Relevant bibliographies by topics / Simulation Process Management

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Simulation Process Management'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Simulation Process Management"

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Gayialis, S. P., G. A. Papadopoulos, S. T. Ponis, P. Vassilakopoulou, and I. P. Tatsiopoulos. "Integrating Process Modeling and Simulation with Benchmarking using a Business Process Management System for Local Government." International Journal of Computer Theory and Engineering 8, no. 6 (December 2016): 482–89. http://dx.doi.org/10.7763/ijcte.2016.v8.1093.

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Tomaskova, Hana, Martin Kopecky, and Petra Maresova. "Process Cost Management of Alzheimer’s Disease." Processes 7, no. 9 (September 2, 2019): 582. http://dx.doi.org/10.3390/pr7090582.

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Summary: Determining the cost of healthcare and social care for patients is a crucial issue for many parties; therefore, both public and private payments play a decisive role in patient care. The article deals with the analysis of the possibilities of the simulation of costs related to Alzheimer’s disease. This disease is highly variable, and the cost items vary considerably. Therefore, it is necessary to use simulation methods. The results of simulation models can then be implemented in sophisticated methods working with activity costs. Findings: Models for health and social care are specific. No significant re-engineering is expected in this area, so the models must be unambiguous and easy to understand for all representatives involved. Modeling of business processes is thus a suitable means for analysis in this area. The process cost calculation is built on two simulation models. The first model is the Business Process Model and Notation (BPMN), the results of which are verified in the system dynamics model created in the stock and flow diagram. The simulations results give us appropriate values for calculating the total activity-based costs of AD. Applications: The practical part of this article deals with the identification of costs related to Alzheimer’s disease and their allocation concerning remedies. Based on this information, models for Alzheimer’s disease process cost management are developed. Results: The BPMN simulation was performed for 100 passes through a fixed-length phase process. The duration of each phase was set at 48, 108, and 40 months. Five simulations were set up, each Mini-Mental State Examination (MMSE) score set, which affected the passage through the process. Software Stella Professional was used for simulations for constant MMSE score values for the home and facility options. The values are as follows: MMSE 5 = 1331 . 26 ( 1627 . 72 ); MMSE 15 = 1202 . 72 ( 1102 . 02 ); MMSE 25 = 1051 . 24 ( 848 . 91 ). Conclusions: Both AD models created in this article produce comparable results, although each of them works on a different principle. The results are based on the selection of original data, and at the same time, these models point to the processes and subprocesses that lead to the costs. The description, specifications, and possible values of partial costs are crucial knowledge for persons in the management functions of public administration and self-government in the area of finance and management not in the field of specific diseases.
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Jain, S., and R. R. Creasey. "Simulation standard for business process management." IEEE Engineering Management Review 43, no. 3 (2015): 80–88. http://dx.doi.org/10.1109/emr.2015.7433292.

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Rus, Ioana, James Collofello, and Peter Lakey. "Software process simulation for reliability management." Journal of Systems and Software 46, no. 2-3 (April 1999): 173–82. http://dx.doi.org/10.1016/s0164-1212(99)00010-2.

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Elliman, Tony, Tally Hatzakis, and Alan Serrano. "Business Process Simulation." International Journal of Enterprise Information Systems 2, no. 3 (July 2006): 43–58. http://dx.doi.org/10.4018/jeis.2006070104.

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Bowles, David E., and Lorraine R. Gardiner. "Supporting process improvements with process mapping and system dynamics." International Journal of Productivity and Performance Management 67, no. 8 (November 12, 2018): 1255–70. http://dx.doi.org/10.1108/ijppm-03-2017-0067.

