scholarly journals An Optimization Tool for Production Planning: A Case Study in a Textile Industry

2021 ◽  
Vol 11 (18) ◽  
pp. 8312
Author(s):  
Rodrigo Ferro ◽  
Gabrielly A. Cordeiro ◽  
Robert E. C. Ordóñez ◽  
Ghassan Beydoun ◽  
Nagesh Shukla
Keyword(s):  
Genetic Algorithms ◽  
Production Planning ◽  
Production Scheduling ◽  
Textile Industry ◽  
Discrete Event ◽  
Event Simulation ◽  
Batch Sizing ◽  
Production Problem ◽  
Plant Simulation

The textile industry is an important sector of the Brazilian economy, being considered the fifth largest textile industry in the world. To support further growth and development in this sector, this document proposes a process for production analysis through the use of Discrete Event Simulation (DES) and optimization through genetic algorithms. The focus is on production planning for weaving processes and optimization to help make decisions about batch sizing and production scheduling activities. In addition, the correlations between some current technological trends and their implications for the textile industry are also highlighted. Another important contribution of this study is to detail the use of the commercial software Tecnomatix Plant Simulation 13®, to simulate and optimize a production problem by applying genetic algorithms with real production data.

Improving Casthouse Throughput Using Discrete-Event Modelling

2011 ◽  
Vol 693 ◽  
pp. 3-9 ◽  
Author(s):  
Bruce Gunn ◽  
Yakov Frayman
Keyword(s):  
Sensitivity Analysis ◽  
Discrete Event ◽  
Casting Machine ◽  
Production Data ◽  
Model Output ◽  
Arrival Times ◽  
Event Simulation ◽  
Modelling System ◽  
Key Parameter

The scheduling of metal to different casters in a casthouse is a complicated problem, attempting to find the balance between pot-line, crucible carrier, furnace and casting machine capacity. In this paper, a description will be given of a casthouse modelling system designed to test different scenarios for casthouse design and operation. Using discrete-event simulation, the casthouse model incorporates variable arrival times of metal carriers, crucible movements, caster operation and furnace conditions. Each part of the system is individually modelled and synchronised using a series of signals or semaphores. In addition, an easy to operate user interface allows for the modification of key parameters, and analysis of model output. Results from the model will be presented for a case study, which highlights the effect different parameters have on overall casthouse performance. The case study uses past production data from a casthouse to validate the model outputs, with the aim to perform a sensitivity analysis on the overall system. Along with metal preparation times and caster strip-down/setup, the temperature evolution within the furnaces is one key parameter in determining casthouse performance.

scholarly journals A novel scheduling framework: integrating genetic algorithms and discrete event simulation

2018 ◽  
Vol 17 (1) ◽  
pp. 1 ◽  
Author(s):  
Marco Macchi ◽  
Adalberto Polenghi ◽  
Edoardo Sottoriva ◽  
Luca Fumagalli ◽  
Elisa Negri
Keyword(s):  
Genetic Algorithms ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Event Simulation

Relocation and Storage Assignment Strategies Evaluation in a Multiple-deep Tier-captive Automated Vehicles Storage and Retrieval System with Undetermined Retrieval Sequence

2021 ◽  
Author(s):  
Jakob Marolt ◽  
Nenad Kosanić ◽  
Tone Lerher
Keyword(s):  
Retrieval System ◽  
Discrete Event ◽  
Nearest Neighbour ◽  
Throughput Performance ◽  
Storage And Retrieval ◽  
Event Simulation ◽  
Retrieval Systems ◽  
Storage Assignment ◽  
And Storage

Abstract This paper studies multiple-deep automated vehicle storage and retrieval systems (AVS/RS) known for their high throughput performance and flexibility. Compared to a single-deep system, multiple-deep AVS/RS has a better space area utilisation. However, a relocation cycle occurs, reducing the throughput performance whenever another stock-keeping unit (SKU) blocks a retrieving SKU. The SKU retrieval sequence is undetermined, meaning that the arrangement is unknown, and all SKUs have an equal probability of retrieval. In addition to the shuttle carrier, a satellite vehicle is attached to the shuttle carrier and is used to access storage locations in multiple depths. A discrete event simulation of multiple-deep AVS/RS with a tier captive shuttle carrier was developed. We focused on the dual command cycle time assessment of nine different storage and relocation assignment strategies combinations in the simulation model. The results of a simulation study for (i) Random, (ii) Depth-first and (iii) Nearest neighbour storage and relocation assignment strategies combinations are examined and benchmarked for five different AVS/RS case study configurations with the same number of storage locations. The results display that the fivefold and sixfold deep AVS/RS outperform systems with fewer depths by utilising Depth-first storage and Nearest neighbour relocation assignment strategies.

Applying Discrete Event Simulation (DES) in Healthcare

2015 ◽  
pp. 390-410
Author(s):  
Stavros T. Ponis ◽  
Angelos Delis ◽  
Sotiris P. Gayialis ◽  
Panagiotis Kasimatis ◽  
Joseph Tan
Keyword(s):  
Discrete Event Simulation ◽  
Capacity Planning ◽  
Planning Process ◽  
Discrete Event ◽  
Healthcare Facilities ◽  
Performance Improvements ◽  
Event Simulation ◽  
Health Insurance Provider ◽  
And Performance

This paper highlights the opportunities and challenges of applying Discrete Event Simulation (DES) to support capacity planning of a network of outpatient facilities. Despite an abundance of studies using simulation techniques to examine the operation and performance of outpatient clinics, the problem of capacity allocation and planning of medical services within a network of outpatient healthcare facilities appears to be underexplored. Here, a case study of a health insurance provider that operates a network of six outpatient medical facilities in the US is used to illustrate and explore the synthesizing and adaptive, yet parsimonious nature of using DES methodology for network design and capacity planning. Results of this case study demonstrate that significant performance improvements for the network operator can be achieved with applying DES method to support the network facility capacity planning process.

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