Resume

• 1982

  M.S. and Ph.D.

  Civil Engineering Planning and Management

  Automation and Robotics

• 1976

  German

  English

  Slovak

  French

  Russian

  Italian

  Polish

  Master of Engineering (M.Eng.)

  Civil Engineering

• Construction

  Research

  Science

  Analysis

  Management

  Lecturing

  Microsoft Excel

  University Teaching

  Start-ups

  Modeling

  Environmental Awareness

  Statistics

  Higher Education

  Sustainability

  Matlab

  Teaching

  Leadership

  Civil Engineering

  Project Management

  Program Management

  Prospective safety performance evaluation on construction sites

  This paper presents a systematic Structural Equation Modeling (SEM) based approach for Prospective Safety Performance Evaluation (PSPE) on construction sites

  with causal relationships and interactions between enablers and the goals of PSPE taken into account. According to a sample of 450 valid questionnaire surveys from 30 Chinese construction enterprises

  a SEM model with 26 items included for PSPE in the context of Chinese construction industry is established and then verified through the goodness-of-fit test. Three typical types of construction enterprises

  namely the state-owned enterprise

  private enterprise and Sino-foreign joint venture

  are selected as samples to measure the level of safety performance given the enterprise scale

  ownership and business strategy are different. Results provide a full understanding of safety performance practice in the construction industry

  and indicate that the level of overall safety performance situation on working sites is rated at least a level of III (Fair) or above. This phenomenon can be explained that the construction industry has gradually matured with the norms

  and construction enterprises should improve the level of safety performance as not to be eliminated from the government-led construction industry. The differences existing in the safety performance practice regarding different construction enterprise categories are compared and analyzed according to evaluation results. This research provides insights into cause–effect relationships among safety performance factors and goals

  which

  in turn

  can facilitate the improvement of high safety performance in the construction industry.

  Prospective safety performance evaluation on construction sites

  This paper presents a systematic Structural Equation Modeling (SEM) based approach for Prospective Safety Performance Evaluation (PSPE) on construction sites

  with causal relationships and interactions between enablers and the goals of PSPE taken into account. According to a sample of 450 valid questionnaire surveys from 30 Chinese construction enterprises

  a SEM model with 26 items included for PSPE in the context of Chinese construction industry is established and then verified through the goodness-of-fit test. Three typical types of construction enterprises

  namely the state-owned enterprise

  private enterprise and Sino-foreign joint venture

  are selected as samples to measure the level of safety performance given the enterprise scale

  ownership and business strategy are different. Results provide a full understanding of safety performance practice in the construction industry

  and indicate that the level of overall safety performance situation on working sites is rated at least a level of III (Fair) or above. This phenomenon can be explained that the construction industry has gradually matured with the norms

  and construction enterprises should improve the level of safety performance as not to be eliminated from the government-led construction industry. The differences existing in the safety performance practice regarding different construction enterprise categories are compared and analyzed according to evaluation results. This research provides insights into cause–effect relationships among safety performance factors and goals

  which

  in turn

  can facilitate the improvement of high safety performance in the construction industry.

  Prospective safety performance evaluation on construction sites

  Abstract\nThis paper presents a systemic decision support approach for safety risk analysis under uncertainty in tunnel construction. Fuzzy Bayesian Networks (FBN) is used to investigate causal relationships between tunnel-induced damage and its influential variables based upon the risk/hazard mechanism analysis. Aiming to overcome limitations on the current probability estimation

  an expert confidence indicator is proposed to ensure the reliability of the surveyed data for fuzzy probability assessment of basic risk factors. A detailed fuzzy-based inference procedure is developed

  which has a capacity of implementing deductive reasoning

  sensitivity analysis and abductive reasoning. The “3σ criterion” is adopted to calculate the characteristic values of a triangular fuzzy number in the probability fuzzification process

  and the α-weighted valuation method is adopted for defuzzification. The construction safety analysis progress is extended to the entire life cycle of risk-prone events

  including the pre-accident

  during-construction continuous and post-accident control. A typical hazard concerning the tunnel leakage in the construction of Wuhan Yangtze Metro Tunnel in China is presented as a case study

  in order to verify the applicability of the proposed approach. The results demonstrate the feasibility of the proposed approach and its application potential. A comparison of advantages and disadvantages between FBN and fuzzy fault tree analysis (FFTA) as risk analysis tools is also conducted. The proposed approach can be used to provide guidelines for safety analysis and management in construction projects

  and thus increase the likelihood of a successful project in a complex environment.

  Bayesian-network-based safety risk analysis in construction projects

  Mirosław

  Skibniewski

  PSI Pittsburgh Testing Lab Div

  University of Maryland

  University of Maryland

  College Park

  Project Management Program

  Clark School of Engineering

  Purdue University

  Engaged in teaching

  research and educational administration. Served as chief international officer for the institution between 2002 and 2004.

  Purdue University

  Professor

  Teaching and research.

  University of Maryland

  A.J.Clark Chair

  University of Maryland

  College Park

  Project Management Program

  Clark School of Engineering

  PSI Pittsburgh Testing Lab Div

  Greater Pittsburgh Area

  Research Project Engineer