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Purpose The purpose of this paper is to study the effectiveness of combining process mapping and system dynamics (SD) in an organization’s ongoing business process improvement projects. Design/methodology/approach Norfield Industries, designer and manufacturer of prehung door machinery, used process mapping and SD in a project targeting the improvement of its design document control process. The project team first used process mapping to document its current process and identify potential improvements. The team then developed an SD model to investigate the potential impacts of proposed process changes. Findings The case study supports the communication and transparency benefits of process mapping reported in earlier studies. Consistent with other case studies using simulation, SD provided useful insights into possible results of proposed process changes. Research limitations/implications The findings have limitations with respect to generalizability consistent with the use of a case study methodology. Practical implications Organizational managers desiring to include simulation modeling in process improvement efforts have a choice between discrete event simulation and SD. SD may prove able to consume less organizational resources than discrete-event simulation and provide similar benefits related to reducing the risks associated with process changes. Originality/value The current case study adds to the existing literature documenting the use of process mapping combined with simulation modeling in process improvement efforts. The case study supports existing literature regarding the value of process mapping in making system processes more transparent. The results also support previous findings regarding the value of SD for simulating the possible results associated with scenarios under consideration for process improvements.
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Nascimento, João, Paulo Resende da Silva, and João Samartinho. "Project Management Simulation Portal." International Journal of Web Portals 5, no. 4 (October 2013): 20–32. http://dx.doi.org/10.4018/ijwp.2013100102.

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Simulation, in the context of Project Management teaching / learning process, has been described as an effective way to achieve better outcomes. There are already some tools developed to simulate the management of technical work. Still, project management is much more than dealing with technical tasks. The system developed aims to sustain the process of teaching / learning the subject of project management in a broad range. When compared with other work in the field, there are two aspects that stand out from the product described in this paper: (1) the use of the Web to enhance the interaction between the agents involved in the teaching / learning process, and (2) the variety of skills considered in the system. More than focusing on a small set of processes dealing with technical work management, the solution presented here involves nearly the full project management life cycle. This paper proposes a simulation system for Project Management, based on the Web environment (Project Management Virtual Environment). It also presents the process of the system's construction and describes its features.
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Ding, Yan, Keh-Chia Yeh, and Shao-Tang Wei. "INTEGRATED COASTAL PROCESS MODELING AND IMPACT ASSESSMENT OF FLOATING AND SEDIMENTATION IN COASTS AND ESTUARIES." Coastal Engineering Proceedings, no. 35 (June 23, 2017): 18. http://dx.doi.org/10.9753/icce.v35.management.18.

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In this study, an integrated coastal process model was applied to assess impact of coastal flooding and sedimentation in an estuary in Taiwan and to evaluate performance of proposed engineering plans for flood prevention and sedimentation management. This in-situ validated model was used to simulate and predict hydrodynamic processes and morphological changes induced by multiple hydrological forcing such as river flood flows, waves, tides, and storms surges from rivers to the estuary and its adjacent coasts. Simulation results quantified coastal flooding risks, erosions, sedimentation, and channel refilling. Predicted dynamic responses to typhoons and monsoons were utilized for identifying the most effective engineering plan to reshape the geometry of the estuary. After the selected engineering plan was accomplished, this model was applied again to further predict morphological changes in the newly-developed estuary. This paper demonstrates effectiveness of a simulation-based coastal and estuary planning approach to manage flood and sedimentation driven by complex physical processes from river flows, waves, tides, and sediment transport.
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Barber, K. D., F. W. Dewhurst, R. L. D. H. Burns, and J. B. B. Rogers. "Business‐process modelling and simulation for manufacturing management." Business Process Management Journal 9, no. 4 (August 2003): 527–42. http://dx.doi.org/10.1108/14637150310484544.

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Wadsley, Michael. "Understanding management of computational process modeling and simulation." JOM 56, no. 12 (December 2004): 33–36. http://dx.doi.org/10.1007/s11837-004-0232-1.

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Dissertations / Theses on the topic "Simulation Process Management"

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Runge, Torsten, and Kondragunda Narendra. "Teamcenter Simulation Process Management." Technische Universität Chemnitz, 2018. https://monarch.qucosa.de/id/qucosa%3A21532.

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Manage your simulation processes, data, tools and workflows The pressure to shorten time-to-market while improving product performance and quality is driving the increased use of simulation throughout the product lifecycle. However, without some form of simulation data management, simulation itself can become a process bottleneck. The Teamcenter simulation process management solution has been specifically designed to help you get control of your simulation data and processes in the context of an overall product lifecycle management (PLM) system. With Teamcenter, you can avoid common problems such as analyses being performed on obsolete data, poor visibility to simulation results, and results arriving too late to influence design direction. You can efficiently manage and share complex product simulations so they are available to all product decision-makers across your business.
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Ettefaghian, Alireza. "Automated input data management in manufacturing process simulation." Thesis, University of Greenwich, 2015. http://gala.gre.ac.uk/14122/.

