Academic literature on the topic 'Process and Product Modeling'

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Journal articles on the topic "Process and Product Modeling"

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Smith, Robert P., and Jeffrey A. Morrow. "Product development process modeling." Design Studies 20, no. 3 (May 1999): 237–61. http://dx.doi.org/10.1016/s0142-694x(98)00018-0.

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Araki, Katsufumi, Katsuya Terashima, Makoto Senoo, and Jun Kanie. "2314 Product and Process Modeling for Product Development." Proceedings of Design & Systems Conference 2010.20 (2010): _2314–1_—_2314–5_. http://dx.doi.org/10.1299/jsmedsd.2010.20._2314-1_.

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Lee, Ghang, Charles M. Eastman, and Rafael Sacks. "Eliciting information for product modeling using process modeling." Data & Knowledge Engineering 62, no. 2 (August 2007): 292–307. http://dx.doi.org/10.1016/j.datak.2006.08.005.

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Campagna, Dario, and Andrea Formisano. "Product and Production Process Modeling and Configuration." Fundamenta Informaticae 124, no. 4 (2013): 403–25. http://dx.doi.org/10.3233/fi-2013-841.

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Arsham, Hossein. "Modeling and simulation for product design process." SIMULATION 89, no. 2 (July 16, 2012): 178–91. http://dx.doi.org/10.1177/0037549712451776.

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Taylor, Barbara Kline. "Content, Process, and Product: Modeling Differentiated Instruction." Kappa Delta Pi Record 51, no. 1 (January 2, 2015): 13–17. http://dx.doi.org/10.1080/00228958.2015.988559.

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Neubauer, Johannes, Bernhard Steffen, and Tiziana Margaria. "Higher-Order Process Modeling: Product-Lining, Variability Modeling and Beyond." Electronic Proceedings in Theoretical Computer Science 129 (September 19, 2013): 259–83. http://dx.doi.org/10.4204/eptcs.129.16.

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Burgess, Mark A. "Digital Product Development." Mechanical Engineering 130, no. 08 (August 1, 2008): 34–38. http://dx.doi.org/10.1115/1.2008-aug-3.

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This article discusses changes in the digital product development. Advances in computing power are multiplying the capabilities of design engineers. Information technology has advanced at a tremendous pace. Developers of design systems have exploited this capability with sophisticated mathematics, and today's systems are capable of producing very complex designs in much higher definition than ever before. Advances in geometric modeling have made it possible to represent 3-D solids in minute detail. Process modeling, which began with the study of a single manufacturing process, eventually gave way to complete factory flow simulations. The recent advances in IT enabled crossing the boundaries among technology, geometry, and process modeling with integrated computer-aided engineering, computer-aided design, and process planning. Current trends have now extended process modeling throughout the integrated supply chain and the extended enterprise.
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Xiao, Renbin, Tinggui Chen, and Zhenwu Tao. "Information modeling and reengineering for product development process." International Journal of Management Science and Engineering Management 2, no. 1 (January 2007): 64–74. http://dx.doi.org/10.1080/17509653.2007.10671010.

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Tausworthe, Robert C. "Software quality management through process and product modeling." Annals of Software Engineering 1, no. 1 (December 1995): 119–39. http://dx.doi.org/10.1007/bf02249048.

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Dissertations / Theses on the topic "Process and Product Modeling"

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Bromberg, Matthew F. (Matthew Fox) 1970. "Modeling design rework in a product development process." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/34712.

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Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Manufacturing Program, Massachusetts Institute of Technology, 2000.
Includes bibliographical references (p. 37-38).
Managing the product development process is of vital concern to corporations. A critical aspect of product development that negatively impacts program cost and timing is rework. Unfortunately, in large organizations with successive development cycles, the product, process and organizational complexity preclude simple solutions. Even given sufficient data, many organizations do not understand what constitutes good and bad performance relative to rework. Through research at General Motors Truck Product Group, a model was developed that forecasts expected total rework. The model assumes rework is a function of: 1) The product portfolio and timing; 2) The complexity of each product program; 3) The pattern of rework over time for product programs; 4) The "lifecycle age" of each product program. The model has four potential uses: A) To aid in portfolio/project planning; B) To provide a rework performance baseline for management; C) To evaluate initiatives with regards to their impact on design rework; D) To identify leverage targets for management attention and improvement.
by Matthew F. Bromberg.
S.M.
M.B.A.
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Srivali, Nahathai. "New approach to drug product process design : leveraging first principles modeling and cross-product process monitoring to improve process design robustness." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/99039.

