Application of Discrete Event Simulation in Industrial Sectors: A Case Study

Discrete Event Simulation (DES) has become a useful tool in the evaluation of changes that may bring positivity to manufacturing and process organizations for both goods and services provision. The main focus of any business entails the reduction of cost and lead time while increasing profits and this is why refining of production processes is essential. This paper reports the application of DES in two case studies. The case studies selected for the implementation of Discrete Event Simulation are a packaging company and a local mobile phone service provider using the software FlexSim. The implementation aims at showcasing the versatility and its ability to provide the relevant data to make more informed decision while optimizing the entire processes involved in production

A General Simulation Framework for Supply Chain Modeling: State of the Art and Case Study

Nowadays there is a large availability of discrete event simulation software that can be easily used in different domains: from industry to supply chain, from healthcare to business management, from training to complex systems design. Simulation engines of commercial discrete event simulation software use specific rules and logics for simulation time and events management. Difficulties and limitations come up when commercial discrete event simulation software are used for modeling complex real world-systems (i.e. supply chains, industrial plants). The objective of this paper is twofold: first a state of the art on commercial discrete event simulation software and an overview on discrete event simulation models development by using general purpose programming languages are presented; then a Supply Chain Order Performance Simulator (SCOPS, developed in C++) for investigating the inventory management problem along the supply chain under different supply chain scenarios is proposed to readers.Comment: International Journal of Computer Science Issues online at http://ijcsi.org/articles/A-General-Simulation-Framework-for-Supply-Chain-Modeling-State-of-the-Art-and-Case-Study.ph

Parallel Discrete Event Simulation with Erlang

Discrete Event Simulation (DES) is a widely used technique in which the state of the simulator is updated by events happening at discrete points in time (hence the name). DES is used to model and analyze many kinds of systems, including computer architectures, communication networks, street traffic, and others. Parallel and Distributed Simulation (PADS) aims at improving the efficiency of DES by partitioning the simulation model across multiple processing elements, in order to enabling larger and/or more detailed studies to be carried out. The interest on PADS is increasing since the widespread availability of multicore processors and affordable high performance computing clusters. However, designing parallel simulation models requires considerable expertise, the result being that PADS techniques are not as widespread as they could be. In this paper we describe ErlangTW, a parallel simulation middleware based on the Time Warp synchronization protocol. ErlangTW is entirely written in Erlang, a concurrent, functional programming language specifically targeted at building distributed systems. We argue that writing parallel simulation models in Erlang is considerably easier than using conventional programming languages. Moreover, ErlangTW allows simulation models to be executed either on single-core, multicore and distributed computing architectures. We describe the design and prototype implementation of ErlangTW, and report some preliminary performance results on multicore and distributed architectures using the well known PHOLD benchmark.Comment: Proceedings of ACM SIGPLAN Workshop on Functional High-Performance Computing (FHPC 2012) in conjunction with ICFP 2012. ISBN: 978-1-4503-1577-

Pemodelan Simulasi Antrian dengan Metode Discrete Event Simulation Queue Simulation Modeling with Discrete Event Simulation Method

