Application of queuing theory: A decision support model for construction companies in the implementation of 3D printing

Zhang, X (2019) Application of queuing theory: A decision support model for construction companies in the implementation of 3D printing. PhD thesis, University of Florida, USA.

Abstract

The application of three-dimensional (3D) printing is a heated discussion in the construction industry. The automatic and accurate printing process not only helps reduce manpower and waste but also increases the productivity and project quality in construction. However, the high capital cost is the main barrier to adopting this new technology for companies in this cost-sensitive industry. Forecasting the performance of 3D printing during the design phase can support companies’ decision making on the issue. In this research, a stochastic model was developed to simulate the implementation of 3D printing in on-site and off-site construction. This paper first identifies the influential factors in the two different construction modes. By assuming the arrival of projects using Poisson distribution and the time interval between projects using a negative exponential distribution, a project stream generator for construction companies was developed based on queuing theory. The Excel Visual Basic programming language was adopted to execute the iteration of a Monte Carlo simulation. Data collected from precast concrete parking structure projects were used as the baseline of sensitivity analysis. Then, a sensitivity analysis was conducted to help the companies select the optimal construction strategies in different situations. By using the baseline value as the input of the model, the significant factors were identified as the number of printers, the number of projects, and the duration of printers’ remobilization and the insensitive factors were the duration of components’ transportation, variance of components’ erection and variance of components’ manufacturing hours. Further research will consider economic performance of 3D printers and uncertainties in the two modes.

Item Type: Thesis (Doctoral)
Thesis advisor: Flood, I
Uncontrolled Keywords: decision support; duration; precast concrete; decision making; forecasting; manpower; manufacturing; off-site construction; productivity; programming; Monte Carlo simulation; simulation
Index terms: productivity, Monte Carlo simulation, variance, new technology, forecasting, construction industry, duration, off-site construction, implementation, design phase, precast concrete, strategy, construction company, sensitivity analysis, decision support, capital cost, 3D printing, decision-making, influential factor, stream, programming
Subjects: accounting and finance, environmental hazards, building construction, programming, manufacturing, organization, innovation and technology management, professional practice, contractual arrangements, water management, management, industry analysis, project controls, decision analysis, measurement and scaling, risk assessment, prediction and forecasting, building materials, modelling and simulation
Topics: Time Control, Digital Applications, Design Practice, Construction Technology, Business Strategy, Construction Materials, Research Practice, Risk Management, Sustainability, Procurement, Engineering Principles
Descriptive scope: 4 PCTA

N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here