scholarly journals Integration of Feedstock Assembly System and Cellulosic Ethanol Conversion Models to Analyze Bioenergy System Performance

Author(s):  
Jared Abodeely ◽  
Doug McCorkle ◽  
Kenneth Bryden ◽  
David Muth ◽  
Daniel Wendt ◽  
...  
2013 ◽  
Vol 769 ◽  
pp. 350-358 ◽  
Author(s):  
Matthias Glonegger ◽  
Wolfgang Ottmann ◽  
Markus Schadl ◽  
Dominic Distel

Increasing demands on the flexibility of assembly workers lead to numerous times of high exposure rates within one shift. Inflexible processing times in synchronised assembly lines mismatch individual, circadian variable work capacities of operators. As a result, frequent performance peaks due to limited possibilities for individualisation elevate physiological and psychological workloads. The main objective of this paper is an individualisation of assembly system performance requirements. The conceptual framework presented gives the opportunity to specify diurnal assembly system performance requirements by recording and evaluating current processing times. The authors focus on the definition of demands on selecting a workstation, on raw data as well as on time measurement. Subsequently, a methodical approach to record current processing times as well as statistical data processing is presented. Moreover, the application of the presented method leads to an analysis of one representative workstation of a German car manufacturer’s engine assembly. Based on this, the authors define the production rhythm for this workstation and deduce statements on how to adapt the production system to current performance levels preventing physiological and psychological deterioration of assembly employees.


2018 ◽  
Vol 48 (7) ◽  
pp. 653-661 ◽  
Author(s):  
Le Chen ◽  
Ji-Liang Du ◽  
Yong-Jia Zhan ◽  
Jian-An Li ◽  
Ran-Ran Zuo ◽  
...  

2013 ◽  
Vol 312 ◽  
pp. 899-903
Author(s):  
Shu Feng Chai ◽  
Su Jun Luo ◽  
Xue Ling Zhang

Building the model of assembly system in virtual environment, analyzing and evaluating assembly system performance by use of system simulating technology, can optimize parameter and configuration of assembly system ahead of production plan in order to optimize production process and improve production efficiency. An example is given to illustrate the process of modeling and simulating the engine assembly system based on the FactoryPrograms software.


Author(s):  
Paulo Peças ◽  
João Semeano

Assembly cells often depend on the human elements when an extended automation is not (economically, even if technologically) possible. The workers’ natural variability is impossible to avoid in a manual assembly system. Usually when simulating an assembly system, a given task time distribution is assumed as the representation of the workers time performance. Workers have variations in their performance that can incur in the shifting of this distribution relative to the expected performance time distribution, as well as in the widening of this distribution, by the increase or decrease of dispersion. This paper presents a discrete event simulation model of an assembly system where the operators have different time distributions, aiming to assess their influence in the overall system performance. Those time distributions were obtained in industrial context, in a previous study, by observing workers in an assembly cell, so representing real performance of workers. The results indicate that the worst performing worker will “pace” the output system performance to a slower rhythm, while better performances of a single worker will only increase very slightly the system productivity.


2014 ◽  
Vol 945-949 ◽  
pp. 3136-3142
Author(s):  
Li Min Zhao

To support aircraft assembly system analysis and optimization, a producing performance analysis method for assembly unit is proposed on aircraft assembly system in this paper. The stochastic volatility characteristics of assembly system are firstly analyzed, and the equivalent transformations method for the analysis of system performance is studied, to study the factors which contribute to system performance, including operation experience and out-of-tolerance. A method for solving the system resource utilization is proposed based on identified probability density function. A formula to calculate the average productivity of the system is derived, and system performance boundaries are calculated based on flow balance principle. Finally, a method for the calculation of balancing factors of assembly operation units is proposed.


1960 ◽  
Author(s):  
S. Seidenstein ◽  
R. Chernikoff ◽  
F. V. Taylor

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