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Abstract

The cost estimation at the pre-project stage provides an important decision-making indicator for the future of the project. With a preliminary cost estimation, project participants can make financial decisions and cost control. The aim of this paper is to propose a model for estimating the costs of facade systems before the pre-design stage, using the GAM (Generalized Additive Model) method. The commonly used method for the valuation of facade systems is based on individual calculation. Such valuation process is complicated and time consuming. For this reason the search for a new forecasting method is justified. The database developed for modelling purposes includes 61 cases of real costs of system façade execution for public buildings. Each case is described by 16 parameters (namely, input variables). The average absolute percentage error (MAPE) was used to assess the model, which takes the value of 14,26% for the generalized model with a logarithmic binding function and 11.77% for the model with an identity binding function. On the basis of the studies and the results obtained, it can be concluded that the constructed model is useful and can improve the process of forecasting system façade costs at the pre-projection stage.
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Bibliography


[1] D. A. Aczel, “Statystyka w Zarządzaniu”, Wydawnictwo Naukowe PWN, 2017.
[2] H. Anysz, „Managing Delays in Construction Projects Aiming at Cost Overrun Minimization”, In IOP Conference Series: Materials Science and Engineering, Vol. 603, No. 3, 2004, 2019. https://doi.org/10.1088/1757-899X/603/3/032004
[3] A. Belusic, I. Herceg-Bulic, Z. Bencetic Klaic, “Using a generalized additive model to quantify the influence of local meterology on air quality in Zagreb”, Geofizyka, Vol. 32, No. 5, pp. 47–77, 2015. https://doi.org/10.15233/gfz.2015.32.5
[4] K. Coussement, D. F. Benoit, D. Van den Poel, “Improved marketing decision making in a customer churn prediction context using generalized additive models”, Expert Systems with Applications, Vol. 37, No. 3, pp. 2132–2143, 2009.
[5] M. S. El-Abbasy, t. Zayed, “Generic scheduling optimization model for multiple construction projects”, Journal of computing in civil engineering, Vol. 31, No. 4, 04017003, 2017. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000659
[6] M. Górka, „Use of aluminium and glass facades in urban architecture”, Budownictwo i Architektura, Vol. 18, No. 3, pp. 29–40, 2019. https://doi.org/10.35784/bud-arch.586
[7] T. J. Hastii, R. J. Tibshirani, „Generalized Additive Models”, Chapman & Hall/CRC Monographs on Statistics & Applied Probability, 1990.
[8] M. Juszczyk, “Residential buildings conceptual cost estimates with the use of support vector regression”, In MATEC Web of Conferences, Vol. 196, 04090, 2018.
[9] M. Juszczyk, K. Zima, W. Lelek, „Forecasting of sports fields construction costs aided by ensembles of neural networks”, Journal of Civil Engineering and Management, Vol. 25, No. 7, pp. 715–729, 2019. https://doi.org/10.3846/jcem.2019.10534
[10] P. Kamble, N. Sanadi, “Optimization of Time and Cost of Building Construction using Fast Tracking Method of Scheduling”, Optimization, Vol. 6, No. 07, 2019.
[11] O. Kapliński, “Problematyka inżynierii przedsięwzięć budowlanych na konferencjach krynickich 2017 i 2018”, Przegląd Budowlany, 89, 2018.
[12] T. Kasprowicz, „Inżynieria przedsięwzięć budowlanych. Metody i modele w Inżynierii przedsięwzięć budowlanych”, Pr. zb. pod red. Kapliński Oleg, PAN KILiW, IPPT, 2007.
[13] M. Kozlovska, M. Spisakova, D. Mackova, „Identifying the construction waste types relating to modern methods of construction”, Book Series: International Multidisciplinary Scientific GeoConference SGEM, pp. 129–136, 2016. https://doi.org/10.5593/SGEM2016/B62/S26.018
[14] M. Krzemiński, “Optimization of work schedules executed using the flow shop model, assuming multitasking performed by work crews”, Archives of Civil Engineering, Vol. 63, No. 4, pp. 3–19, 2017. https://doi.org/10.1515/ace-2017-0037
[15] A. Kylili, P.A. Fokaides, “Policy trends for the sustainability assessment of construction materials: A review”, Sustainable Cities and Society, Vol. 35, pp. 280–288, 2017. https://doi.org/10.1016/j.scs.2017.08.013
[16] A. Leśniak, M. Górka, “Analysis of the cost structure of aluminum and glass facades”, In Advances and Trends in Engineering Sciences and Technologies III: Proceedings of the 3rd International Conference on Engineering Sciences and Technologies (ESaT 2018), CRC Press, 445, 2019. https://doi.org/10.1201/9780429021596-70