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Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2015. In conjunction with the Leaders for Global Operations Program at MIT.
Thesis: S.M., Massachusetts Institute of Technology, Engineering Systems Division, 2015. In conjunction with the Leaders for Global Operations Program at MIT.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 88-89).
Abstract The vision of the Operations Technology Group at Amgen is to enable a robust pipeline through focused and efficient operations research studies. Process design is traditionally developed by performing experiments, but other approaches can be used to improve cost, efficiency, and robustness. The scope of this internship included the use of First Principles, Computational Fluid Dynamics (CFD), and Cross-Product Process Monitoring (CPPM) to improve process design robustness with reduced testing and faster development cycle. The project focused specifically on the drug product development network, which included the development of processes from formulation to filling and finishing, clinical manufacturing, and technology transfer to commercial manufacturing The goal of this internship was to explore opportunities to utilize First Principles, CFD, and CPPM in drug product process design space. First Principles and CFD modeling tools were used to look into the physics of drug product filling process (specifically parameters influencing two key filling issues - drying during line stoppage and dripping between fills). Criteria for analyzing cost and benefits for the use of First Principles were also provided as strategic recommendations on where the new approach should be utilized. Clinical data were leveraged, with multivariate statistical data analysis, to determine inspection reject limit for the purpose of process monitoring and root cause analysis.
by Nahathai Srivali.
M.B.A.
S.M.
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Pinkett, Randal D. (Randal Dike) 1971. "Product development process modeling and analysis of digital wireless telephones." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/9863.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; and, (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management, 1998.
Includes bibliographical references (p. 128-130).
by Randal D. Pinkett.
M.B.A.
S.M.
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Osborne, Sean M. "Product development cycle time characterization through modeling of process iteration." Thesis, Massachusetts Institute of Technology, 1993. http://hdl.handle.net/1721.1/12381.

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Chang, Ai-Fu. "Process Modeling of Next-Generation Liquid Fuel Production - Commercial Hydrocracking Process and Biodiesel Manufacturing." Diss., Virginia Tech, 2011. http://hdl.handle.net/10919/58043.

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This dissertation includes two process modeling studies -- (1) predictive modeling of large-scale integrated refinery reaction and fractionation systems from plant data – hydrocracking process; and (2) integrated process modeling and product design of biodiesel manufacturing. \r\n1. Predictive Modeling of Large-Scale Integrated Refinery Reaction and Fractionation Systems from Plant Data -- Hydrocracking Processes: This work represents a workflow to develop, validate and apply a predictive model for rating and optimization of large-scale integrated refinery reaction and fractionation systems from plant data. We demonstrate the workflow with two commercial processes -- medium-pressure hydrocracking unit with a feed capacity of 1 million ton per year and high-pressure hydrocracking unit with a feed capacity of 2 million ton per year in the Asia Pacific. This work represents the detailed procedure for data acquisition to ensure accurate mass balances, and for implementing the workflow using Excel spreadsheets and a commercial software tool, Aspen HYSYS from Aspen Technology, Inc. The workflow includes special tools to facilitate an accurate transition from lumped kinetic components used in reactor modeling to the boiling point based pseudo-components required in the rigorous tray-by-tray distillation simulation. Two to three months of plant data are used to validate models' predictability. The resulting models accurately predict unit performance, product yields, and fuel properties from the corresponding operating conditions.\r\n2. Integrated Process Modeling and Product Design of Biodiesel Manufacturing: This work represents first a comprehensive review of published literature pertaining to developing an integrated process modeling and product design of biodiesel manufacturing, and identifies those deficient areas for further development. It also represents new modeling tools and a methodology for the integrated process modeling and product design of an entire biodiesel manufacturing train. We demonstrate the methodology by simulating an integrated process to predict reactor and \r\nseparator performance, stream conditions, and product qualities with different feedstocks. The results show that the methodology is effective not only for the rating and optimization of an existing biodiesel manufacturing, and but also for the design of a new process to produce biodiesel with specified fuel properties.
Ph. D.
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Ira), Zemel Marc I. (Marc. "Process modeling and capability feedback for integrated injection molded product development." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/38155.

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Daley, John E. "Autonomic Product Development Process Automation." BYU ScholarsArchive, 2007. https://scholarsarchive.byu.edu/etd/965.