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Input Data Management (IDM) is a time consuming and costly process for Discrete Event Simulation (DES) projects. Input Data Management is considered as the basis of real-time process simulation (Bergmann, Stelzer and Strassburger, 2011). According to Bengtsson et al. (2009), data input phase constitutes on the average about 31% of the time of an entire simulation project. Moreover, the lack of interoperability between manufacturing applications and simulation software leads to a high cost to users in developing custom-built interfaces (NIST, 2011). Therefore, a standard structure is needed to facilitate data exchange within different manufacturing data from various sources and simulation packages (Harari, 2012). This work aims to develop an IDM system in order to enhance automatic data exchange within manufacturing process simulation projects. The approach is to use a Business Intelligence (BI) package to extract and collect simulation data from various sources, and then import to a DES application. Thus, a simulation model can be automatically updated in DES application by real-time system data. The prototype system is currently implemented in pilot-scale, and results are based on sample data files retrieved from the Simulation Engineering Department at Ford Motor Company. In addition to automatic data management, the system also generates an interoperable data file, which is compatible with most DES packages for simulation experiments. For the first time, a Business Intelligence system is applied to simulation data management projects, and is introduced as a novel solution for this context. The results of pilot-implementation indicated the possibility of direct connection between raw data sources and model database. The direct connection allows DES applications to integrate with different business systems without the need of plug-in translators for interpreting the exchanged data file. The system developed also reduces the number of human-driven processes through model update procedures. Also, it is found that the BI package can be integrated with existing middleware used in a company, to maintain an “as-is” simulation procedure, and minimise the possibility of process change in systematic model update.
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Polyakov, Denis, and Willi Gründer. "Design Process Management." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-228289.

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Aus der Einleitung: "Arbeitsabläufe werden in der Regel durch eine jahrzehntelange Praxis geprägt. Eine Vielzahl von individuellen Gewohnheiten und Aspekten bildet oft eine hermetische Abgrenzung gegenüber allen Versuchen, organisatorische Veränderungen herbeizuführen. Dies gilt in besonderem Maße für die Konstruktion. Die unvoreingenommene Betrachtung heutiger Konstruktionsabläufe lässt uns feststellen, dass der Arbeitsprozess an sich seit Anbeginn vor vielen tausend Jahren fast unverändert geblieben ist. Abgesehen von einer Reihe mehr oder weniger voneinander isolierter Computer-Aided Software-Tools, die den Konstrukteur bei der Modellierung, Simulation und Datenspeicherung unterstützen, bekommt er keine weiteren Hilfestellungen. Eine Ausnahme bilden hier automatisierte Verfahrensketten, die auf der Basis fest definierter Produktmodelle in parametrisierten Verfahren Fertigungsunterlagen automatisch erstellen können. Prozessorientiert sind auch neuere Benutzeroberflächen zur Kopplung von Simulationsanwendungen. Hiermit können Anwendungen über mehrere Softwareapplikationen hinweg geschaffen werden (ModelCenter, modeFrontier). Das Wissensmanagement hingegen ist so gut wie gar nicht in die Abläufe integriert, lässt man die Fülle der Freigabeprozeduren einmal außen vor."
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Von, Raubenheimer Albert Ludwich. "Strategic supply chain management using simulation." Pretoria : [s.n.], 2005. http://upetd.up.ac.za/thesis/available/etd-12012005-092956/.

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Polyakov, Denis, and Willi Gründer. "Design Process Management." TUDpress - Verlag der Wissenschaften GmbH, 2012. https://tud.qucosa.de/id/qucosa%3A29486.

