35,970 research outputs found
Using simulation to analyze picker blocking in manual order picking systems
The rise of the e-commerce practice makes the warehouses be confronted with ever smaller orders that must be met ever faster, often within a 24-h period. This pressures the order picking process as the orders pickers' workload becomes higher and higher, leading subsequently to congestion in the warehouse and impacting its productivity. It is therefore crucial to determine which order batching and picking policies enhance the performance of order picking activities. This paper carries out an intensive simulation study to examine the performance of different order picking policies with batching in a wide-aisle warehouse with a low-level picker-to-parts system. The performance of the system is measured in terms of total travelled distance, number of collisions between operators (congestion) and order lead times. A full factorial design is set up and the simulation output is statistically analyzed. The results are reported and thoroughly discussed
Analysis-of-marginal-Tail-Means (ATM): a robust method for discrete black-box optimization
We present a new method, called Analysis-of-marginal-Tail-Means (ATM), for
effective robust optimization of discrete black-box problems. ATM has important
applications to many real-world engineering problems (e.g., manufacturing
optimization, product design, molecular engineering), where the objective to
optimize is black-box and expensive, and the design space is inherently
discrete. One weakness of existing methods is that they are not robust: these
methods perform well under certain assumptions, but yield poor results when
such assumptions (which are difficult to verify in black-box problems) are
violated. ATM addresses this via the use of marginal tail means for
optimization, which combines both rank-based and model-based methods. The
trade-off between rank- and model-based optimization is tuned by first
identifying important main effects and interactions, then finding a good
compromise which best exploits additive structure. By adaptively tuning this
trade-off from data, ATM provides improved robust optimization over existing
methods, particularly in problems with (i) a large number of factors, (ii)
unordered factors, or (iii) experimental noise. We demonstrate the
effectiveness of ATM in simulations and in two real-world engineering problems:
the first on robust parameter design of a circular piston, and the second on
product family design of a thermistor network
The AliEn system, status and perspectives
AliEn is a production environment that implements several components of the
Grid paradigm needed to simulate, reconstruct and analyse HEP data in a
distributed way. The system is built around Open Source components, uses the
Web Services model and standard network protocols to implement the computing
platform that is currently being used to produce and analyse Monte Carlo data
at over 30 sites on four continents. The aim of this paper is to present the
current AliEn architecture and outline its future developments in the light of
emerging standards.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics
(CHEP03), La Jolla, Ca, USA, March 2003, 10 pages, Word, 10 figures. PSN
MOAT00
Libra: An Economy driven Job Scheduling System for Clusters
Clusters of computers have emerged as mainstream parallel and distributed
platforms for high-performance, high-throughput and high-availability
computing. To enable effective resource management on clusters, numerous
cluster managements systems and schedulers have been designed. However, their
focus has essentially been on maximizing CPU performance, but not on improving
the value of utility delivered to the user and quality of services. This paper
presents a new computational economy driven scheduling system called Libra,
which has been designed to support allocation of resources based on the users?
quality of service (QoS) requirements. It is intended to work as an add-on to
the existing queuing and resource management system. The first version has been
implemented as a plugin scheduler to the PBS (Portable Batch System) system.
The scheduler offers market-based economy driven service for managing batch
jobs on clusters by scheduling CPU time according to user utility as determined
by their budget and deadline rather than system performance considerations. The
Libra scheduler ensures that both these constraints are met within an O(n)
run-time. The Libra scheduler has been simulated using the GridSim toolkit to
carry out a detailed performance analysis. Results show that the deadline and
budget based proportional resource allocation strategy improves the utility of
the system and user satisfaction as compared to system-centric scheduling
strategies.Comment: 13 page
Simulation study for investment decisions on the EcoBoost camshaft machining line
Design/redesign of manufacturing systems is a complex, risky, and expensive task. Ford Motor Company’s Valencia Engine Plant faces this challenge as it plans to upgrade its machining and assembly lines to introduce the new EcoBoost engines. The research project described in this paper aimed to support the transition process particularly at the camshaft machining line by using simulation modelling techniques. A series of experiments was carried out using the simulation model developed, and recommendations were proposed based on the results of these experiments to support the decision as to where to invest on the line. The outcomes from the research project indicated that investment is required in terms of increasing the capacity of two bottleneck operations through retooling and improving the conveyor routing logic in one key area.
Keywords: simulation modelling, closed-loop network, automotive production system
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