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Market globalization and mass customization requirements are forcing companies towards automation of their product development processes. Many task-specific software solutions provide localized automation. Coordinating these local solutions to automate higher-level processes requires significant software maintenance costs due to the incompatibility of the software tools and the dynamic nature of the product development environment. Current automation methods do not provide the required level of flexibility to operate in this dynamic environment. An autonomic product development process automation strategy is proposed in order to provide a flexible, standardized approach to product development process automation and to significantly reduce the software maintenance costs associated with traditional automation methods. Key elements of the strategy include a formal approach to decompose product development processes into services, a method to describe functional and quality attributes of services, a process modeling algorithm to configure processes composed of services, a method to evaluate process utility based on quality metrics and user preferences, and an implementation that allows a user to instantiate the optimal process. Because the framework allows a user to rapidly reconfigure and select optimal processes as new services are introduced or as requirements change, the framework should reduce burdensome software maintenance costs associated with traditional automation methods and provide a more flexible approach.
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Kimawati, Lenni. "Modeling consumer insight strategy in product development process : a decision and implementation framework for product managers." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113518.

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Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, 2017.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 154-158).
Companies today must constantly innovate to delight consumers and stay ahead of the competition. One way to deliver these is through new product launches. Despite significant investments, product failure rate in consumer products industry is high. Studies attribute failures to lack of quality and lack of integration of consumer insight in the Product Development Process. This thesis is an attempt for improvement, adopting the lens of consumer insight as information in the Product Development Process, and proposes a method to evaluate options more strategically. This thesis first examines available literature on Product Development Processes and consumer insight methodologies. It then uses Design Structure Matrix to identify consumer insight involvement in Product Development Process, and identifies gaps between the theoretical model and industry practice. Thereafter, this thesis proposes a technique to compare the quality of different consumer research methods at a given point in the process. Using this information, this thesis builds a Quantitative model to simulate the propagation effect of individual consumer insights decision on quality of output information, using rate of market change as a secondary factor. Within the constraints of this model, it was found that consumer insight strategy decisions should not be done in an ad-hoc manner, since consumer research method selection at each point in the Product Development Process has direct and propagative effects on the quality of the outcome. To obtain good quality, the selection of a good method is critical; first, because it allows for flexibility of options in subsequent phases, and second, because it is more effective than rework, under Slow and Rapid rate of market change. This thesis proposes decision and implementation frameworks as a guide for Product Managers, who can combine the predicted outcome of consumer insight quality with project management iron triangle, to select the best consumer insight strategy. While this consumer insight systemic model is a step towards a model-based design of consumer insight strategy, future work is needed to validate the quantitative model and resulting decision framework.
by Lenni Kimawati.
S.M. in Engineering and Management
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Darira, Rishi. "Modeling demand uncertainty and processing time variability for multi-product chemical batch process." [Tampa, Fla.] : University of South Florida, 2004. http://purl.fcla.edu/fcla/etd/SFE0000401.

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Pool, Kirby Vinton. "Product/process improvement through performance measurements and modeling : a case study in aerospace welding." Thesis, Massachusetts Institute of Technology, 1991. http://hdl.handle.net/1721.1/13376.

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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, and Sloan School of Management, 1991.
Includes bibliographical references (leaves 135-136).
by Kirby Vinton Pool.
M.S.
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Books on the topic "Process and Product Modeling"

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A, Liu Y., ed. Step-growth polymerization process modeling and product design. Hoboken, N.J: Wiley, 2008.

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Ma, Yongsheng, ed. Semantic Modeling and Interoperability in Product and Process Engineering. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5073-2.

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Ma, Yongsheng. Semantic Modeling and Interoperability in Product and Process Engineering: A Technology for Engineering Informatics. London: Springer London, 2013.

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European Conference on Product and Process Modelling in the Building Industry (3rd 2000 Lisbon, Portugal). Product and process modelling in building and construction: Proceedings of the Third European Conference on product and process modelling in the building and related industries, Lisbon/Portugal, 25-27 September 2000. Rotterdam: Balkema, 2000.

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European Conference on Product and Process Modelling in the Building Industry (2nd 1998 Building Research Establishment). Product and process modelling in the building industry: Proceedings of ECPPM'98 - the Second European Conference on Product and Process Modelling in the Building Industry, BRE, UK. 19-21 October 1998. Watford: BRE, 1998.

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European Conference on Product and Process Modelling in the Building Industry (1st 1994 Dresden, Germany). Product and process modelling in the building industry: Proceedings of ECPPM '94, the First European Conference on Product and Process Modelling in the Building Industry, Dresden, Germany, 5-7 October 1994. Rotterdam: A.A. Balkema, 1995.

