scholarly journals A Simulation-Based Decision Support Tool for Arctic Transit Transport

2015 ◽  
Author(s):  
Bernhard Schartmüller ◽  
Aleksandar-Saša Milaković ◽  
Martin Bergström ◽  
Sören Ehlers
Keyword(s):  
Decision Support ◽  
Discrete Event Simulation ◽  
Scale Effects ◽  
Discrete Event ◽  
Open Water ◽  
Decision Support Tool ◽  
Comparative Case Study ◽  
Support Tool ◽  
Event Simulation ◽  
Simulation Based

The Russian Federation attempts to foster the Northern Sea Route (NSR) as a transport alternative to the current Suez Canal Route (SCR). Therefore, this paper seeks to identify under which conditions the use of the NSR is economically feasible. To evaluate this in a realistic way it is essential to take the significant uncertainty of input variables like ice data predictions into account. For that reason a simulation-based decision-support (SBDS)-tool based on a discrete-event simulation model is developed. The SBDS-tool requires as input vessel dimensions, available power and information about the route(s) including waypoints and ice data. It calculates then the general performance of the vessel in both open water and ice. Next it generates day-specific ice conditions according to a probability distribution between lower and upper limit obtained from satellite measurements. Based on this and the previously calculated vessels’ performance the SBDS-tool calculates day-specific transit times and fuel consumptions for examined time period. This is then used as input for a discrete-event simulation to assess the number of roundtrips, transported cargo and fuel consumption for joint use of different routes, dependent on the predefined operational days along the routes. The obtained results are then used to calculate the cost per transported cargo unit between two ports and to assess the sensitivity in order to determine if an economically advantageous and robust transport system can be achieved. In addition, possible economy of scale effects using larger vessels can be evaluated. In order to show the applicability of the developed model a comparative case study for three container vessels operating between Rotterdam (NL) and Yokohama (JP) is carried out.

scholarly journals Framework for Operational Performance Measurements in Small and Medium Scale Industries Using Discrete Event Simulation Approach

2018 ◽  
Vol 8 (4) ◽  
pp. 3103-3107
Author(s):  
B. O. Odedairo ◽  
N. Nwabuokei
Keyword(s):  
Discrete Event Simulation ◽  
Discrete Event ◽  
Decision Support Tool ◽  
Simulation Approach ◽  
Case Scenario ◽  
Worst Case ◽  
Support Tool ◽  
Event Simulation ◽  
Work In Process ◽  
The Status

Globally, production systems must cope with limitations arising from variabilities and complexities due to globalization and technological advancements. To survive in spite of these challenges, critical process measures need to be closely monitored to ensure improved system performance. For production managers, the availability of accurate measurements which depict the status of production activities in real time is desired. This study is designed to develop an operational data decision support tool (ODATA-DST) using discrete event simulation approach. The work-in-process and processing time of each workstation/buffer station in a bottled water production system were investigated. The status of each job as they move through the system was used to simulate a routing matrix. The production output data for 50cl and 75cl product from 2014-2016 were collected. A mathematical model for routing jobs from the point of arrival to the point of departure was developed using discrete event simulation. A graphical user interface (GUI) was designed based on the factory’s performance measurement algorithm. Simulating the factory’s work-in-process with respect to internal benchmarks yielded a cycle time of 4.4, 6.23, 5.04 and throughput of 0.645, 0.455, 0.637 for best case scenario, worst case scenario and practical worst case scenario respectively. The factory performed below the simulated benchmark at 26%, 28%, 28% for the 50cl and at 51%, 54%, 59% for 75cl regarding the year 2014, 2015 and 2017 respectively. Performance measurement decision support tool has been developed to enhance the production manager’s decision making capability. The tool can improve production data analysis and performance predictions.

Automation of input data to discrete event simulation for manufacturing: A review

2016 ◽  
Vol 07 (01) ◽  
pp. 1630001 ◽  
Author(s):  
Panagiotis Barlas ◽  
Cathal Heavey
Keyword(s):  
Discrete Event Simulation ◽  
Input Data ◽  
Manufacturing Industry ◽  
Discrete Event ◽  
Decision Support Tool ◽  
Future Research ◽  
Support Tool ◽  
Event Simulation ◽  
Manufacturing Applications ◽  
The Cost

Discrete event simulation (DES) is a well-established decision support tool in modeling work flows in manufacturing industry. But, there are an amount of practical and financial obstacles that deter the employment of this technology in industry. One of the main weaknesses of operating DES is the costs spent on collecting and mapping input data from different enterprise data resources into a DES model. Another issue is the cost of integrating simulation applications with other manufacturing applications. These barriers hinder the automated input of data into DES models and as a result deter use of real-time DES in manufacturing. This review presents the existing research studies in the literature that address the above issues, demonstrating in parallel the already implemented concepts. The scope of this review is to provide an overview of the input data phase, focusing on its automation and motivating researchers to re-examine this phase by highlighting future research directions.

scholarly journals Simulation-Based Decision Support System to Improve Material Flow of a Textile Company

2021 ◽  
Vol 13 (5) ◽  
pp. 2947
Author(s):  
Vítor Silva ◽  
Luís Pinto Ferreira ◽  
Francisco J. G. Silva ◽  
Benny Tjahjono ◽  
Paulo Ávila
Keyword(s):  
Decision Support ◽  
Material Flow ◽  
Control Strategies ◽  
Decision Support Tool ◽  
Raw Material ◽  
Support Tool ◽  
Point Of Entry ◽  
Work Area ◽  
Simulation Based ◽  
Positive Results

To remain competitive, companies must continuously improve the processes at hand, be they administrative, production, or logistics. The objective of the study described in this paper was to develop a decision-making tool based on a simulation model to support the production of knits and damask fabrics. The tool was used to test different control strategies for material flow, from the raw material warehouse to the finished product warehouse, and thus can also be used to evaluate the impacts of these strategies on the productivity. The data upon which the decision support tool was built were collected from five sectors of the plant: the raw material warehouse, knit production, damask production, finishing work, and the finished product warehouse. The decision support tool met the objectives of the project, with all five strategies developed showing positive results. Knit and damask production rates increased by up to 8% and 44%, respectively, and a reduction of 75% was observed in the waiting time on the point of entry to the finishing work area, compared to the company’s existing system.

Sign in / Sign up

Export Citation Format

Share Document