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Aus der Einleitung: "Arbeitsabläufe werden in der Regel durch eine jahrzehntelange Praxis geprägt. Eine Vielzahl von individuellen Gewohnheiten und Aspekten bildet oft eine hermetische Abgrenzung gegenüber allen Versuchen, organisatorische Veränderungen herbeizuführen. Dies gilt in besonderem Maße für die Konstruktion. Die unvoreingenommene Betrachtung heutiger Konstruktionsabläufe lässt uns feststellen, dass der Arbeitsprozess an sich seit Anbeginn vor vielen tausend Jahren fast unverändert geblieben ist. Abgesehen von einer Reihe mehr oder weniger voneinander isolierter Computer-Aided Software-Tools, die den Konstrukteur bei der Modellierung, Simulation und Datenspeicherung unterstützen, bekommt er keine weiteren Hilfestellungen. Eine Ausnahme bilden hier automatisierte Verfahrensketten, die auf der Basis fest definierter Produktmodelle in parametrisierten Verfahren Fertigungsunterlagen automatisch erstellen können. Prozessorientiert sind auch neuere Benutzeroberflächen zur Kopplung von Simulationsanwendungen. Hiermit können Anwendungen über mehrere Softwareapplikationen hinweg geschaffen werden (ModelCenter, modeFrontier). Das Wissensmanagement hingegen ist so gut wie gar nicht in die Abläufe integriert, lässt man die Fülle der Freigabeprozeduren einmal außen vor."
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Arikan, Merve. "Systems Engineering Process Modeling And Simulation." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12615164/index.pdf.

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In this study, an approach is proposed to model and simulate the systems engineering process of design projects. One of the main aims is to model the systems engineering process, treating the process itself as a complex system. A conceptual model is developed as a result of a two-phase survey conducted with systems engineers. The conceptual model includes two levels of activity networks. Each first level systems engineering activity has its own network of second level activities. The model is then implemented in object oriented modeling language, namely SysML, using block definition diagrams and activity diagrams. Another aim is to generate a discrete event simulation model of the process for performance evaluation. For this purpose the SysML model is transformed to an Arena model using an Excel interface and VBA codes. Three deterministic and three stochastic cases are created to represent systems engineering process alternatives, which originate from the same conceptual model but possess different activity durations, resource availabilities and resource requirements. The scale of the project and the effect of uncertainty in activity durations are also considered. The proposed approach is applied to each of these six cases, developing the SysML models, transforming them to Arena models, and running the simulations. Project duration and resource utilization results are reported for these cases.
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Evenson, Grey Rogers. "A Process-Comprehensive Simulation-Optimization Framework for Watershed Scale Wetland Restoration Planning." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1406213250.

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Masood, Uzzafer. "Simulation of strategic management process of software projects : a dynamic approach." Thesis, University of Nottingham, 2014. http://eprints.nottingham.ac.uk/14039/.

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This research presents and validates a simulation model for the strategic management process of software projects. The proposed simulation model maps strategic decisions with parameters of strategic importance and links them to project management plans. Hence, the proposed simulation model is a complete framework for the analysis and the selection of strategic decisions for the development of software projects. The proposed framework integrates critical elements of software development projects, i.e. risk assessment, cost estimation and project management planning, for the analysis of strategic decisions which helps in choosing a strategic decision, among various strategic alternatives for the project, that suits the requirement of an organization the best. The simulation model captures the effects of strategic decisions on parameters of software projects in dynamic settings during the simulation of different phases of the development. The dynamic variations in project parameters affect project management plans. Capturing these variations of strategic parameters in dynamic settings brings out critical information about strategic decisions for the effective project management planning. This research work explains that the measure of risk and contingency estimates are fundamental, in-addition to risk assessment and cost estimation, for the strategic management of software development projects. Therefore, risk measure and contingency estimation models are developed for software projects. The proposed simulation model is generic, i.e. having generic components with plug-and-play interfaces; hence, it is independent of any risk assessment, cost estimation, risk measurement and contingency estimation models and project management tools for software development projects. This research presents a successful case study which shows that different strategic management decisions produce different sets of risk and cost options, as well as different project management plans for the development of software projects.
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Hughes, Nina(Nina Yuchen). "Reverse logistics supply chain process modeling and simulation." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122581.

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Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2019, In conjunction with the Leaders for Global Operations Program at MIT
Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2019, In conjunction with the Leaders for Global Operations Program at MIT
Cataloged from PDF version of thesis.
Includes bibliographical references (page 67).
As consumer preferences shift towards online shopping and utilizing their homes as fitting rooms, traditional brick and mortar retailers are faced with the challenge to adapt. Many retailers are experiencing a growing number of returned merchandize, many of which cannot be easily resold to consumers due to various supply chain challenges. This thesis explores the opportunities to improve the consumer returns process and presents methods for modeling the supply chain process for reverse logistics in the retail industry derived from case studies. The model then allows for hypothesis testing. By changing parameters in the model, this thesis further explores the scenarios in which the supply chain process may be improved to increase margin and decrease cost. The primary recommendations include specific modifications to the current reverse supply chain flow, enabling new channels that improve speed and margin, as well as developing the decision tool further for better accuracy and integration into the supply chain.
by Nina Hughes.
M.B.A.
S.M.
M.B.A. Massachusetts Institute of Technology, Sloan School of Management
S.M. Massachusetts Institute of Technology, Department of Civil and Environmental Engineering
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Ekman, Mats. "Urban water management : Modelling, simulation and control of the activated sludge process." Licentiate thesis, Uppsala universitet, Avdelningen för systemteknik, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-86143.

