Buffer Size Planning Versus Transfer Line Efficiency

1986 ◽  
Vol 108 (2) ◽  
pp. 105-112 ◽  
Author(s):  
A. Villa ◽  
B. Fassino ◽  
S. Rossetto
Keyword(s):  
Buffer Capacity ◽  
Production Systems ◽  
Design Tool ◽  
Buffer Size ◽  
Planning Problem ◽  
Series Production ◽  
Main Design ◽  
Transfer Line ◽  
Optimal Values ◽  
Buffer Capacities

The paper deals with the main design problem for series production systems, namely the choice of efficiency-optimal values of interstage buffer capacities. It is shown that the design tool must be an accurate dynamic model, able to describe both work station reliability and the couplings among stations (i.e., blocking and starving situations) due to finite storage spaces. By use of this model, the buffer size planning problem can be solved by developing a sensitivity analysis of the model operation modes with respect to buffer capacity values. According to this approach, an analysis of the transfer line efficiency reduction, due to either nonoptimal capacity values or station reliability variations, is also performed.

scholarly journals Using Computer Simulation Method to Improve Throughput of Production Systems by Buffers and Workers Allocation

2015 ◽  
Vol 6 (4) ◽  
pp. 60-69 ◽  
Author(s):  
Sławomir Kłos ◽  
Peter Trebuna
Keyword(s):  
Computer Simulation ◽  
Production System ◽  
Production Systems ◽  
Simulation Method ◽  
System Throughput ◽  
Buffer Allocation ◽  
Simulation Experiments ◽  
Buffer Capacities ◽  
The Relationship ◽  
Support Decision Making

Abstract This paper proposes the application of computer simulation methods to support decision making regarding intermediate buffer allocations in a series-parallel production line. The simulation model of the production system is based on a real example of a manufacturing company working in the automotive industry. Simulation experiments were conducted for different allocations of buffer capacities and different numbers of employees. The production system consists of three technological operations with intermediate buffers between each operation. The technological operations are carried out using machines and every machine can be operated by one worker. Multi-work in the production system is available (one operator operates several machines). On the basis of the simulation experiments, the relationship between system throughput, buffer allocation and the number of employees is analyzed. Increasing the buffer capacity results in an increase in the average product lifespan. Therefore, in the article a new index is proposed that includes the throughput of the manufacturing system and product life span. Simulation experiments were performed for different configurations of technological operations.

Adaptive PPS durch simulationsbasierte Optimierung*/Adaptive PPC by simulation-based optimization

2017 ◽  
Vol 107 (04) ◽  
pp. 288-292
Author(s):  
M. Kück ◽  
J. Ehm ◽  
T. Hildebrandt ◽  
M. Prof. Freitag ◽  
E. M. Prof. Frazzon
Keyword(s):  
Job Shop ◽  
Job Shop Scheduling ◽  
Production Systems ◽  
Semiconductor Industry ◽  
Small Scale ◽  
Planning Problem ◽  
Optimization Approach ◽  
Flexible Production Systems ◽  
Simulation Based ◽  
Simulation Based Optimization

Der Trend zur Fertigung individualisierter Produkte in kleinen Losgrößen erfordert hochflexible Produktionssysteme. Durch die damit verbundene Systemdynamik wird die Reihenfolgeplanung zu einem komplexen Planungsproblem. Der Beitrag beschreibt ein simulationsbasiertes Optimierungsverfahren, welches Echtzeitinformationen zur adaptiven Selektion geeigneter Prioritätsregeln verwendet. Das Potenzial des Ansatzes wird anhand eines Anwendungsfalls aus der Halbleiterindustrie demonstriert.   The trend to manufacturing individualized products in small-scale series demands highly flexible production systems. Because of the dynamic nature of such production systems, scheduling becomes a complex planning problem with frequent need for rescheduling. This article describes a data-driven simulation-based optimization approach using real-time information for adaptive job shop scheduling. The potential of the approach is demonstrated by a use case from semiconductor industry.

The effect of valence and Ionic-strength on the measurement of pH buffer capacity

Soil Research ◽  
1994 ◽  
Vol 32 (5) ◽  
pp. 975 ◽  
Author(s):  
RL Aitken ◽  
PW Moody
Keyword(s):  
Ionic Strength ◽  
Titration Curve ◽  
Buffer Capacity ◽  
Experimental Conditions ◽  
Linear Portion ◽  
Titration Curves ◽  
Addition Rate ◽  
Ph Buffer ◽  
Buffer Capacities ◽  
Linear Regressions

Although the measurement of pH buffer capacity (pHBC) is used to determine lime requirement and acid addition rate in acidification studies, the experimental conditions under which pHBC is determined have not been studied. The effect of valence and ionic strength on the measurement of pHBC was investigated on a range of soils. The effect of the monovalent or divalent accompanying ion was examined by establishing separate titration curves for each of 100 soils by adding incremental amounts of either Ca(OH)2, NaOH, HCl or H2SO4 to soil suspended (1 : 5) in water. Linear regressions were fitted to the linear portion of each titration curve and the slopes of these lines were used as a measure of pHBC. For each soil, the pH buffer capacities were statistically compared. The pHBC determined with Ca(OH)2 was significantly (P = 0.05) greater than that determined with NaOH in 92 soils and, on average (all soils), was 2.2 times the pHBC in NaOH. The effect of ionic strength on pHBC was investigated in each of 20 soils by titrating with HCI in water and suspensions at nominal ionic strengths of 0.006, 0.03 and 0.3 m. In all soils there was a trend for increasing pHBC with increasing ionic strength (I) and, for I < 0.03 m, there was a marked increase in pHBC with increasing I. The results are discussed in relation to the effect of valence and ionic strength on pH buffer capacity mechanisms, and the implications with respect to calculating acidification rates and lime requirements.

Composite stage effects in unbalancing of series production systems

1985 ◽  
Vol 23 (1) ◽  
pp. 1-20 ◽  
Author(s):  
A. MISHRA ◽  
D. ACHARYA ◽  
N. P. RAO ◽  
G. P. SASTRY
Keyword(s):  
Production Systems ◽  
Series Production

scholarly journals Development of Production Simulator for Buffer Size Decisions in Complex Production Systems Using Genetic Algorithm

2007 ◽  
Vol 1 (3) ◽  
pp. 418-429 ◽  
Author(s):  
Jaber ABU QUDEIRI ◽  
Hidehiko YAMAMOTO ◽  
Rizauddin RAMLI ◽  
Khalid R. Al-MOMANI
Keyword(s):  
Genetic Algorithm ◽  
Production Systems ◽  
Buffer Size
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