The Development of the Complete X-Factor Contribution Measurement for Improving Cycle Time and Cycle Time Variability

2006 ◽  
Vol 19 (3) ◽  
pp. 352-362 ◽  
Author(s):  
D. Delp ◽  
J. Si ◽  
J.W. Fowler
Keyword(s):  
Cycle Time ◽  
Time Variability ◽  
Factor Contribution

Effective Cycle Time: A Real World Balancing Index for Paced Assembly Lines

2010 ◽  
Vol 14 (5) ◽  
pp. 431-441
Author(s):  
Konstantinos N. Genikomsakis ◽  
◽  
Vassilios D. Tourassis
Keyword(s):  
Performance Measures ◽  
Cycle Time ◽  
Assembly Line ◽  
Assembly Line Balancing ◽  
Line Balancing ◽  
Research Trend ◽  
Time Variability ◽  
Assembly Lines ◽  
Simulation Experiments

Assembly Line Balancing (ALB) aims at optimally assigning the work elements required to assemble a product to an ordered sequence of workstations, while satisfying precedence constraints. Notwithstanding the advances and developments in ALB over the years, recent and thorough surveys on this field reveal that only a small percentage of companies employ ALB procedures to configure their assembly lines. This paradox may be attributed, to some extent, to the fact that ALB is addressed mostly under ideal conditions. Despite the time variability inherent in manufacturing tasks, there is a strong research trend towards designing and implementing algorithms that consider ALB on a deterministic basis and focus on the optimality of the proposed task assignments according to existing ALB performance measures. In this paper, the need to assess the performance of the proposed solutions of various algorithms in the literature is corroborated through simulation experiments on a benchmark ALB problem under more realistic conditions. A novel ALB index, namely the Effective Cycle Time, ECT, is proposed to assess the quality of alternative assembly line configurations in paced assembly lines operating under task times variations.

Cycle-Time Reduction in Machining by Recursive Constraint Bounding

1997 ◽  
Vol 119 (2) ◽  
pp. 201-207 ◽  
Author(s):  
R. Ivester ◽  
K. Danai ◽  
S. Malkin
Keyword(s):  
Cycle Time ◽  
Process Models ◽  
Process Time ◽  
Time Variability ◽  
Optimal Conditions ◽  
Modeling Uncertainty ◽  
Confidence Levels ◽  
Part Quality ◽  
Control Optimization ◽  
Process Feedback

Modeling uncertainty in machining, caused by modeling inaccuracy, noise and process time-variability due to tool wear, hinders application of traditional optimization to minimize cost or production time. Process time-variability can be overcome by adaptive control optimization (ACO) to improve machine settings in reference to process feedback so as to satisfy constraints associated with part quality and machine capability. However, ACO systems rely on process models to define the optimal conditions, so they are still affected by modeling inaccuracy and noise. This paper presents the method of Recursive Constraint Bounding (RCB2) which is designed to cope with modeling uncertainty as well as process time-variability. RCB2 uses a model, similar to other ACO methods. However, it considers confidence levels and noise buffers to account for degrees of inaccuracy and randomness associated with each modeled constraint. RCB2 assesses optimality by measuring the slack in individual constraints after each part is completed (cycle), and then redefines the constraints to yield more aggressive machine settings for the next cycle. The application of RCB2 is demonstrated here in reducing cycle-time for internal cylindrical plunge grinding.

Lean Manufacturing and Cycle Time Variability Analysis for Factory Automation Using Simulation Tools

2008 ◽  
Author(s):  
Ricardo Andrecioli ◽  
Y. J. Lin
Keyword(s):  
Cycle Time ◽  
Lean Manufacturing ◽  
Time Variability ◽  
Manufacturing Processes ◽  
Factory Automation ◽  
Simulation Tools ◽  
Manufacturing Automation ◽  
Variability Analysis ◽  
Manufacturing Cell ◽  
Optimization Function

This paper presents the influence of cycle time variation and number of kanban cards on the throughput of manufacturing cell supported by simulation tools. The ultimate goal of the work is for attaining factory automation. Based on this analysis the paper will introduce the concept of “Moving Bottleneck”. We also propose an optimization function to enable manufacturing processes optimization outcomes by employing the proposed function. The results show that the analysis performed and methodology proposed are effective tools towards lean factory manufacturing automation.

Pragmatic Approach for Assembly Lines Selection Based on Discrete-Event Simulation

2013 ◽  
Vol 13 (3) ◽  
pp. 165-176
Author(s):  
Paulo Peças ◽  
Raquel Folgado ◽  
Elsa Henriques
Keyword(s):  
Discrete Event Simulation ◽  
Cycle Time ◽  
Assembly Line ◽  
Discrete Event ◽  
Assembly Line Balancing ◽  
Simulation Software ◽  
Time Variability ◽  
Assembly Lines ◽  
Pragmatic Approach ◽  
Event Simulation

AbstractThis paper presents a pragmatic approach to the study of the influence of tasks time variability in the performance of linear and parallel assembly lines. Discrete event simulation is used to assess the performance of several configurations for two assembly line balancing problems, and for four different levels of time variability. From the simulation studies, a set of equations were developed allowing the prediction of the assembly line performance, measured by the cycle time for common ALBPs, with considerable accuracy. These equations show the interactions between the sum of average task times, the balancing difficulty of the problem and the tasks time variability, as well as the number of workstations and their level of parallelism. With these equations it's possible to reduce the search for the best candidate solutions (number of workstations and level of parallelism) for a given target cycle time, considering the time variability level of the problem. With this approach, the assembly line designer is able to select beforehand the possible feasible solutions in a more practical way when using simulation software.

Neuroticism and Speed-Accuracy Tradeoff in Self-Paced Speeded Mental Addition and Comparison

2010 ◽  
Vol 31 (3) ◽  
pp. 130-137 ◽  
Author(s):  
Hagen C. Flehmig ◽  
Michael B. Steinborn ◽  
Karl Westhoff ◽  
Robert Langner
Keyword(s):  
Reaction Time ◽  
Response Speed ◽  
Time Variability ◽  
Reaction Time Variability ◽  
Comparison Task ◽  
Processing Efficiency ◽  
Mental Addition ◽  
Speed Accuracy ◽  
The Relationship ◽  
Accuracy Tradeoff

Previous research suggests a relationship between neuroticism (N) and the speed-accuracy tradeoff in speeded performance: High-N individuals were observed performing less efficiently than low-N individuals and compensatorily overemphasizing response speed at the expense of accuracy. This study examined N-related performance differences in the serial mental addition and comparison task (SMACT) in 99 individuals, comparing several performance measures (i.e., response speed, accuracy, and variability), retest reliability, and practice effects. N was negatively correlated with mean reaction time but positively correlated with error percentage, indicating that high-N individuals tended to be faster but less accurate in their performance than low-N individuals. The strengthening of the relationship after practice demonstrated the reliability of the findings. There was, however, no relationship between N and distractibility (assessed via measures of reaction time variability). Our main findings are in line with the processing efficiency theory, extending the relationship between N and working style to sustained self-paced speeded mental addition.

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