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During the last few decades, wastewater treatment processes in urban water management have become more and more efficient and complex. Several factors such as urbanization, stricter legislations on effluent quality, economics, increased knowledge of the involved biological, chemical and physical processes as well as technical achievements have been important incentives for the development of more efficient procedures for wastewater treatment plants. Future requirements on more sustainable urban water systems, in combination with increasing wastewater loads, will most probably further increase the need for optimization and control of both existing and emerging wastewater treatment processes. In this thesis estimation, modelling and control strategies are developed in order to improve the efficiency of the activated sludge process. The first part of the thesis presents a JAVA based simulator of the activated sludge process. An overview of its features, with some emphasis on implemented control strategies, is given. In particular, a new control strategy for the internal recycling flow rate is described. A summary of experiences from using the simulator as a teaching and training tool is also given. The second part of the thesis includes a derivation of reduced order models for the activated sludge process. The resulting models, a time-varying linear state-space model for the anoxic part and a time-varying bilinear state-space model for the aerobic part, are intended to be used for control applications. In the third part, an adaptive control strategy for control of the nitrate level using an external carbon source is presented. The controller adapts and compensates for changes in the system dynamics since important system parameters are estimated adaptively and incorporated on-line in the control design. The estimated system parameters and model states also give guidance about the state of the process and the characteristics of the wastewater. Several simulation examples are used to illustrate the control law. Finally, a new suboptimal control law for the bilinear quadratic regulator problem with infinite final time is presented. The control strategy is evaluated in a simulation study, where special concern is devoted to controlling the activated sludge process, using the bilinear model developed in the second part of this thesis.
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Books on the topic "Simulation Process Management"

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Johan, Marklund, ed. Business process modeling, simulation, and design. Boca Raton: Taylor & Francis, 2013.

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Johan, Marklund, ed. Business process modeling, simulation, and design. Upper Saddle River, NJ: Pearson/Prentice Hall, 2004.

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Laguna, Manuel. Business process modeling: Simulation and design. North Chelmsford, MA: Erudition Books, 1999.

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Managing change with business process simulation. Upper Saddle River, NJ: Prentice Hall PTR, 1998.

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Yu, Eric Siu-Kwong. Modelling strategic relationships for process reengineering. Toronto: University of Toronto, Dept. of Computer Science, 1995.

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Yu, Eric Siu-Kwong. Modelling strategic relationships for process reengineering. Toronto: Dept. of Computer Science, University of Toronto, 1994.

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Morales, Peter J. Process Simulation and Parametric Modeling for Strategic Project Management. New York, NY: Springer New York, 2013.

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Morales, Peter J., and Dennis Anderson. Process Simulation and Parametric Modeling for Strategic Project Management. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6989-6.

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Holcombe, W. M. L. Correct systems: Building a business process solution. London: Springer, 1998.

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Taskinen, Leo Tapani. Measuring change management in manufacturing processes: A measurement method for simulation-game-based process development. Espoo [Finland]: Technical Research Centre of Finland, 2002.

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Book chapters on the topic "Simulation Process Management"

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Neumann, Stefan, Michael Rosemann, and Ansgar Schwegmann. "Simulation of Business Processes." In Process Management, 373–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15190-3_13.

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van der Aalst, Wil M. P., Joyce Nakatumba, Anne Rozinat, and Nick Russell. "Business Process Simulation." In Handbook on Business Process Management 1, 313–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-00416-2_15.

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Morales, Peter J., and Dennis Anderson. "Quantitative Process Simulation." In Process Simulation and Parametric Modeling for Strategic Project Management, 35–48. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6989-6_6.

