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.

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.

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 Modeling Clinical Outcomes in Prostate Cancer: Application and Validation of the Discrete Event Simulation Approach

2018 ◽  
Vol 21 (4) ◽  
pp. 416-422 ◽  
Author(s):  
Feng Pan ◽  
Odette Reifsnider ◽  
Ying Zheng ◽  
Irina Proskorovsky ◽  
Tracy Li ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Clinical Outcomes ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Simulation Approach ◽  
Event Simulation

scholarly journals CONWIP versus POLCA: A comparative analysis in a high-mix, low-volume (HMLV) manufacturing environment

2016 ◽  
Vol 9 (2) ◽  
pp. 432 ◽  
Author(s):  
Todd Frazee ◽  
Charles Standridge
Keyword(s):  
Discrete Event Simulation ◽  
Lead Time ◽  
Manufacturing Systems ◽  
Discrete Event ◽  
Model Verification ◽  
Manufacturing Environment ◽  
Event Simulation ◽  
Work In Process ◽  
Low Volume ◽  
Average Lead

Purpose: Few studies comparing manufacturing control systems as they relate to high-mix, low-volume applications have been reported. This paper compares two strategies, constant work in process (CONWIP) and Paired-cell Overlapping Loops of Cards with Authorization (POLCA), for controlling work in process (WIP) in such a manufacturing environment. Characteristics of each control method are explained in regards to lead time impact and thus, why one may be advantageous over the other.Design/methodology/approach: An industrial system in the Photonics industry is studied. Discrete event simulation is used as the primary tool to compare performance of CONWIP and POLCA controls for the same WIP level with respect to lead time. Model verification and validation are accomplished by comparing historic data to simulation generated data including utilizations. Both deterministic and Poisson distributed order arrivals are considered. Findings: For the system considered in this case study, including order arrival patterns, a POLCA control can outperform a CONWIP parameter in terms of average lead time for a given level of WIP. At higher levels of WIP, the performance of POLCA and CONWIP is equivalent. Practical Implications: The POLCA control helps limit WIP in specific áreas of the system where the CONWIP control only limits the overall WIP in the system. Thus, POLCA can generate acceptably low lead times at lower levels of WIP for conditions equivalent to the HMLV manufacturing systems studied.Originality/value: The study compliments and extends previous studies of  CONWIP and POLCA performance to a HMLV manufacturing environment. It demonstrates the utility of discrete event simulation in that regard. It shows that proper inventory controls in bottleneck áreas of a system can reduce average lead time.

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