Journal articles: 'Production system models'

1

Guseinova, T. N. "INNOVATION PRODUCTION MODELS." MGIMO Review of International Relations, no. 3(48) (June 28, 2016): 54–65. http://dx.doi.org/10.24833/2071-8160-2016-3-48-54-65.

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The article is dedicated to the study of the models of production of innovations at enterprise and state levels. The shift towards a new technology wave induces a change in systems of division of labour as well as establishment of new forms of cooperation that are reflected both in theory and practice of innovation policy and management. Within the scope of the research question we have studied different generation of innovation process, starting with simple linear models - "technology push" and "market pull" - and ending with a complex integrated model of open innovations. There are two organizational models of innovation production at the enterprise level: start-ups in the early stages of their development and ambidextrous organizations. The former are prone to linear models of innovation process, while the latter create innovation within more sophisticated inclusive processes. Companies that effectuate reciprocal ambidexterity stand out from all the rest, since together with start-ups, research and development centres, elements of innovation infrastructure and other economic agents operating in the same value chain they constitute the core of most advanced forms of national innovation systems, namely Triple Helix and Quadruple Helix systems. National innovation systems - models of innovation production at the state level - evolve into systems with a more profound division of labour that enable "line production" of innovations. These tendencies are closely related to the advent and development of the concept of serial entrepreneurship that transforms entrepreneurship into a new type of profession. International experience proves this concept to be efficient in various parts of the world. Nevertheless, the use of above mentioned models and concepts in national innovation system should be justified by socioeconomic conditions of economic regions, since they determine the efficiency of implementation of certain innovation processes and organizational designs at company and national system level.

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Matveykin, V. G., B. S. Dmitrievsky, N. S. Popov, and O. V. Dmitriyeva. "Integrated Models of Innovative Production System." Vestnik Tambovskogo gosudarstvennogo tehnicheskogo universiteta 22, no. 4 (2016): 550–58. http://dx.doi.org/10.17277/vestnik.2016.04.pp.550-558.

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Anyadike, CC, CC Mbajiorgu, and GN Ajah. "REVIEW OF AQUACULTURAL PRODUCTION SYSTEM MODELS." Nigerian Journal of Technology 35, no. 2 (April 2, 2016): 448. http://dx.doi.org/10.4314/njt.v35i2.29.

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Brunoe, Thomas Ditlev, Daniel Grud Hellerup Sørensen, Ann-Louise Andersen, and Kjeld Nielsen. "Framework for Integrating Production System Models and Product Family Models." Procedia CIRP 72 (2018): 592–97. http://dx.doi.org/10.1016/j.procir.2018.03.020.

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SCHMITT, THOMAS G., THEODORE KLASTORIN, and AVRAHAM SHTUB. "Production classification system: concepts, models and strategies." International Journal of Production Research 23, no. 3 (January 1985): 563–78. http://dx.doi.org/10.1080/00207548508904729.

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Ružarovský, Roman. "Direct Production from CAD Models Considering on Integration with CIM Flexible Production System." Applied Mechanics and Materials 474 (January 2014): 103–8. http://dx.doi.org/10.4028/www.scientific.net/amm.474.103.

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Production engineering is currently characterized with continuously changing and expanding, producers have to be flexible in this regard. It means that need to offer production possibilities, which can respond to the quick change. Engineering product development is focused on supporting CAD software; such systems are mainly used for product design. The integration of flexible manufacturing systems and subunits together with product design and of engineering is a possible solution for this issue. Product designers use different types of CAD systems that are incompatible with each other. To enter a new product, it is necessary to transform CAD data and re-enter into the production system used by the manufacturer. The solution is to generate NC data directly from a CAD model and transform the data uploading to control system of flexible manufacturing system. The integration of flexible manufacturing systems and subunits together with product design in CAD and of engineering is a possible solution for this issue. Integration is possible through the implementation of CIM systems. Such an explanation and finding a connection between CAD and production system ICIM 3000 from Festo Co. is engaged in the research project and this contribution.

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Shmyrin, A. M., N. M. Mishachev, and V. V. Semina. "Hierarchical Neighborhood Models for Ventilation System." International Journal of Engineering & Technology 7, no. 3.5 (July 7, 2018): 24. http://dx.doi.org/10.14419/ijet.v7i3.5.15194.

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Considering cement production, we deal with dust, associated with a non-optimal operation of the dust-free ventilation system in the clinker burning department. The optimally organized heating, ventilating, and air conditioning system in any type of production ensures the microclimate of the production premises, corresponding to the sanitary norms and rules, which contribute to the increase of the staff’s efficiency. In this paper, the questions of the neighborhood modeling of the heating, ventilating, and air conditioning system in the premises of the cement production shop are considered. A system for minimizing energy costs and reducing dust emission in the clinker burning shop is proposed, which allows increasing the environmental safety of production.

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Sarker, Bhaba R. "Optimum manpower models for a production system with varying production rates." European Journal of Operational Research 24, no. 3 (March 1986): 447–54. http://dx.doi.org/10.1016/0377-2217(86)90038-x.