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Laguna, Manuel, and Johan Marklund. "Process Management and Process-Oriented Improvement Programs." In Business Process Modeling, Simulation and Design, 27–76. Third Edition. | Boca Raton, FL : CRC Press, [2019] | Revised edition of the authors’ Business process modeling, simulation, and design, [2013]: Chapman and Hall/CRC, 2018. http://dx.doi.org/10.1201/9781315162119-2.

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Tatsiopoulos, I. P., N. A. Panayiotou, and S. T. Ponis. "Business process assessment using discrete simulation." In Global Production Management, 498–504. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-0-387-35569-6_61.

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Ackermann, Lars, Stefan Schönig, and Stefan Jablonski. "Simulation of Multi-perspective Declarative Process Models." In Business Process Management Workshops, 61–73. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58457-7_5.

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Wynn, Moe Thandar, Marlon Dumas, Colin J. Fidge, Arthur H. M. ter Hofstede, and Wil M. P. van der Aalst. "Business Process Simulation for Operational Decision Support." In Business Process Management Workshops, 66–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-78238-4_8.

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Senderovich, Arik. "Service Analysis and Simulation in Process Mining." In Business Process Management Workshops, 578–81. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15895-2_51.

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van der Aalst, Wil M. P. "Business Process Simulation Survival Guide." In Handbook on Business Process Management 1, 337–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-45100-3_15.

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Redlich, David, and Wasif Gilani. "Event-Driven Process-Centric Performance Prediction via Simulation." In Business Process Management Workshops, 473–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28108-2_46.

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Conference papers on the topic "Simulation Process Management"

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Januszczak, John, and Geoff Hook. "Simulation standard for business process management." In 2011 Winter Simulation Conference - (WSC 2011). IEEE, 2011. http://dx.doi.org/10.1109/wsc.2011.6147801.

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April, Jay, Marco Better, Fred Glover, James Kelly, and Manuel Laguna. "Enhancing Business Process Management with Simulation Optimization." In 2006 Winter Simulation Conference. IEEE, 2006. http://dx.doi.org/10.1109/wsc.2006.323141.

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Curcio, Duilio, Francesco Longo, and Giovanni Mirabelli. "Manufacturing process management using a flexible modeling and simulation approach." In 2007 Winter Simulation Conference. IEEE, 2007. http://dx.doi.org/10.1109/wsc.2007.4419778.

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Bocheng Gao, Linhan Guo, Lin Ma, and Kai Wang. "Corrective maintenance process simulation algorithm research based on process interaction." In 2012 Prognostics and System Health Management Conference (PHM). IEEE, 2012. http://dx.doi.org/10.1109/phm.2012.6228942.

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Huber, Wayne C. "Wet-Weather Treatment Process Simulation Using SWMM." In Third International Conference on Watershed Management. Reston, VA: American Society of Civil Engineers, 2003. http://dx.doi.org/10.1061/40706(266)22.

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Jünemann, Konrad, Jochen Dinger, and Hannes Hartenstein. "Ensuring reproducibility through tool-based simulation process management." In 3rd International ICST Conference on Simulation Tools and Techniques. ICST, 2010. http://dx.doi.org/10.4108/icst.simutools2010.8714.

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Zhou, Peng, and Hareton K. N. Leung. "A Stochastic Simulation Model for Risk Management Process." In 2012 19th Asia-Pacific Software Engineering Conference (APSEC). IEEE, 2012. http://dx.doi.org/10.1109/apsec.2012.12.

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Rousseaux, Francis, and Kevin Lhoste. "Process Analysis, Modeling and Simulation for Crisis Management." In 2008 International Workshop on Advanced Information Systems for Enterprises IWAISE '08. IEEE, 2008. http://dx.doi.org/10.1109/iwaise.2008.19.

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Xue, Lian, and Ling Tian. "Research on Simulation Process Management for Product Development." In 2008 ISECS International Colloquium on Computing, Communication, Control, and Management. IEEE, 2008. http://dx.doi.org/10.1109/cccm.2008.27.

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Mohammadi, Shayan. "A Risk Management Framework via Multi-paradigm Simulation for Supply Chain and Business Process Management." In The 33rd European Modeling & Simulation Symposium. CAL-TEK srl, 2021. http://dx.doi.org/10.46354/i3m.2021.emss.041.

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Reports on the topic "Simulation Process Management"

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Zachmann, David. Final Report: A Model Management System for Numerical Simulations of Subsurface Processes. Office of Scientific and Technical Information (OSTI), October 2013. http://dx.doi.org/10.2172/1095616.