[17] A. Leśniak, M. Górka, D. Wieczorek, „Identification of factors shaping tender prices for lightweight”, Scientific Review Engineering and Environmental Sciences, Vol. 2, pp. 171–182, 2019. https://doi.org/10.22630/PNIKS.2019.28.2.16
[18] A. Leśniak, F. Janowiec. “Risk Assessment of Additional Works in Railway Construction Investments Using the Bayes Network”, Sustainability, Vol. 11, No. 19, pp. 53–88, 2019. https://doi.org/10.3390/su11195388
[19] A. Leśniak, M. Juszczyk, “Prediction of site overhead costs with the use of artificial neural network based model”, Archives of Civil and Mechanical Engineering, Vol. 18, No. 3, pp. 973–982, 2018. https://doi.org/10.1016/j.acme.2018.01.014
[20] A. Leśniak, M. Juszczyk, G. Piskorz, „Modelling Delays in Bridge Construction Projects Based on the Logit and Probit Regression”, Archives of Civil Engineering, Vol. 65, No. 2, pp. 107–120, 2019. http://doi.org/10.2478/ace-2019-0022
[21] A. Leśniak, K. Zima, „Cost calculation of construction projects including sustainability factors using the Case Based Reasoning (CBR) method”, Sustainability, Vol. 10, No. 5, 1608, 2018. https://doi.org/10.3390/su10051608
[22] P. Mccullagh, J.A. Nelder, “Generalized Linear models”, Chapman and Hall, 1989.
[23] M. Mrówczyńska, M. Sztubecka, M. Skiba, A. Bazan-Krzywoszańska, P. Bejga, „The Use of Artificial Intelligence as a Tool Supporting Sustainable Development Local Policy”, Sustainbility, Vol. 11, No. 15, 4199, 2019. https://doi.org/10.3390/su11154199
[24] T. Nivea, T. Anu V, “Regression modelling for prediction of construction cost and duration”, In: Applied Mechanics and Materials. Trans Tech Publications, pp. 195–199, 2017. https://doi.org/10.4028/www.scientific.net/AMM.857.195
[25] B. Nowogońska, J. Korentz, “Value of Technical Wear and Costs of Restoring Performance Characteristics to Residential Buildings”, Buildings, Vol. 10, No. 1, pp. 2075–5309, 2020. https://doi.org/10.3390/buildings10010009
[26] A. Oke, C. Aigbavboa, E. Dlamini, “Factors Affecting Quality of Construction Projects in Swazilland”, In Conference: Conference: 9th International Conference on Construction in the 21st Century, At Dubai, UAE, 2017.
[27] A. Panwar, K.N. Jha, “A many-objective optimization model for construction scheduling”, Construction management and economics, Vo. 37, No. 12, pp. 727–739, 2019. https://doi.org/10.1080/01446193.2019.1590615
[28] Z. Rachid, B. Toufik, B. Mohammed, “Causes of schedule delays in construction projects in Algeria”, International Journal of Construction Management, Vol. 19, No. 5, pp. 371–381, 2019. https://doi.org/10.1080/15623599.2018.1435234
[29] M. Rogalska, “Prognozowanie rzeczywistego zużycia mieszanki betonowej do wykonania ścian szczelinowych metodą uogólnionych modeli addytywnych GAM”, Materiały Budowalne, Vol. 6, pp. 88–89, 2016.
[30] M. Rogalska, „Wieloczynnikowe modele w prognozowaniu czasu procesów budowlanych”, Politechnika Lubelska, 2016. https://doi.org/10.15199/33.2016.06.38
[31] M. Rogalska, P. Wolski, „Prognozowanie ceny 1m2 mieszkania na rynku pierwotnym w warszawie metodą uogólnionych modeli addytywnych”, Logistyka, Vol. 6, pp. 9101–9110, 2014.
[32] M. Saeedi, “Study the Effects of Constructions New Techniques and Technologies on Time, Cost and Quality of Construction Projects from the Perspective of Construction Management”, Journal of Civil Engineering and Materials Application, Vol. 1, No. 2, pp. 61–76, 2017.
[33] S.S. Shaikh, M.M. Darade, “Key performance indicator for measuring and improving quality of construction projects”, International Research Journal of Engineering and Technology (IRJET), Vol. 4, No. 5, pp. 2133–2139, 2017.
[34] D. Skorupka, A. Duchaczek, M. Kowacka, P. Zagrodnik, „Quantification of geodetic risk factors occurring at the construction project preparation stage”, Archives of Civil Engineering, Vol. 64, No. 3, pp. 195–200, 2018. https://doi.org/10.2478/ace-2018-0039
[35] M. Sztubecka, M. Skiba, M. Mrówczyńska, A. Bazan-Krzywoszańska, „An Innovative Decision Support System to Improve the Energy Efficiency of Buildings in Urban Areas”, Remote Sensing, Vol. 12, No. 2, 259, 2020. https://doi.org/10.3390/rs12020259
[36] Y. Wang, B. Yu, J. Wei, F. Li, „Direct numerical simulation on drag-reducing flow by polymer additives using a spring-dumbbell model”, Progress in Computational Fliud Dynamics, an International Journal, Vol. 9, 2009. https://doi.org/10.1504/PCFD.2009.024822
[37] D. Wieczorek, E. Plebankiewicz, K. Zima, „Model estimation of the whole life cost of a building with respect to risk factors”, Technological and Economic Development of Economy, Vol. 25 No. 1, pp. 20–38, 2019. https://doi.org/10.3846/tede.2019.7455
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Authors and Affiliations

