Simulation Support in Construction Uncertainty Management: a Production Modelling Approach

Abstract

The execution of construction projects such as a highway construction or the elevation of a new bridge is a complex, highly equipment-intensive process and are subject to many different uncertainties. This is very similar to the manufacturing execution level in production systems where predefined productions plans and schedules cannot be completely implemented due to unexpected internal and external changes and disturbances. Following this analogy, the paper proposes the application of a discrete-event simulation based method which was already applied in the decision-support for manufacturing control to develop the decision-support in the execution of a construction project where the effects of the deviation from the short-term schedule can be easily and quickly analyzed. Keywords Construction project, simulation, planning and scheduling, disturbance handling, uncertainty management IntroductionThe execution of construction projects such as a highway construction or the elevation of a new bridge is a complex, highly equipment-intensive process and are subject to many different uncertainties (Motawa et al., 2007). Capacity and availability of machinery and human resources, material supply, technology and precedence constraints, geographical and weather conditions are all important aspect in both planning and the execution of a construction project. Planning and scheduling of such projects are done a-priori taking into account the relevant resources, preliminary set-up activities, time, space and precedence constraints, etc. (Hinze, 2011). Nowadays, several different approaches and tools are applied to generate the longer-term plan and shorter-term, detailed schedule(s) of a construction project. The schedules which cover shorter periods like several days or weeks are subject to changes thus new and new schedules are generated on given-period basis (e.g. weekly) taking the finished operations and the new tasks to be performed into consideration. The need for change in the schedule the so-called rescheduling comes from the field manager's level where the monitoring and controlling of real-time construction activities are carried out. The milestones of the project are always kept in the longer-term plan and these plans are only changed if significant delays occur, which danger the achievement of milestones and success of the construction.The aspects enumerated above are analogous with the characteristics of production planning and scheduling and manufacturing shop-floor control, especially of those in project-base manufacturing. In the paper we propose the application of a discrete-event simulation based method which was already applied in the decision-support for manufacturing control. The method addresses the decision-support in the execution of a construction project where the effects of the deviation from the short-term schedule can be easily and quickly analysed.

Decision making in highway construction: a systematic review and future directions

“…Sometimes when discrepancies exist between the actual execution and initial plans, practitioners need to reschedule construction activities. Bohács et al (2016) developed a decision support tool to analyse the impact of deviations in short-term schedules. Other research has developed decision-making techniques to enhance schedule compression (Moselhi and Roofigari-Esfahan, 2013) and reduce unexpected troubles (Bosurgi et al , 2017).…”

Development of an ontology-driven, component based framework for the implementation of adaptiveness in a Jellyfish-type simulation model

“…DES models are extremely popular among researchers as there are many software environments which enable easy model development and implementation of complex operational logic. An example for this can be found in [3], and the model presented in the current paper has also been developed as a DES model. Tako and Robinson give a comprehensive overview and analysis on applicability of both models in the logistics and supply chain context in their paper [29].…”