Performance Evaluation of Kanban-Controlled Line Production Systems with Constant Processing Times

2010 ◽  
Vol 24 (4) ◽  
pp. 183-207
Author(s):  
Hochang Lee ◽  
Seo Dong Won
2007 ◽  
Vol 06 (02) ◽  
pp. 115-128
Author(s):  
SEYED MAHDI HOMAYOUNI ◽  
TANG SAI HONG ◽  
NAPSIAH ISMAIL

Genetic distributed fuzzy (GDF) controllers are proposed for multi-part-type production line. These production systems can produce more than one part type. For these systems, "production rate" and "priority of production" for each part type is determined by production controllers. The GDF controllers have already been applied to single-part-type production systems. The methodology is illustrated and evaluated using a two-part-type production line. For these controllers, genetic algorithm (GA) is used to tune the membership functions (MFs) of GDF. The objective function of the GDF controllers minimizes the surplus level in production line. The results show that GDF controllers can improve the performance of production systems. GDF controllers show their abilities in reducing the backlog level. In production systems in which the backlog has a high penalty or is not allowed, the implementation of GDF controllers is advisable.


2016 ◽  
Vol 39 (3) ◽  
pp. 334-343 ◽  
Author(s):  
Rafal Cupek ◽  
Kamil Folkert ◽  
Marcin Fojcik ◽  
Tomasz Klopot ◽  
Grzegorz Polaków

Classical control applications with a centralized logic and distributed input/output system are being replaced by dynamic environments of cooperating components. Thus, the OPC (Object Linking and Embedding for Process Control) UA (Unified Architecture) is becoming more popular, because the OPC Data Access substandard is not well suited for distributed systems. Moreover, in many production systems, redundant data servers are preferred, for financial and legal reasons. Providing performance evaluation gives an estimate of the time required (and data samples lost) to switch to a backup data source for redundant OPC UA architecture, depending on the failure detection method, number of variables and redundancy mode.


Author(s):  
Andrea Maria Zanchettin

AbstractMotivated by the increasing demand of mass customisation in production systems, this paper proposes a robust and adaptive scheduling and dispatching method for high-mix human-robot collaborative manufacturing facilities. Scheduling and dispatching rules are derived to optimally track the desired production within the mix, while handling uncertainty in job processing times. The sequencing policy is dynamically adjusted by online forecasting the throughput of the facility as a function of the scheduling and dispatching rules. Numerical verification experiments confirm the possibility to accurately track highly variable production requests, despite the uncertainty of the system.


2018 ◽  
Vol 12 (2) ◽  
pp. 233 ◽  
Author(s):  
Farhad Zahedi Hosseini ◽  
Aris A. Syntetos ◽  
Philip A. Scarf

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