Research on Lean Planning and Optimization for Precast Component Production Based on Discrete Event Simulation
Component factories are experiencing the problems associated with lean production, especially the accuracy of production time prediction and the unnecessary waste in terms of time and resource utilization. In order to solve these problems, a discrete event simulation- (DES-) based lean planning and...
Main Authors: | , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2020-01-01
|
Series: | Advances in Civil Engineering |
Online Access: | http://dx.doi.org/10.1155/2020/8814914 |
id |
doaj-a19fc049e8594077baf1136c6ffdbd14 |
---|---|
record_format |
Article |
spelling |
doaj-a19fc049e8594077baf1136c6ffdbd142020-11-25T03:08:41ZengHindawi LimitedAdvances in Civil Engineering1687-80861687-80942020-01-01202010.1155/2020/88149148814914Research on Lean Planning and Optimization for Precast Component Production Based on Discrete Event SimulationZhenmin Yuan0Yaning Qiao1Yaru Guo2Yaowu Wang3Chen Chen4Wenshun Wang5School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Civil Engineering, Harbin Institute of Technology, Harbin 150001, ChinaNantong Prefabricated Buildings and Intelligent Structures Institute, Nantong 226000, ChinaSchool of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaComponent factories are experiencing the problems associated with lean production, especially the accuracy of production time prediction and the unnecessary waste in terms of time and resource utilization. In order to solve these problems, a discrete event simulation- (DES-) based lean planning and optimization method for precast component production is proposed by integrating the complexity assessment (CS), discrete event simulation (DES), and lean management (LM). The method includes three submodels: improved production planning, DES, and lean analysis and optimization. In the submodel of improved production planning, a complexity evaluation index system for precast components is established through investigating five component factories, consulting seven domain experts and analysing relevant literature. In the submodel of DES, the DES technique is adopted to simulate and analyse the production activities of precast components. The submodel of lean analysis and optimization provides multidimensional analysis, comparative analysis, and suggestions. Finally, a detailed production case is selected to simulate and test the proposed method. The important findings are as follows: (1) this method can minimize the difference between the processing time of each workstation to avoid bottleneck stations as much as possible; (2) this method can capture the uncertainty during precast component production, and the most likely production time calculated by the method is 12.05 hours instead of the 11.50 hours originally estimated by the component factory; (3) this method can identify some unnecessary waste in the production process of precast components, including less than 50% utilization of workstations and unnecessary equipment purchases; (4) this method also provides some suggestions regarding production optimization. Due to the particularity of precast component production, it further expands the boundary of lean production methodology from the perspective of the construction industry rather than the manufacturing industry. The proposed method assists component factories in planning and optimizing the precast component production when they make detailed production plans.http://dx.doi.org/10.1155/2020/8814914 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zhenmin Yuan Yaning Qiao Yaru Guo Yaowu Wang Chen Chen Wenshun Wang |
spellingShingle |
Zhenmin Yuan Yaning Qiao Yaru Guo Yaowu Wang Chen Chen Wenshun Wang Research on Lean Planning and Optimization for Precast Component Production Based on Discrete Event Simulation Advances in Civil Engineering |
author_facet |
Zhenmin Yuan Yaning Qiao Yaru Guo Yaowu Wang Chen Chen Wenshun Wang |
author_sort |
Zhenmin Yuan |
title |
Research on Lean Planning and Optimization for Precast Component Production Based on Discrete Event Simulation |
title_short |
Research on Lean Planning and Optimization for Precast Component Production Based on Discrete Event Simulation |
title_full |
Research on Lean Planning and Optimization for Precast Component Production Based on Discrete Event Simulation |
title_fullStr |
Research on Lean Planning and Optimization for Precast Component Production Based on Discrete Event Simulation |
title_full_unstemmed |
Research on Lean Planning and Optimization for Precast Component Production Based on Discrete Event Simulation |
title_sort |
research on lean planning and optimization for precast component production based on discrete event simulation |
publisher |
Hindawi Limited |
series |
Advances in Civil Engineering |
issn |
1687-8086 1687-8094 |
publishDate |
2020-01-01 |
description |
Component factories are experiencing the problems associated with lean production, especially the accuracy of production time prediction and the unnecessary waste in terms of time and resource utilization. In order to solve these problems, a discrete event simulation- (DES-) based lean planning and optimization method for precast component production is proposed by integrating the complexity assessment (CS), discrete event simulation (DES), and lean management (LM). The method includes three submodels: improved production planning, DES, and lean analysis and optimization. In the submodel of improved production planning, a complexity evaluation index system for precast components is established through investigating five component factories, consulting seven domain experts and analysing relevant literature. In the submodel of DES, the DES technique is adopted to simulate and analyse the production activities of precast components. The submodel of lean analysis and optimization provides multidimensional analysis, comparative analysis, and suggestions. Finally, a detailed production case is selected to simulate and test the proposed method. The important findings are as follows: (1) this method can minimize the difference between the processing time of each workstation to avoid bottleneck stations as much as possible; (2) this method can capture the uncertainty during precast component production, and the most likely production time calculated by the method is 12.05 hours instead of the 11.50 hours originally estimated by the component factory; (3) this method can identify some unnecessary waste in the production process of precast components, including less than 50% utilization of workstations and unnecessary equipment purchases; (4) this method also provides some suggestions regarding production optimization. Due to the particularity of precast component production, it further expands the boundary of lean production methodology from the perspective of the construction industry rather than the manufacturing industry. The proposed method assists component factories in planning and optimizing the precast component production when they make detailed production plans. |
url |
http://dx.doi.org/10.1155/2020/8814914 |
work_keys_str_mv |
AT zhenminyuan researchonleanplanningandoptimizationforprecastcomponentproductionbasedondiscreteeventsimulation AT yaningqiao researchonleanplanningandoptimizationforprecastcomponentproductionbasedondiscreteeventsimulation AT yaruguo researchonleanplanningandoptimizationforprecastcomponentproductionbasedondiscreteeventsimulation AT yaowuwang researchonleanplanningandoptimizationforprecastcomponentproductionbasedondiscreteeventsimulation AT chenchen researchonleanplanningandoptimizationforprecastcomponentproductionbasedondiscreteeventsimulation AT wenshunwang researchonleanplanningandoptimizationforprecastcomponentproductionbasedondiscreteeventsimulation |
_version_ |
1715293797204623360 |