ABSTRAKSI: Pemodelan adalah suatu representasi sistem nyata dari objek-objek dengan mengambil bentuk matematis dan suatu relasi logika. Secara umum, simulasi didefinisikan sebagai representasi dinamis dari sebagian dunia nyata dengan menggunakan komputer dan berjalan berdasarkan waktu tertentu. Salah satu teknik pemodelan adalah Discrete Event Simulation (DES), melakukan pemodelan suatu sistem yang berubah setiap satuan waktu. Metode ini bersifat stochastic, dynamic, dan discret-event.Dalam tugas akhir ini diimplementasikan beberapa model simulasi antrian yang menggunakan aturan antrian yang berbeda-beda pada tiap model antrian. Model simulasi antrian yang dibangun adalah single server queue, multi server queue, time shared computer model, multi teller bank with jockeying, dan job-shop model.Model yang dihasilkan memiliki parameter customer, arrival dan service time. Dengan menghasilkan output waktu rata-rata dari jumlah total customer atau job dalam antrian, waktu rata-rata utilisasi server, waktu tunggu rata-rata customer sebelum dilayani oleh server. Hasil pengujian terhadap fungsionalitas aplikasi menunjukkan bahwa fungsi-fungsi dari model antrian dapat berjalan sesuai dengan spesifikasi yang telah ditetapkan.Kata Kunci : DES, antrian, state, event, model, simulasi.ABSTRACT: Modeling is a real system representation of objects with mathematical form and a logic relationship. In general, simulation defined as dynamic representation from some of real worlds by using computer and run with selected time. One of modeling technique is Discrete Event Simulation (DES), doing a system modeling what changing each everytime. This method have the character of stochastic, dynamic, and discrete-event.In this final exam implementation some queue simulation models using queue rule which different each other queue model. Queue simulation models the build are single server queue, multi server queue, time shared computer model, multi teller bank with jockeying, dan job-shop model.The model have parameter customer, arrival dan service time. With result output time average size of the queue, time average utilization of the Server, time average wait in queue. Examination result to application functionality indicate that functions of queue model can run and match with specification have been specified.Keyword: DES, queue, state, event, modeling, simulatio

A Novel Chronic Disease Policy Model

We develop a simulation tool to support policy-decisions about healthcare for chronic diseases in defined populations. Incident disease-cases are generated in-silico from an age-sex characterised general population using standard epidemiological approaches. A novel disease-treatment model then simulates continuous life courses for each patient using discrete event simulation. Ideally, the discrete event simulation model would be inferred from complete longitudinal healthcare data via a likelihood or Bayesian approach. Such data is seldom available for relevant populations, therefore an innovative approach to evidence synthesis is required. We propose a novel entropy-based approach to fit survival densities. This method provides a fully flexible way to incorporate the available information, which can be derived from arbitrary sources. Discrete event simulation then takes place on the fitted model using a competing hazards framework. The output is then used to help evaluate the potential impacts of policy options for a given population.Comment: 24 pages, 13 figures, 11 table

Modeling emergency departments using discrete event simulation techniques

This paper discusses the application of Discrete Event Simulation (DES) for modeling the operations of an Emer-gency Department (ED). The model was developed to help the ED managers understand the behavior of the system with regards to the hidden causes of excessive waiting times. It served as a tool for assessing the impact of major departmental resources on Key Performance Indicators (KPIs), and was also used as a cost effective method for testing various what-if scenarios for possible system im-provement. The study greatly enhanced managers’ under-standing of the system and how patient flow is influenced by process changes and resource availability. The results of this work also helped managers to either reverse or modify some proposed changes to the system that were previously being considered. The results also show a possible reduc-tion of more than 20% in patients waiting times

Discrete-event simulation unmasks the quantum Cheshire Cat

It is shown that discrete-event simulation accurately reproduces the experimental data of a single-neutron interferometry experiment [T. Denkmayr {\sl et al.}, Nat. Commun. 5, 4492 (2014)] and provides a logically consistent, paradox-free, cause-and-effect explanation of the quantum Cheshire cat effect without invoking the notion that the neutron and its magnetic moment separate. Describing the experimental neutron data using weak-measurement theory is shown to be useless for unravelling the quantum Cheshire cat effect

Discrete-event simulation of uncertainty in single-neutron experiments

A discrete-event simulation approach which provides a cause-and-effect description of many experiments with photons and neutrons exhibiting interference and entanglement is applied to a recent single-neutron experiment that tests (generalizations of) Heisenberg's uncertainty relation. The event-based simulation algorithm reproduces the results of the quantum theoretical description of the experiment but does not require the knowledge of the solution of a wave equation nor does it rely on concepts of quantum theory. In particular, the data satisfies uncertainty relations derived in the context of quantum theory