Many construction projects fail to meet deadlines or they exceed the assumed budget. This scenari... more Many construction projects fail to meet deadlines or they exceed the assumed budget. This scenario is particularly common in the case of innovative projects, in which too late identification of a high risk of delays and exceeding the assumed costs makes a potentially profitable project untenable. A high risk level, far exceeding the level of risk in standard non-innovative projects, is a characteristic feature of the realization phase of innovative projects. This is associated not only with greater complexity of the design and construction phases, but also with the problems with application of new technologies and prototype solutions, lack of qualified personnel with suitable expertise in specialized areas, and with the ability to properly identify the gaps between available and required knowledge and skills. This paper discusses the process of effective risk management in innovative projects on the example of the realization phase of an innovative, energy-efficient and sustainable building of the Laboratory of Intelligent Building in Cracow - DLJM Lab, from the point of view of DORBUD S.A., its general contractor. In this paper, a new approach to risk management process for innovative construction projects is proposed. Risk management process was divided into five stages: gathering information, identification of the important unwanted events, first risk assessment, development and choice of risk reaction strategies, assessment of the residual risk after introducing risk reactions. 18 unwanted events in an innovative construction project were identified. The first risk assessment was carried out using two-parametric risk matrix, in which the probability of unwanted event occurrence and its consequences were analysed. Three levels of risks were defined: tolerable, controlled and uncontrolled. Risk reactions to each defined unwanted event were developed. The following risk reaction types were considered: risk retention, risk reduction, risk transfer and risk elimination. Three-parametric risk matrix was developed to make it possible to assess risk after implementing risk reactions. The possibility of implementing risk management was inversely proportional to the probability of unwanted event occurrence and its contribution to the project outcome. Introducing this risk management strategy allowed to significantly reduce the risk of the innovative construction project. It proved to be an effective tool to reduce risk to an acceptable level. It had a significant contribution to carrying out the project within the assumed time, budget and quality standards.
Journal of the Construction Division and Management, May 1, 2020
AbstractNowadays, horizontal directional drilling (HDD) technology is one of the most popular tre... more AbstractNowadays, horizontal directional drilling (HDD) technology is one of the most popular trenchless construction methods for installing pipelines under obstacles. Both risk analysis and risk m...
Scientific Papers of Silesian University of Technology. Organization and Management Series
Purpose: The aim of this paper is to present a new model for risk assessment of unfavorable inter... more Purpose: The aim of this paper is to present a new model for risk assessment of unfavorable interorganizational relationships, among other things, in ventures classified as corporate social responsibility (CSR) projects. Design/methodology/approach: Scenario analysis, brainstorm sessions, literature study and own observations of interorganizational projects were used to develop a list of unwanted events and factors determining their occurrence. In the proposed risk assessment model, fault tree analysis and fuzzy logic were applied for qualitative and quantitative risk analysis. Thanks to applying the elements of fuzzy sets theory, it was possible to decrease the uncertainty and lack of precision in obtaining crisp values of the basic events’ probability. Findings: In this work 13 basic events and 41 risk factors determining occurrence of unfavorable interorganizational relationships in ventures were identified and described. The proposed model enabled to carry out qualitative and qu...
Bearing in mind European Green Deal assumptions regarding a significant reduction of green house ... more Bearing in mind European Green Deal assumptions regarding a significant reduction of green house emissions, electricity generation from Renewable Energy Sources (RES) is more and more important nowadays. Besides this, accurate and reliable electricity generation forecasts from RES are needed for capacity planning, scheduling, managing inertia and frequency response during contingency events. The recent three years have proved that Machine Learning (ML) models are a promising solution for forecasting electricity generation from RES. In this review, the 8-step methodology was used to find and analyze 262 relevant research articles from the Scopus database. Statistic analysis based on eight criteria (ML method used, renewable energy source involved, affiliation location, hybrid model proposed, short term prediction, author name, number of citations, and journal title) was shown. The results indicate that (1) Extreme Learning Machine and ensemble methods were the most popular methods us...
Wooden construction constitutes a specific branch of the building industry that focuses on high-q... more Wooden construction constitutes a specific branch of the building industry that focuses on high-quality materials, a developed sense of aesthetics connected with comfort and functionality, and concern for ecology and durability. This type of construction has a positive effect on human quality of life. This article focuses on modular frame construction and technological aspects of wooden houses built according to Canadian or Scandinavian technologies. Taking weather conditions of Scandinavian countries into consideration, timber is a popular building material, which, when preserving certain parameters such as density of rings, may provide durability of a modular wooden building even up to 200–300 years. This article is a review and presents the possibility of producing frame buildings in Europe (Poland) in accordance with the applicable standards, including a heat transfer coefficient U = 2 [W/(m²·K]. In Poland, wooden frame buildings can be traced back to the 14th century. Wooden fr...
Problems with inaccurate prediction of electricity generation from photovoltaic (PV) farms cause ... more Problems with inaccurate prediction of electricity generation from photovoltaic (PV) farms cause severe operational, technical, and financial risks, which seriously affect both their owners and grid operators. Proper prediction results are required for optimal planning the spinning reserve as well as managing inertia and frequency response in the case of contingency events. In this work, the impact of a number of meteorological parameters on PV electricity generation in Poland was analyzed using the Pearson coefficient. Furthermore, seven machine learning models using Lasso Regression, K–Nearest Neighbours Regression, Support Vector Regression, AdaBoosted Regression Tree, Gradient Boosted Regression Tree, Random Forest Regression, and Artificial Neural Network were developed to predict electricity generation from a 0.7 MW solar PV power plant in Poland. The models were evaluated using determination coefficient (R2), the mean absolute error (MAE), and root mean square error (RMSE). I...
