Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
A simulation-based decision-making framework for construction supply chain management (SCM)
https://orcid.org/http://orcid.org/0000-0002-5460-8623
The conventional economic order quantity (EOQ) model used for calculating re-order point in construction material procurement cycle is fundamentally limited by the assumed constant lead time. In real construction scenario, the lead time is hardly ever constant. This study uses a PERT-based simulation model to calculate optimum re-order point and order size with an objective of minimizing the average inventory level and downtime due to non-availability of material. The simulation is run on the STROBOSCOPE simulation framework developed by the researchers at the University of Michigan. The duration data collected from a construction project are used to model each step of the procurement process. The results from the simulation are analyzed to study the relationships between order size, re-order point, average inventory level and work–idle time. A decision-making framework is proposed to choose the optimum order size and re-order point (minimum inventory threshold) for efficient use of storage space and minimum idling.
A simulation-based decision-making framework for construction supply chain management (SCM)
https://orcid.org/http://orcid.org/0000-0002-5460-8623
The conventional economic order quantity (EOQ) model used for calculating re-order point in construction material procurement cycle is fundamentally limited by the assumed constant lead time. In real construction scenario, the lead time is hardly ever constant. This study uses a PERT-based simulation model to calculate optimum re-order point and order size with an objective of minimizing the average inventory level and downtime due to non-availability of material. The simulation is run on the STROBOSCOPE simulation framework developed by the researchers at the University of Michigan. The duration data collected from a construction project are used to model each step of the procurement process. The results from the simulation are analyzed to study the relationships between order size, re-order point, average inventory level and work–idle time. A decision-making framework is proposed to choose the optimum order size and re-order point (minimum inventory threshold) for efficient use of storage space and minimum idling.
A simulation-based decision-making framework for construction supply chain management (SCM)
https://orcid.org/http://orcid.org/0000-0002-5460-8623
The conventional economic order quantity (EOQ) model used for calculating re-order point in construction material procurement cycle is fundamentally limited by the assumed constant lead time. In real construction scenario, the lead time is hardly ever constant. This study uses a PERT-based simulation model to calculate optimum re-order point and order size with an objective of minimizing the average inventory level and downtime due to non-availability of material. The simulation is run on the STROBOSCOPE simulation framework developed by the researchers at the University of Michigan. The duration data collected from a construction project are used to model each step of the procurement process. The results from the simulation are analyzed to study the relationships between order size, re-order point, average inventory level and work–idle time. A decision-making framework is proposed to choose the optimum order size and re-order point (minimum inventory threshold) for efficient use of storage space and minimum idling.
A simulation-based decision-making framework for construction supply chain management (SCM)
Asian J Civ Eng
Kulkarni, Ajinkya (Autor:in) / Halder, Srijeet (Autor:in)
Asian Journal of Civil Engineering ; 21 ; 229-241
01.03.2020
13 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
A simulation-based decision-making framework for construction supply chain management (SCM)
| Online Contents | 2019
Agent-Based Simulation Framework for Supply Chain Management of Large-Scale Construction Projects
| British Library Conference Proceedings | 2017
| Taylor & Francis Verlag | 2020
Innovative decision support model for construction supply chain performance management
| BASE | 2020