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Iyer, Ananth V., Steven R. Dunlop, Olga Senicheva, Dutt J. Thakkar, Ruier Yan, Karthikeyan Subramanian, Suraj Vasu, Gokul Siddharthan, Juily Vasandani, and Srijan Saurabh. Improve and Gain Efficiency in Winter Operations. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317312.

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This report analyzes the current service level of winter operations in Indiana and explores opportunities to optimize performance. We analyze data regarding winter operations managed by INDOT and provide specific quantified estimates of opportunities to improve efficiency while also managing costs. For our exploration, we use data provided by INDOT sources, qualitative insights from interviews with INDOT personnel, literature survey data and benchmarking information, salt and supplier data analysis, and simulation. As part of our research, we developed a simulation model to visually represent the impact of alternate management of trucks for snow removal and a dashboard to understand the impact. Our analysis suggests the following: (1) opportunities exist to coordinate salt delivery by suppliers and combine local city salt purchases with INDOT’s purchases to save costs, (2) adjusting routes will reduce deadhead, (3) understanding truck maintenance and truck locations improves performance, and (4) incorporating critical locations into snow route planning will meet service thresholds. These insights provide implementable recommendation initiatives to improve winter operations performance. The simulation tool developed in this project simulates various weather events to draw insights and determine appropriate resource allocations and opportunities for improving operational efficiency. The report thus provides a quantifiable approach to winter operations that can improve the overall service level and efficiency of the process.
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Chapman, Ray, Phu Luong, Sung-Chan Kim, and Earl Hayter. Development of three-dimensional wetting and drying algorithm for the Geophysical Scale Transport Multi-Block Hydrodynamic Sediment and Water Quality Transport Modeling System (GSMB). Engineer Research and Development Center (U.S.), July 2021. http://dx.doi.org/10.21079/11681/41085.

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The Environmental Laboratory (EL) and the Coastal and Hydraulics Laboratory (CHL) have jointly completed a number of large-scale hydrodynamic, sediment and water quality transport studies. EL and CHL have successfully executed these studies utilizing the Geophysical Scale Transport Modeling System (GSMB). The model framework of GSMB is composed of multiple process models as shown in Figure 1. Figure 1 shows that the United States Army Corps of Engineers (USACE) accepted wave, hydrodynamic, sediment and water quality transport models are directly and indirectly linked within the GSMB framework. The components of GSMB are the two-dimensional (2D) deep-water wave action model (WAM) (Komen et al. 1994, Jensen et al. 2012), data from meteorological model (MET) (e.g., Saha et al. 2010 - http://journals.ametsoc.org/doi/pdf/10.1175/2010BAMS3001.1), shallow water wave models (STWAVE) (Smith et al. 1999), Coastal Modeling System wave (CMS-WAVE) (Lin et al. 2008), the large-scale, unstructured two-dimensional Advanced Circulation (2D ADCIRC) hydrodynamic model (http://www.adcirc.org), and the regional scale models, Curvilinear Hydrodynamics in three dimensions-Multi-Block (CH3D-MB) (Luong and Chapman 2009), which is the multi-block (MB) version of Curvilinear Hydrodynamics in three-dimensions-Waterways Experiments Station (CH3D-WES) (Chapman et al. 1996, Chapman et al. 2009), MB CH3D-SEDZLJ sediment transport model (Hayter et al. 2012), and CE-QUAL Management - ICM water quality model (Bunch et al. 2003, Cerco and Cole 1994). Task 1 of the DOER project, “Modeling Transport in Wetting/Drying and Vegetated Regions,” is to implement and test three-dimensional (3D) wetting and drying (W/D) within GSMB. This technical note describes the methods and results of Task 1. The original W/D routines were restricted to a single vertical layer or depth-averaged simulations. In order to retain the required 3D or multi-layer capability of MB-CH3D, a multi-block version with variable block layers was developed (Chapman and Luong 2009). This approach requires a combination of grid decomposition, MB, and Message Passing Interface (MPI) communication (Snir et al. 1998). The MB single layer W/D has demonstrated itself as an effective tool in hyper-tide environments, such as Cook Inlet, Alaska (Hayter et al. 2012). The code modifications, implementation, and testing of a fully 3D W/D are described in the following sections of this technical note.
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