Many construction projects fail to meet deadlines or they exceed the assumed budget. This scenari... more Many construction projects fail to meet deadlines or they exceed the assumed budget. This scenario is particularly common in the case of innovative projects, in which too late identification of a high risk of delays and exceeding the assumed costs makes a potentially profitable project untenable. A high risk level, far exceeding the level of risk in standard non-innovative projects, is a characteristic feature of the realization phase of innovative projects. This is associated not only with greater complexity of the design and construction phases, but also with the problems with application of new technologies and prototype solutions, lack of qualified personnel with suitable expertise in specialized areas, and with the ability to properly identify the gaps between available and required knowledge and skills. This paper discusses the process of effective risk management in innovative projects on the example of the realization phase of an innovative, energy-efficient and sustainable building of the Laboratory of Intelligent Building in Cracow - DLJM Lab, from the point of view of DORBUD S.A., its general contractor. In this paper, a new approach to risk management process for innovative construction projects is proposed. Risk management process was divided into five stages: gathering information, identification of the important unwanted events, first risk assessment, development and choice of risk reaction strategies, assessment of the residual risk after introducing risk reactions. 18 unwanted events in an innovative construction project were identified. The first risk assessment was carried out using two-parametric risk matrix, in which the probability of unwanted event occurrence and its consequences were analysed. Three levels of risks were defined: tolerable, controlled and uncontrolled. Risk reactions to each defined unwanted event were developed. The following risk reaction types were considered: risk retention, risk reduction, risk transfer and risk elimination. Three-parametric risk matrix was developed to make it possible to assess risk after implementing risk reactions. The possibility of implementing risk management was inversely proportional to the probability of unwanted event occurrence and its contribution to the project outcome. Introducing this risk management strategy allowed to significantly reduce the risk of the innovative construction project. It proved to be an effective tool to reduce risk to an acceptable level. It had a significant contribution to carrying out the project within the assumed time, budget and quality standards.
Journal of the Construction Division and Management, May 1, 2020
AbstractNowadays, horizontal directional drilling (HDD) technology is one of the most popular tre... more AbstractNowadays, horizontal directional drilling (HDD) technology is one of the most popular trenchless construction methods for installing pipelines under obstacles. Both risk analysis and risk m...
Scientific Papers of Silesian University of Technology. Organization and Management Series
Purpose: The aim of this paper is to present a new model for risk assessment of unfavorable inter... more Purpose: The aim of this paper is to present a new model for risk assessment of unfavorable interorganizational relationships, among other things, in ventures classified as corporate social responsibility (CSR) projects. Design/methodology/approach: Scenario analysis, brainstorm sessions, literature study and own observations of interorganizational projects were used to develop a list of unwanted events and factors determining their occurrence. In the proposed risk assessment model, fault tree analysis and fuzzy logic were applied for qualitative and quantitative risk analysis. Thanks to applying the elements of fuzzy sets theory, it was possible to decrease the uncertainty and lack of precision in obtaining crisp values of the basic events’ probability. Findings: In this work 13 basic events and 41 risk factors determining occurrence of unfavorable interorganizational relationships in ventures were identified and described. The proposed model enabled to carry out qualitative and qu...
Bearing in mind European Green Deal assumptions regarding a significant reduction of green house ... more Bearing in mind European Green Deal assumptions regarding a significant reduction of green house emissions, electricity generation from Renewable Energy Sources (RES) is more and more important nowadays. Besides this, accurate and reliable electricity generation forecasts from RES are needed for capacity planning, scheduling, managing inertia and frequency response during contingency events. The recent three years have proved that Machine Learning (ML) models are a promising solution for forecasting electricity generation from RES. In this review, the 8-step methodology was used to find and analyze 262 relevant research articles from the Scopus database. Statistic analysis based on eight criteria (ML method used, renewable energy source involved, affiliation location, hybrid model proposed, short term prediction, author name, number of citations, and journal title) was shown. The results indicate that (1) Extreme Learning Machine and ensemble methods were the most popular methods us...
Wooden construction constitutes a specific branch of the building industry that focuses on high-q... more Wooden construction constitutes a specific branch of the building industry that focuses on high-quality materials, a developed sense of aesthetics connected with comfort and functionality, and concern for ecology and durability. This type of construction has a positive effect on human quality of life. This article focuses on modular frame construction and technological aspects of wooden houses built according to Canadian or Scandinavian technologies. Taking weather conditions of Scandinavian countries into consideration, timber is a popular building material, which, when preserving certain parameters such as density of rings, may provide durability of a modular wooden building even up to 200–300 years. This article is a review and presents the possibility of producing frame buildings in Europe (Poland) in accordance with the applicable standards, including a heat transfer coefficient U = 2 [W/(m²·K]. In Poland, wooden frame buildings can be traced back to the 14th century. Wooden fr...
Problems with inaccurate prediction of electricity generation from photovoltaic (PV) farms cause ... more Problems with inaccurate prediction of electricity generation from photovoltaic (PV) farms cause severe operational, technical, and financial risks, which seriously affect both their owners and grid operators. Proper prediction results are required for optimal planning the spinning reserve as well as managing inertia and frequency response in the case of contingency events. In this work, the impact of a number of meteorological parameters on PV electricity generation in Poland was analyzed using the Pearson coefficient. Furthermore, seven machine learning models using Lasso Regression, K–Nearest Neighbours Regression, Support Vector Regression, AdaBoosted Regression Tree, Gradient Boosted Regression Tree, Random Forest Regression, and Artificial Neural Network were developed to predict electricity generation from a 0.7 MW solar PV power plant in Poland. The models were evaluated using determination coefficient (R2), the mean absolute error (MAE), and root mean square error (RMSE). I...
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Papers by Maria Krechowicz