Abstract: Communication security is of particular interest to military data networks. A relatively novel approach to network security is blockchain, a cryptographically secured distribution ledger with a decentralized consensus mechanism for data transaction processing. Recent advances in blockchain technology have proposed new techniques for both data validation and trust management, as well as different frameworks for managing dataflow. The purpose of this work is to test the feasibility of different blockchain architectures as applied to military command and control networks. Various architectures are tested through discrete-event simulation and the feasibility is determined based upon a blockchain design’s ability to maintain long-term stable performance at industry standards of throughput, network latency, and security. This work proposes a consortium blockchain architecture with a computationally inexpensive consensus mechanism, one that leverages a Proof-of-Identity (PoI) concept and a reputation management mechanism.
Abstract: In this paper, the flow of different classes of patients
into a hospital is modelled and analyzed by using the queueing
network analyzer (QNA) algorithm and discrete event simulation.
Input data for QNA are the rate and variability parameters of the
arrival and service times in addition to the number of servers in each
facility. Patient flows mostly match real flow for a hospital in Egypt.
Based on the analysis of the waiting times, two approaches are
suggested for improving performance: Separating patients into
service groups, and adopting different service policies for sequencing
patients through hospital units. The separation of a specific group of
patients, with higher performance target, to be served separately from
the rest of patients requiring lower performance target, requires the
same capacity while improves performance for the selected group of
patients with higher target. Besides, it is shown that adopting the
shortest processing time and shortest remaining processing time
service policies among other tested policies would results in,
respectively, 11.47% and 13.75% reduction in average waiting time
relative to first come first served policy.
Abstract: An important number of technological equipment and high-skilled workers over long periods of time have to be mobilized during nuclear decommissioning processes. The related operations generate complex flows of waste and high inventory levels, associated to information flows of heterogeneous types. Taking into account that more than 10 decommissioning operations are on-going in France and about 50 are expected toward 2025: A big challenge is addressed today. The management of decommissioning and dismantling of nuclear installations represents an important part of the nuclear-based energy lifecycle, since it has an environmental impact as well as an important influence on the electricity cost and therefore the price for end-users. Bringing new technologies and new solutions into decommissioning methodologies is thus mandatory to improve the quality, cost and delay efficiency of these operations. The purpose of our project is to improve decommissioning management efficiency by developing a decision-support framework dedicated to plan nuclear facility decommissioning operations and to optimize waste evacuation by means of a logistic approach. The target is to create an easy-to-handle tool capable of i) predicting waste flows and proposing the best decommissioning logistics scenario and ii) managing information during all the steps of the process and following the progress: planning, resources, delays, authorizations, saturation zones, waste volume, etc. In this article we present our results from waste nuclear flows simulation during decommissioning process, including discrete-event simulation supported by FLEXSIM 3-D software. This approach was successfully tested and our works confirms its ability to improve this type of industrial process by identifying the critical points of the chain and optimizing it by identifying improvement actions. This type of simulation, executed before the start of the process operations on the basis of a first conception, allow ‘what-if’ process evaluation and help to ensure quality of the process in an uncertain context. The simulation of nuclear waste flows before evacuation from the site will help reducing the cost and duration of the decommissioning process by optimizing the planning and the use of resources, transitional storage and expensive radioactive waste containers. Additional benefits are expected for the governance system of the waste evacuation since it will enable a shared responsibility of the waste flows.
Abstract: This research tested the performance of alternative
warehouse designs concerning the picking process. The chosen
performance measures were Travel Distance and Total Fulfilment
Time. An explanatory case study was built up around a model
implemented with SIMUL8. Hypotheses were set by selecting
outcomes from the literature survey matching popular empirical
findings. 17.4% reductions were found for Total Fulfilment Time and
Resource Utilisation. The latter was then used as a proxy for
operational efficiency. Literal replication of theoretical data-patterns
was considered as an internal validity sign. Assessing the estimated
changes benefits ahead of implementation was found to be a
contribution to practice.
Abstract: Container handling problems at container terminals
are NP-hard problems. This paper presents an approach using
discrete-event simulation modeling to optimize solution for storage
space allocation problem, taking into account all various interrelated
container terminal handling activities. The proposed approach is
applied on a real case study data of container terminal at Alexandria
port. The computational results show the effectiveness of the
proposed model for optimization of storage space allocation in
container terminal where 54% reduction in containers handling time
in port is achieved.
