Abstract (EN):
Improving on-site productivity and increasing the mechanisation of tasks is one of the construction industry's main challenges. A craft-workforce motion productivity framework was conceptualised and established nine processes to map and measure on-site performance, being composed of: i) Free-hand performing, ii) Auxiliary tools, iii) Manual tools, iv) Electric/Electronic tools, v) Machines operation, vi) Robotic automation, vii) Do not operating value, viii) Walking, ix) Carrying. An experiment was conducted to model masonry activity in residential and commercial sites. A work sampling methodology was conducted to collect data and test the proposed framework's feasibility. Through human observation, randomly performed, the sample was stratified according to the pre-established framework. The activities include laying individual masonry units (expanded clay blocks 400x190x200mm) with horizontal and vertical joints in mortar. Only the brickwork was analysed (without coatings). For the observed five working days in the residential building worksite, 198 square meters of masonry were carried out, undertaking 145 labour-hours, achieving a rating of 0.73 labour-hours/m2. In the same period, conducting the work sampling methodology, 3,484 observation points were made about the crew performance. Also, for the commercial building worksite, at five working days, 242 square meters of masonry, undertaking 158 labour-hours, achieving a rate of 0.65 labour-hours/m2. With a total of 3,606 observations made about the processes. Resulting of the masonry processes modelled for each site indicate that most activities performed concern manual tools and free-hand performing. Finally, the comparative analysis between different worksites regarding masonry tasks allows the evaluation of the processes. It identifies characteristics that can be better adapted to enhance production and increase mechanisation levels. Modelling process methods can lead to measures to standardise the crew's activities and improve productivity. © 2024, University of Cantabria - Building Technology R&D Group. All rights reserved.
Language:
English
Type (Professor's evaluation):
Scientific
No. of pages:
7