Potential applications of the CCS/BM method in the scheduling of continuous LSM (Linear Scheduling Model) construction activities are considered. The effect of time buffers – feeding buffers (FB) and project buffers (PB) – on total project realisation time (TT) is examined. Feeding buffers are found to have no direct full influence on TT if construction activities continuity is assumed. The influence of FBs on TT for other conditions considered in this paper still needs to be examined. Laiko atsargos statybos procesų kalendoriniame planavime Santrauka Straipsnyje nagrinėjamos CCS/BM metodo pritaikymo galimybės nepertraukiamo LSM (grafinio linijinio modelio) statybos procesų kalendoriniam planavimui. Tikrinama laiko atsargų, tokių kaip laiko atsargos pasirengti (FB) ir laiko atsargos projektui baigti (PB), įtaka projekto trukmei (TT). Nustatyta, kad laiko atsargos pasirengti neturi tiesioginės įtakos projekto trukmei, jeigu daroma prielaida, kad statybos procesai yra nepertraukiami. Esant kitoms straipsnyje aptariamoms sąlygoms, pasirengimo laiko atsargų (FB) poveikį bendrajai projekto trukmei (TT) reikėtų patikrinti. Reikšminiai žodžiai: kritinė procesų seka, laiko atsargos, grafinis linijinis modelis. First Published Online: 14 Oct 2010 Keyword : critical chain, time buffers, Linear Scheduling Model

Complex construction projects require appropriate planning that allows for time and cost optimization, maximization of the use of available resources and appropriate investment control. Scheduling is a complicated process, due to the uncertainties and risks associated with construction works, the paper describes the development of the scheduling method traditionally used in Poland, based on data from KNR catalogs, by using the RiskyProject Professional program. In the RiskyProject Professional program, the risk and uncertainty with reference to a specific construction project were modeled, and the calculation results were compared with the real time of the project implementation. The conclusions from the work carried out confirm that the SRA (Schedule Risk Analysis) analysis of the base schedule allows for a more faithful representation of the actual conditions of a construction project. The probability of investment realization generated on the basis of the SRA analysis may be assumed at the level of 75÷90%.

Asymmetry of employee productivity is an important issue when planning production work. Estimated time to complete the work depends on many factors, such as employee experience, qualifications, and efficiency of brigades and subcontractors, accidents, unreliable suppliers, material shortages, the need for correction work, fatigue, stress, etc. The paper presents the statistical method—Multivariate Method of Statistical Models—MMSM. It enables the assessment of the impact on the duration of works of its characteristic variables and the prediction of the duration of individual orders. In order to carry out the multi-criteria method (MMSM) analysis, the employees’ working time was measured at the newly opened steel structure production plant in Kielce. The results of the analyses clearly show that thanks to the method used, quick and accurate prediction of employees’ work efficiency is possible. In the analyzed case, the best forecast was obtained using the method of automatic neural networks, where the MAPE error = 0.02%.

The paper evaluates the relationship between the selection of the probability density function and the construction price, and the price of the building's life cycle, in relation to the deterministic cost estimate in terms of the minimum, mean, and maximum. The deterministic cost estimates were made based on the minimum, mean, and maximum prices: labor rates, indirect costs, profit, and the cost of equipment and materials. The net construction prices received were given different probability density distributions based on the minimum, mean, and maximum values. Twelve kinds of probability distributions were used: triangular, normal, lognormal, beta pert, gamma, beta, exponential, Laplace, Cauchy, Gumbel, Rayleigh, and uniform. The results of calculations with the event probability from 5 to 95% were subjected to the statistical comparative analysis. The dependencies between the results of calculations were determined, for which different probability density distributions of price factors were assumed. A certain price level was assigned to specific distributions in 6 groups based on the t-test. It was shown that each of the distributions analyzed is suitable for use, however, it has consequences in the form of a final result. The lowest final price is obtained using the gamma distribution, the highest is obtained by the beta distribution, beta pert, normal, and uniform.

Worker absenteeism is identified as the greatest threat to not meeting the completion date of a construction project. The purpose of this paper is to quantify the impact of employee absenteeism risk on the probabilistic lead time of a construction project. Calculations of employee absenteeism risk values were performed using data from the Central Statistical Office (Big Data). Probabilistic schedules with probability density functions (Normal, Exponential, Reyleigh, Triangle, Gamma, Cauchy) with and without calculated employee absenteeism risk were prepared. Student’s t-test and MAPE analysis of mean absolute percentage errors were performed to determine differences between groups. It was found that with respect to the probability of completing the task in the range of 75 to 95% for all functions, an unacceptable MAPE error of 32.82% to 69.23% arises. Therefore, the authors postulate that the risk of worker absenteeism should be considered in every construction process when performing probabilistic scheduling, i.e., in the Building Information Modeling BIM methodology.

Effective planning is crucial in the construction sector to ensure projects are completed on time and on budget. However, the construction industry faces various challenges that can complicate the planning process. There are often delays, exceedances of the baseline and increases in investment costs. One planning method is Time Couplings Methods (TCM), which can be improved using predictive multivariate statistical model method (MMSM) construction process times and standard deviations. A new scheduling method in the probabilistic approach was developed – Probabilistic Time Couplings Method II (PTCM II). In PTCM II, the priority is to maintain the continuity of work on working sectors, because sector downtime is unfavorable and extends the investment implementation time. The work presents a case study and compares it with other planning methods and with the real time of the considered investment. he results clearly indicate that the developed methodology is correct, provides good mapping and can be successfully used in planning construction works.