Simulation Modeling of Milk-Run Internal Logistics System – Case Study

2019 ◽  
pp. 15-26
Author(s):  
Kamila Kluska ◽  
Patrycja Hoffa-Dabrowska ◽  
Anna Zwolankiewicz
Keyword(s):  
Simulation Modeling ◽  
Logistics System ◽  
Milk Run

scholarly journals Lifetime Benefit Analysis of Intelligent Maintenance: Simulation Modeling Approach and Industrial Case Study

2021 ◽  
Vol 11 (8) ◽  
pp. 3487
Author(s):  
Helge Nordal ◽  
Idriss El-Thalji
Keyword(s):  
Simulation Model ◽  
Simulation Modeling ◽  
Study Data ◽  
Opportunistic Maintenance ◽  
Maintenance Strategies ◽  
Modeling Approach ◽  
Intelligent Maintenance ◽  
Diagnosis And Prognosis ◽  
Case Study Data

The introduction of Industry 4.0 is expected to revolutionize current maintenance practices by reaching new levels of predictive (detection, diagnosis, and prognosis processes) and prescriptive maintenance analytics. In general, the new maintenance paradigms (predictive and prescriptive) are often difficult to justify because of their multiple inherent trade-offs and hidden systems causalities. The prediction models, in the literature, can be considered as a “black box” that is missing the links between input data, analysis, and final predictions, which makes the industrial adaptability to such models almost impossible. It is also missing enable modeling deterioration based on loading, or considering technical specifications related to detection, diagnosis, and prognosis, which are all decisive for intelligent maintenance purposes. The purpose and scientific contribution of this paper is to present a novel simulation model that enables estimating the lifetime benefits of an industrial asset when an intelligent maintenance management system is utilized as mixed maintenance strategies and the predictive maintenance (PdM) is leveraged into opportunistic intervals. The multi-method simulation modeling approach combining agent-based modeling with system dynamics is applied with a purposefully selected case study to conceptualize and validate the simulation model. Three maintenance strategies (preventive, corrective, and intelligent) and five different scenarios (case study data, manipulated case study data, offshore and onshore reliability data handbook (OREDA) database, physics-based data, and hybrid) are modeled and simulated for a time period of 20 years (175,200 h). Intelligent maintenance is defined as PdM leveraged in opportunistic maintenance intervals. The results clearly demonstrate the possible lifetime benefits of implementing an intelligent maintenance system into the case study as it enhanced the operational availability by 0.268% and reduced corrective maintenance workload by 459 h or 11%. The multi-method simulation model leverages and shows the effect of the physics-based data (deterioration curves), loading profiles, and detection and prediction levels. It is concluded that implementing intelligent maintenance without an effective predictive horizon of the associated PdM and effective frequency of opportunistic maintenance intervals, does not guarantee the gain of its lifetime benefits. Moreover, the case study maintenance data shall be collected in a complete (no missing data) and more accurate manner (use hours instead of date only) and used to continuously upgrade the failure rates and maintenance times.

Design and Validation of a Simulation-Based Modular Planning and Scheduling System of Semiconductor Fabrication Facilities

2011 ◽  
Vol 48-49 ◽  
pp. 378-381
Author(s):  
Li Li ◽  
Fei Qiao
Keyword(s):  
Simulation Modeling ◽  
General Structure ◽  
Structure Model ◽  
Planning And Scheduling ◽  
Scheduling System ◽  
Information Layer ◽  
Simulation Based ◽  
Semiconductor Fabrication ◽  
Control Modules

A simulation-based modular planning and scheduling system developed for semiconductor fabrication facilities (SFFs) is discussed. Firstly, the general structure model (GSM) for SFFs, composed of a configurable definition layer, a physical layer, a process information layer and a planning and scheduling layer, is proposed. Secondly, a data-based dynamic simulation modeling method is given. Thirdly, a simulation-based modular planning and scheduling system (SMPSS) for SFFs, including model modules, release control modules, scheduling modules and rescheduling modules, is designed and developed. Finally, a case study is used to demonstrate the effectiveness of

scholarly journals Developing an Analytical Solution that Mimics Simulation Modeling for Construction Planning: Earthwork Case

2019 ◽  
pp. 552-562
Author(s):  
Waleed Shakeel ◽  
Ming Lu
Keyword(s):  
Analytical Solution ◽  
Dynamic System ◽  
Simulation Modeling ◽  
High Accuracy ◽  
Analytical Tool ◽  
Controlled Experiments ◽  
Cost Estimating ◽  
Construction Planning ◽  
Using Data

Deriving a reliable earthwork job cost estimate entails analysis of the interaction of numerous variables defined in a highly complex and dynamic system. Using simulation to plan earthwork haul jobs delivers high accuracy in cost estimating. However, given practical limitations of time and expertise, simulation remains prohibitively expensive and rarely applied in the construction field. The development of a pragmatic tool for field applications that would mimic simulation-derived results while consuming less time was thus warranted. In this research, a spreadsheet based analytical tool was developed using data from industry benchmark databases (such as CAT Handbook and RSMeans). Based on a case study, the proposed methodology outperformed commonly used estimating methods and compared closely to the results obtained from simulation in controlled experiments.

Simulation-Based Methodology for Evaluation of High-Occupancy-Vehicle Facilities

1996 ◽  
Vol 1554 (1) ◽  
pp. 90-98
Author(s):  
Dennis E. Sheppard ◽  
K. Larry Head ◽  
Sarath Joshua ◽  
Pitu B. Mirchandani
Keyword(s):  
Metropolitan Area ◽  
Simulation Modeling ◽  
Financial Resources ◽  
Preferential Treatment ◽  
Stochastic Environments ◽  
Design Alternatives ◽  
Simulation Based ◽  
Social Concerns ◽  
The Phoenix

There has been an increasing interest in improving the use of transportation facilities as environmental and social concerns have grown and as financial resources for infrastructure expansion have become increasingly scarce. Numerous programs for increasing carpooling, van-pooling, and transit usage have been undertaken to decrease reliance on single-occupant vehicles and increase the use of multioccupant vehicles. One program has been to develop facilities that give preferential treatment to high-occupancy vehicles (HOVs). Although HOV facilities have been implemented, they often have been found to be unsuccessful in attaining their stated or implied goals. Because interest in the use of HOV facilities is growing, there is a need to improve the ability to evaluate and compare design alternatives in the context of realistic (stochastic) environments. Simulation modeling has long been recognized as a powerful tool for such purposes. A structured simulation-based methodology for the evaluation of HOV design alternatives is presented. An example case study for a corridor in the Phoenix, Arizona, metropolitan area is used to demonstrate the methodology.

Effects of underground logistics system on urban freight traffic: A case study in Shanghai, China

2020 ◽  
Vol 260 ◽  
pp. 121019 ◽  
Author(s):  
Dejun Hai ◽  
Junhong Xu ◽  
Zhengyu Duan ◽  
Chuan Chen
Keyword(s):  
Logistics System ◽  
Urban Freight ◽  
Freight Traffic
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