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Andreas, Jedlitschka, Juristo Natalia, and SpringerLink (Online service), eds. Product-Focused Software Process Improvement: 13th International Conference, PROFES 2012, Madrid, Spain, June 13-15, 2012 Proceedings. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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European Conference on Product and Process Modelling in the Building and Related Industries, 3rd, ECPPM 2000, Lisbon, 2000. Products and process modelling in building and construction: Proceedings of the Third European Conference on Product and Process Modelling in the Building and Related Industries, Lisbon, Portugal, 25-27 September 2000. Rotterdam: Balkema, 2000.

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Process modeling. Harlow: Longman Scientific & Technical, 1987.

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Denn, Morton M. Process modeling. New York: Longman, 1986.

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Book chapters on the topic "Process and Product Modeling"

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am Ende, Mary T., William Ketterhagen, Andrew Prpich, Pankaj Doshi, Salvador García-Muñoz, and Rahul Bharadwajh. "DRUG PRODUCT PROCESS MODELING." In Chemical Engineering in the Pharmaceutical Industry, 489–525. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2019. http://dx.doi.org/10.1002/9781119600800.ch70.

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Cooper, Rachel, Ghassan Aouad, Angela Lee, and Song Wu. "Process and Product Modeling." In The Wiley Guide to Managing Projects, 471–97. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2007. http://dx.doi.org/10.1002/9780470172391.ch20.

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Farrington, P. A., J. J. Swain, and S. L. Messimer. "Systems modeling and simulation." In Integrated Product, Process and Enterprise Design, 435–64. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6383-9_14.

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Ocampo Ramírez, Alexis Eduardo. "ECO-MAPS: Information Quality-Driven Enterprise Modeling." In Product-Focused Software Process Improvement, 3. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39259-7_2.

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Monden, Akito, Shin-ichi Sato, Ken-ichi Matsumoto, and Katsuro Inoue. "Modeling and Analysis of Software Aging Process." In Product Focused Software Process Improvement, 140–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-540-45051-1_15.

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Visconti, Marcello, and Curtis R. Cook. "A Meta-model Framework for Software Process Modeling." In Product Focused Software Process Improvement, 532–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36209-6_44.

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Neumann, Frank. "Process Elements of Mechatronic Product Development." In Analyzing and Modeling Interdisciplinary Product Development, 141–55. Wiesbaden: Springer Fachmedien Wiesbaden, 2015. http://dx.doi.org/10.1007/978-3-658-11092-5_7.

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Karniel, Arie, and Yoram Reich. "Process Modeling Using Workflow-Nets." In Managing the Dynamics of New Product Development Processes, 75–95. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-570-5_6.

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Ruiz, Francisco, Mario Piattini, Félix García, and Macario Polo. "An XMI-Based Repository for Software Process Meta-modeling." In Product Focused Software Process Improvement, 546–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36209-6_45.

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Becker-Kornstaedt, Ulrike. "Towards Systematic Knowledge Elicitation for Descriptive Software Process Modeling." In Product Focused Software Process Improvement, 312–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44813-6_27.

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Conference papers on the topic "Process and Product Modeling"

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La Rosa, Marcello. "Modeling Business Process Variability." In SPLC '17: 21st International Systems and Software Product Line Conference. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3106195.3106196.

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Shuxia Li and Hongbo Shan. "Function flow-based product design process modeling." In 2010 IEEE International Conference on Automation and Logistics (ICAL). IEEE, 2010. http://dx.doi.org/10.1109/ical.2010.5585302.

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Cho, Soo-Haeng, and Steven D. Eppinger. "Product Development Process Modeling Using Advanced Simulation." In ASME 2001 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/detc2001/dtm-21691.

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Abstract This paper presents a product development process modeling and analysis technique using advanced simulation. The model computes the probability distribution of lead time in a resource-constrained project network where iterations take place among sequential, parallel and overlapped tasks. The model uses the design structure matrix representation to capture the information flows between tasks. In each simulation run, the expected durations of tasks are initially sampled using the Latin Hypercube Sampling method and decrease over time as the model simulates the progress of dynamic stochastic processes. It is assumed that the rework of a task occurs for the following reasons: (1) new information is obtained from overlapped tasks after starting to work with preliminary inputs, (2) inputs change when other tasks are reworked, and (3) outputs fail to meet established criteria. The model can be used for better project planning and control by identifying leverage points for process improvements and evaluating alternative planning and execution strategies. An industrial example is used to illustrate the utility of the model.
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Zhang, Lianfeng, Jianxin Jiao, and Petri Helo. "Integrated Product and Process Family Data Modeling for Product Lifecycle Management." In 2006 IEEE International Conference on Industrial Informatics. IEEE, 2006. http://dx.doi.org/10.1109/indin.2006.275612.