Abstract: Optimization of business processes in trading companies is reviewed in the report. There is the presentation of the “Wholesale Customer Order Handling Process” business process model applicable for small and medium businesses. It is proposed to apply the algorithm for automation of the customer order processing which will significantly reduce labor costs and time expenditures and increase the profitability of companies. An optimized business process is an element of the information system of accounting of spare parts trading network activity. The considered algorithm may find application in the trading industry as well.
Abstract: Ultra-light overhead conveyor systems are rope-based conveying systems with individually driven vehicles. The vehicles can move automatically on the rope and this can be realized by energy and signals. The ultra-light overhead conveyor systems always must be integrated with a logistical process by finding a best way for a cheaper material flow in order to guarantee precise and fast workflows. This paper analyzes the process of an ultra-light overhead conveyor system using necessary assumptions. The analysis consists of three scenarios. These scenarios are based on raising the vehicle speeds with equal increments at each case. The correlation between the vehicle speed and system throughput is investigated. A discrete-event simulation model of an ultra-light overhead conveyor system is constructed using DOSIMIS-3 software to implement three scenarios. According to simulation results; the optimal scenario, hence the optimal vehicle speed, is found out among three scenarios. This simulation model demonstrates the effect of increased speed on the system throughput.
Abstract: Earthmoving operations are a major part of many
construction projects. Because of the complexity and fast-changing
environment of such operations, the planning and estimating are
crucial on both planning and operational levels. This paper presents
the framework ofa microscopic discrete-event simulation system for
modeling earthmoving operations and conducting productivity
estimations on an operational level.A prototype has been developed
to demonstrate the applicability of the proposed framework, and this
simulation system is presented via a case study based on an actual
earthmoving project. The case study shows that the proposed
simulation model is capable of evaluating alternative operating
strategies and resource utilization at a very detailed level.
Abstract: A local municipality has decided to build a sewage pit
to receive residential sewage waste arriving by tank trucks. Daily
accumulated waste are to be pumped to a nearby waste water
treatment facility to be re-consumed for agricultural and construction
projects. A discrete-event simulation model using Arena Software
was constructed to assist in defining the capacity of the system in
cubic meters, number of tank trucks to use the system, number of
unload docks required, number of standby areas needed and
manpower required for data collection at entrance checkpoint and
truck tank load toxicity testing. The results of the model are
statistically validated. Simulation turned out to be an excellent tool
in the facility planning effort for the pit project, as it insured smooth
flow lines of tank trucks load discharge and best utilization of
facilities on site.
Abstract: In recent years, sustainable supply chain management
(SSCM) has been widely researched in academic domain. However,
due to the traditional operational role and the complexity of supply
chain management in the cement industry, a relatively small amount
of research has been conducted on cement supply chain simulation
integrated with sustainability criteria. This paper analyses the cement
supply chain operations using the Push-Pull supply chain
frameworks, the Life Cycle Assessment (LCA) methodology; and
proposal integration approach, proposes three supply chain scenarios
based on Make-To-Stock (MTS), Pack-To-Order (PTO) and Grind-
To-Order (GTO) strategies. A Discrete-Event Simulation (DES)
model of SSCM is constructed using Arena software to implement
the three-target scenarios. We conclude with the simulation results
that (GTO) is the optimal supply chain strategy that demonstrates the
best economic, ecological and social performance in the cement
industry.
Abstract: Time series analysis often requires data that represents
the evolution of an observed variable in equidistant time steps. In
order to collect this data sampling is applied. While continuous
signals may be sampled, analyzed and reconstructed applying
Shannon-s sampling theorem, time-discrete signals have to be dealt
with differently. In this article we consider the discrete-event
simulation (DES) of job-shop-systems and study the effects of
different sampling rates on data quality regarding completeness and
accuracy of reconstructed inventory evolutions. At this we discuss
deterministic as well as non-deterministic behavior of system
variables. Error curves are deployed to illustrate and discuss the
sampling rate-s impact and to derive recommendations for its wellfounded
choice.