Analysis of a Serial Production Line with Single Part-Type and Multiple Parallel-Machine Workstations

2014 ◽  
Vol 47 (2) ◽  
pp. 306-313
Author(s):  
Zheng Wang ◽  
Hualing Mu ◽  
Jia You
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.


Author(s):  
Cheng Zhu ◽  
Tian Yu ◽  
Qing Chang ◽  
Jorge Arinez

Abstract In a multistage serial production line, products with defect can be repaired or reworked to ensure high product quality. This paper studies a multistage serial manufacturing system with quality rework loops. Rework is the activity to repair or repeat the work on the defect parts during manufacturing processes, and it adds to cost and cycle time. This paper introduces an event-based data-enabled mathematical model for a stochastic production line with quality rework loops. The system performance properties are analyzed and permanent production loss due to quality rework loops is identified. The mathematical model and system performance identification methodology are studied analytically through numerical case studies.


2014 ◽  
Vol 11 (3) ◽  
pp. 789-797 ◽  
Author(s):  
Michael P. Brundage ◽  
Qing Chang ◽  
Yang Li ◽  
Guoxian Xiao ◽  
Jorge Arinez

Author(s):  
Peng Yang ◽  
Zilong Zhang ◽  
Bingling Cai ◽  
Peng Li ◽  
Yuegang Tao

Author(s):  
Yang Li ◽  
Qing Chang ◽  
Michael P. Brundage ◽  
Guoxian Xiao ◽  
Stephan Biller

Standalone throughput (SAT) of a single station is one of the most widely used performance indexes in industry due to its clear definition, ease of evaluation and the ability to provide a guidance for continuous improvement in production systems. A complex multistage manufacturing system is typically segmented into several subsystems for efficient local management. It is important to evaluate performance of each subsystem to improve overall system productivity. However, the definition of standalone throughput of a production subsystem is not as clear as for a single station in current literatures or in practice, not to say an effective evaluation method. This paper deals with the standalone throughput of a serial production line segment. The definition and implication of standalone throughput of a line segment is discussed. A data driven method is developed based on online production data and is proved analytically under a practical assumption. In addition, the method is verified through simulation case studies to be an accurate and fast estimation of the standalone throughput of a production line segment.


2001 ◽  
Vol 7 (6) ◽  
pp. 543-578 ◽  
Author(s):  
S.-Y. Chiang ◽  
C.-T. Kuo ◽  
S. M. Meerkov

The bottleneck of a production line is a machine that impedes the system performance in the strongest manner. In production lines with the so-called Markovian model of machine reliability, bottlenecks with respect to the downtime, uptime, and the cycle time of the machines can be introduced. The two former have been addressed in recent publications [1] and [2]. The latter is investigated in this paper. Specifically, using a novel aggregation procedure for performance analysis of production lines with Markovian machines having different cycle time, we develop a method for c-bottleneck identification and apply it in a case study to a camshaft production line at an automotive engine plant.


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