Open AccessBIM-Integrated Simulation of Construction Operations for Lean Production Management
Author(s) -
Soo Chul Chang,
JeongWook Son,
WoonSeong Jeong,
June-Seong Yi
Publication year - 2015
Publication title -
modular and offsite construction (moc) summit proceedings
Language(s) - English
Resource type - Journals
ISSN - 2562-5438
DOI - 10.29173/mocs149
Subject(s) - procurement , productivity , schedule , production (economics) , computer science , plan (archaeology) , supply chain , reliability (semiconductor) , lean manufacturing , simulation modeling , reliability engineering , operations management , engineering , business , history , power (physics) , physics , archaeology , marketing , quantum mechanics , economics , macroeconomics , operating system , microeconomics
As construction projects become larger and more complex, traditional construction planning and control practice which relies on historical data and heuristic adjustment can no longer produce a plan that incorporates all the managerial details such as productivity dynamics. In addition, the plan, more often than not, does not synchronize with the procurement schedule; as a result, the whole supply chain has failed to accomplish expected level of efficiency. In these regards, this paper presents a simulation framework that can not only predict productivity dynamics by considering factors affecting on productivity at the operational level, but also automatically generate a procurement plan harmonizing with the simulation results for reliable production management. We developed APIs for the framework 1) enabling a BIM model to produce input data for the construction operation simulation; 2) composing construction simulation in operational level; 3) facilitating the productivity prediction by providing BIMintegrated construction simulation models. The simulation framework had tested with structural steel erection cases. The results show that we can expect significant improvement of efficiency along supply chain including optimized resource allocation, schedule reliability increase, storage cost saving, and material loss reduction.