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Nilsson, Patrik, and Bjo¨rn Fagerstro¨m. "Integrated Product and Process Modelling." In ASME 2003 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/detc2003/dtm-48656.

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This paper presents a model for integrated product and process modeling. The aim is to investigate how product and process related information could be structured and managed in order to bridge the gap between the product and the process. Integrated product and process modeling is an important basis for concurrent engineering, as it provides a shared representation of the evolving design. First, an introduction to product modeling is discussed. Then, the proposed model, theoretically based on chromosome model, is presented. Second, process modeling is discussed, and more common tools/methods for process modeling are presented. Third, and finally, an industrial case study is presented, where the proposed model has been applied and evaluated in commercial software.
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Geuss, Hartwich. "Optimizing the Product Design Process by Computer Aided Ergonomics." In Digital Human Modeling For Design And Engineering Conference & Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1998. http://dx.doi.org/10.4271/981310.

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Daniel Sinnhofer, Andreas, Christian Kreiner, and Christian Kreiner. "varBPMA Product Line for Creating Business Process Model Variants." In Fifth International Symposium on Business Modeling and Software Design. SCITEPRESS - Science and and Technology Publications, 2015. http://dx.doi.org/10.5220/0005886901840191.

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Palaniswamy, S., and N. Singh. "Simulation based approach to modeling product and process interactions." In Innovation in Technology Management. The Key to Global Leadership. PICMET '97. IEEE, 1997. http://dx.doi.org/10.1109/picmet.1997.653736.

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Sutherland, John W., and William J. Zdeblick. "Modeling the Thread Chasing Process for Improved Product Quality." In Earthmoving Industry Conference & Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1992. http://dx.doi.org/10.4271/920919.

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Zhang, Xu, Yadong Sun, Lijuan Wang, and Dehao Xu. "Product model-based design process modeling in collaborative design." In EM). IEEE, 2010. http://dx.doi.org/10.1109/ieem.2010.5674307.

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Reports on the topic "Process and Product Modeling"

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Lyons, Kevin W., Michael R. Duffey, and Richard C. Anderson. Product realization process modeling:. Gaithersburg, MD: National Institute of Standards and Technology, 1995. http://dx.doi.org/10.6028/nist.ir.5745.

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Ray, W. Harmon. New process modeling [sic], design, and control strategies for energy efficiency, high product quality, and improved productivity in the process industries. Final project report. Office of Scientific and Technical Information (OSTI), June 2002. http://dx.doi.org/10.2172/771265.

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Kellner, Marc I., and Gregory A. Hansen. Software Process Modeling. Fort Belvoir, VA: Defense Technical Information Center, May 1988. http://dx.doi.org/10.21236/ada197137.

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Hillaire, R., and C. Loucks. Self-tuning process monitoring system for process-based product. Office of Scientific and Technical Information (OSTI), February 1998. http://dx.doi.org/10.2172/658293.

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Bock, Conrad, XuanFang Zha, Hyo-Won Suh, and Jae-Hyun Lee. Ontological product modeling for collaborative design. Gaithersburg, MD: National Institute of Standards and Technology, 2009. http://dx.doi.org/10.6028/nist.ir.7643.

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Morari, M. Modeling for process control. Office of Scientific and Technical Information (OSTI), January 1991. http://dx.doi.org/10.2172/5951697.

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Kocks, U. F., J. D. Embury, A. J. Beaudoin, P. R. Dawson, S. R. MacEwen, and H. J. Mecking. Advanced deformation process modeling. Office of Scientific and Technical Information (OSTI), August 1997. http://dx.doi.org/10.2172/516981.

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Szlufarska, Izabela, Dane Morgan, and Todd Allen. Modeling Fission Product Sorption in Graphite Structures. Office of Scientific and Technical Information (OSTI), April 2013. http://dx.doi.org/10.2172/1082917.

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Comella-Dorda, Santiago, John Dean, Grace Lewis, Edwin Morris, Patricia Oberndorf, and Erin Harper. A Process for COTS Software Product Evaluation. Fort Belvoir, VA: Defense Technical Information Center, July 2004. http://dx.doi.org/10.21236/ada443491.

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Baker, Stuart W. SIDR Relative Weighted Product (RWP) Assignment Process. Fort Belvoir, VA: Defense Technical Information Center, July 1992. http://dx.doi.org/10.21236/ada255801.

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