The model concept, as presented in this paper, is an original solution created by the author, and can be used as a proposal to build an innovative mechanism to increase the effectiveness of programming and implementation of the development policy, and improve the quality of functioning of a building research institute. The development management system included in this model is a set of actions targeting at the effective use of human and tangible resources, undertaken in a coordinated manner and leading to the achievement of previously established objectives. The market activity of building research institutes is directly or indirectly involved in construction projects, which translates into market mechanisms, such as innovation and competitiveness. In addition, it indicates the participation of a building research institute in the engineering of construction projects as a key to entrepreneurship and implementations.

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.

This article discusses the impact of economic, environmental and legal policies on management of the companies involved in investment projects in the area of industrial construction in Poland. Our empirical research relied on conducting a survey in a group of construction managers and experts. The survey involved 158 Polish companies from the SME sector dealing from the industrial construction. The questionnaire responses were thoroughly analysed and interpreted with the use of a method called exploratory factor analysis (EFA). The results provide an insight into successful management of investment processes realised by construction companies implementing projects in the area of industrial construction. The most important factors identified with the use of this research method turned out to be the availability of technology in a stable political system, stability of economic and tax systems, stable social policy, stability and transparency of the legal system and well-targeted environmental policies. In general, it can be stated that the effective management of industrial construction projects is influenced by the economic, environmental and legal policies of the state.

It is often spoken and written about the use and benefits of BIM in the design, build, and exploitation phases. Based on an extensive analysis of scientific articles and practice, it has been noticed that, however, there is no comprehensive solution for the use of BIM at the stage of preparation for construction. And there is no relevant approach to the organization of construction though various software offers availability to calculate separate processes that are important for the organization of it. For example, based on the BIM model, determine the optimal place for the tower crane. But the problem is that such a local solution does not represent a comprehensive approach and does not represent apprehensive construction planning. It means, currently there is no method of planning, which will answer the questions: whether to choose a tower crane or a truck crane, where is the optimal place for unloading construction materials, considering the location of the crane, etc. Therefore, this article presents the vision and strategy of BIM development at the construction stage. The problem that should be solved now is the creation the strategy that will allow to improve the efficiency of construction works, adjusting them to the current situation in an optimal way. Therefore, the aim of the article is to combine separate ideas of BIM using in construction management as a whole and call scientists to discuss and supplement the topics of using BIM in construction management.

Most scheduling methods used in the construction industry to plan repetitive projects assume that process durations are deterministic. This assumption is acceptable if actions are taken to reduce the impact of random phenomena or if the impact is low. However, construction projects at large are notorious for their susceptibility to the naturally volatile conditions of their implementation. It is unwise to ignore this fact while preparing construction schedules. Repetitive scheduling methods developed so far do respond to many constructionspecific needs, e.g. of smooth resource flow (continuity of work of construction crews) and the continuity of works. The main focus of schedule optimization is minimizing the total time to complete. This means reducing idle time, but idle time may serve as a buffer in case of disruptions. Disruptions just happen and make optimized schedules expire. As process durations are random, the project may be delayed and the crews’ workflow may be severely affected to the detriment of the project budget and profits. For this reason, the authors put forward a novel approach to scheduling repetitive processes. It aims to reduce the probability of missing the deadline and, at the same time, to reduce resource idle time. Discrete simulation is applied to evaluate feasible solutions (sequence of units) in terms of schedule robustness.

The construction contractor is concerned with reducing the cost of the project, including reducing unnecessary downtime. This is achieved when resources are fully utilized; this means the crews work continuously moving without interruption from one location to the other. However, any disturbance in the optimally scheduled workflow caused by random events is likely to result in delays, interruptions in the crews work, and productivity losses. There is therefore a need for scheduling methods that allow plans to be more resilient to disruptions and ensure a reduction in downtime and implementation costs. The authors put forward a proactive-reactive approach to the schedule risk management. Proposed method makes it possible to protect schedule deadlines from the impact of risk factors by allocating time buffers (proactive approach). It also takes into account the measures that managers take during execution in response to delays that occur, such as changing construction methods, employing extra resources, or working overtime (reactive approach). It combines both ideas and is based on project simulation technique. The merits of the proposed approach are illustrated by a case of a repetitive project to erect a number of buildings. The presented example proves that the proposed method enables the planner to estimate the scale of delays of processes’ start and consider the impact of measures to reduce duration of processes in particular locations taken in reaction to delays. Thus, it is possible to determine the optimal schedule, at which the costs of losses associated with delays and downtime are minimal.

It is a usual practice for a contractor to deliver several projects at a time. Typically, the projects involve similar types of works and share the same pool of resources (i.e. construction crews). For this reason, the company’s portfolio of orders considered for a particular planning horizon can be modeled as a project with repeatable processes to be performed in heterogeneous units located in a number of construction sites. Its scheduling requires determining the best sequence of the resources’ moving from unit to unit while minding the due dates related with particular orders as well as resource continuity constraints. The authors present a model of this scheduling problem in the form of a mixed-integer linear program. The aim is to schedule a portfolio of projects in a way that minimizes the total of the resource idle time-related costs, the indirect costs, and the delay penalties. The model can be solved by means of a general-purpose solver. The model is applied to schedule a portfolio of multifamily housing projects.

Duration of construction projects can be reduced by harmonizing construction processes: adjusting productivity rates of specialized crews and enabling the crews to work in parallel as in a production line. This is achievable in the case of projects whose scope can be divided into units where a similar type of work needs to be conducted in the same sequence. A number of repetitive project scheduling methods have been developed to assist the planner in minimizing the execution time and smoothing resource profiles. However, the workflow, especially in construction, is subject to disturbance, and the actual process durations are likely to vary from the as-scheduled ones. The inherent variability of process durations results not only in delays of a particular process in a particular unit but also in the propagation of disruptions throughout the initially well-harmonized schedule. To counteract the negative effects of process duration variability, a number of proactive scheduling methods have been developed. They consist in some form of predicting the conditions to occur in the course of the project and implementing a strategy to mitigate disturbance propagation. This paper puts forward a method of scheduling repetitive heterogeneous processes. The method aims to reduce idle time of crews. It is based on allocating time buffers in the form of breaks between processes conducted within units. The merits of the method are illustrated by an example and assessed in the course of a simulation experiment.