


The main goal of this study is to provide a platform for LCC calculation rules for timber buildings that comply with the Standards EN 16627:2015 and EN 15643-4, by employing a refined technical service life estimation. The database includes economic data for the building envelope and structural elements at the product level. In addition, the use phase of the building is included as maintenance, and the relevant economic data related to design failure, user preferences, and technical defects due to moisture. This model is under development as part of the WoodLCC project, with partners from Germany, Sweden, Norway, Estonia, Slovenia, and Austria, aiming to implement advanced methods to calculate accurate technical service life estimations and give the users the opportunity to evaluate the differences in building and maintenance costs based on different parameters.

In this study, a data structure is created based on the necessary indicators and parameters for LCC calculation. An Excel model is developed, which will be used as a base for a software development in the WoodLCC project. Only wooden material is being considered for building envelope and bearing system. All material price data and installation times for each element is taken from a Norwegian dataset. This data is then modified for the selected European country using country specific labour cost- and material cost-indexes, convertible to the inquired currency. Inflation and escalation rates are considered for calculating the maintenance or repair that will occur in future. Material prices for different species and modification are included.     

Improved service life input data will enable more precise LCC for wood-based products, resulting in improved economic impact. LCC finds common acceptance only if reliable input data are available and complemented with knowledge about user expectations. We will evaluate the possibility of future improvements of such models.