Agnieszka Leśniak
1
ORCID: ORCID
Monika Górka
1
ORCID: ORCID

  1. Cracow University of Technology, Faculty of Civil Engineering, Institute, 24 Warszawska street, 31-155 Cracow, Poland
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Abstract

Cost estimation in the pre-design phase both for the contractor as well as the investor is an important aspect from the point of view of budget planning for a construction project. Constantly growing commercial market, especially the one of public utility constructions, makes the contractor, at the stage of development the design concept, initially estimate the cost of the facade, e.g. office buildings, commercial buildings, etc., which are most often implemented in the form of aluminum-glass facades or ventilated elevations. The valuation of facade systems is of an individual calculation nature, which makes the process complicated, time-consuming, and requiring a high cost estimation work. The authors suggest using a model for estimating the cost of facade systems with the use of statistical methods based on multiple and stepwise regression. The data base used to form statistical models is the result of quantitative-qualitative research of the design and cost documentation of completed public facilities. Basing on the obtained information, the factors that shape the costs of construction façade systems were identified; which then constitute the input variables to the suggested cost estimation models.

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Authors and Affiliations

Agnieszka Leśniak
ORCID: ORCID
Damian Wieczorek
ORCID: ORCID
Monika Górka
ORCID: ORCID
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Abstract

This research aimed to investigate the water vapour transmission properties of chosen EPDM membranes applied in façade and window systems under laboratory tests. The applied procedure included in national and international standards utilized for the laboratory tests of water vapour transmission properties of EPDMmembrane is described. Two main types (outside and inside types) ofEPDMmembranes are laboratory tested. The authors indicated that the EPDM membranes should differ in surface factures. Nevertheless, some manufacturers mark EPDM membranes on each roll (on the package only) without different permanent denotations on the EPDM membranes surfaces. This form of denotations can cause using problems – using the wrong types of the EPDM aprons in building partitions, because when the package is removed there is impossible to visually identify the type of EPDM membrane (outside or inside type) from the texture of the membrane surface. The experimental results of laboratory tests indicated using the wrong type of EPDM membrane in the inside aprons in building partitions in the investigated façade window system. The designed proportion of the sd values (the resistance to movement of water vapour) of inside and out-side EPDM façade membranes should be designed equally to about 3.0 (recommended value 4) to provide proper diffusion properties of partitions around windows in façade systems. The paper can provide scientists, engineers, and designers an experimental basis in the field of the EPDM membranes water vapour transmission properties applied to façades and windows systems.
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Authors and Affiliations

Andrzej Ambroziak
1
ORCID: ORCID
Sławomir Dobrowolski
1
ORCID: ORCID

  1. Gdansk University of Technology, Faculty of Civil and Environmental Engineering, St.Gabriela Narutowicza 11/12, 80-233 Gdańsk, Poland

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