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Halim, K. A., B. C. Giri, and K. S. Chaudhuri. "Fuzzy EPQ models for an imperfect production system." International Journal of Systems Science 40, no. 1 (January 2009): 45–52. http://dx.doi.org/10.1080/00207720802090427.

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Mazumdar, M., and A. Kapoor. "Stochastic models for power generation system production costs." Electric Power Systems Research 35, no. 2 (November 1995): 93–100. http://dx.doi.org/10.1016/0378-7796(95)00993-0.

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Attri, Rajesh, and Sandeep Grover. "A comparison of production system life cycle models." Frontiers of Mechanical Engineering 7, no. 3 (September 2012): 305–11. http://dx.doi.org/10.1007/s11465-012-0332-5.

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M., Mazumdar, and Kapoor A. "Stochastic models for power generation system production costs." Fuel and Energy Abstracts 37, no. 3 (May 1996): 197. http://dx.doi.org/10.1016/0140-6701(96)88739-x.

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13

White, Robin R. "198 Beef cattle support system modeling." Journal of Animal Science 98, Supplement_2 (November 1, 2020): 68–69. http://dx.doi.org/10.1093/jas/skz397.160.

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Abstract A model is a tool used to study the dynamics of a system when investigations on the system itself are difficult because of scope, scale, sensitivity, or other complexities. Beef cattle production in the United States is at least a 2- to 4-phase process, consisting of economic, social, environmental, and biological relationships. As such, modeling is a logical strategy to handle many research questions focused on systems responses of beef cattle production systems. There are a number of modeling tools that can be used to research beef cattle production settings, including but not limited to: nutrient requirement models, pasture models, farm system models, and life cycle assessments. Life cycle assessments are the broadest category of models and typically fall under the umbrella of static, deterministic, empirical models that encompass the entirety of the beef production system from manufacture of the inputs through production of the outputs. There are a number of life cycle assessments of beef cattle production systems and comparison of the outcome of these models is a strategy to discern how changes in one aspect of the production system affect all downstream processes. Farm system models can assess an individual economic enterprise or an entirety of a beef production system and typically are dynamic, mechanistic models of the interactions between cattle and their external environments. Several researchers have also established deterministic, empirical farm system models, or hybrids of these two model types. Pasture models can be independent of or tightly linked with farm system models. Most pasture models are dynamic, mechanistic models; however, deterministic, empirical models also exist. Pasture models typically seek to model plant/soil/water interactions. Finally, animal response models and nutrient requirement models can be used to represent animal/feed/management interactions. These models can be dynamic or static, deterministic or mechanistic.

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Maffei, Antonio, and Mauro Onori. "Evolvable Production Systems: Environment for New Business Models." Key Engineering Materials 467-469 (February 2011): 1592–97. http://dx.doi.org/10.4028/www.scientific.net/kem.467-469.1592.

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The increasing threats and opportunities, on the global markets, challenge today the company at several levels. The actual Manufacturing Systems becomes dramatic for the survival and prosperity of the organization. Agility, Sustainability and high rate of Re-usability are the main objectives of an “Evolvable Production System”. Task-specific and process-oriented modules with embedded intelligence, together with distributed control based on agent technology are the cornerstones of an EPS. The realization and management of this kind of systems entail an ontological approach due to their implicit complexity. The reference architecture is the key to canalize the underlying holism of an EPS towards an effective instantiation, which exploits the “Emergent Behavior”, the key driver of the Evolvability of a system. The issues related with the application of this view, such as dynamic link between product and system design as well as the management of a module repository, underline the weakness of present business models. Therefore a model for the emplacement of a System that follows the “Evolvable Paradigm” predicament has been produced in order to enable further studies. One of the conclusions of the work is the need for a more suitable approach to business by the main actors involved in the realization of an EPS. Sharing information and standards about product design and modules realization becomes a compulsory strategic choice.

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Poulisse, Nanda. "Models of Second Language Production." EUROSLA 6 55 (January 1, 1996): 151–59. http://dx.doi.org/10.1075/ttwia.55.12pou.

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The article discusses to what extent bilingual models of speech production can account for the fact that L2 speakers are generally, but not always, able to select LI words when speaking the LI and L2 words when speaking the L2. After a brief discussion of word selection in monolingual models of speech production, two bilingual models are presented. In one of these, LI and L2 systems form separate subsets which are activated in their entirety. In the other one there is only one network containing both LI and L2 items, and the language feature plays a role in activating individual lexical items. It is argued that the second representation has the advantage of being more efficient, because it allows one to explain the selection of a single LI word to be used in L2 speech without having to activate the entire LI system. The first model cannot give an efficient explanation for the language switches violating the matching principle proposed by Bierwisch & Schreuder (1993), which entails that a lemma is selected only if it includes all and only those of the semantic features contained in the chunk to be lexicalized. The article also addresses the chunking problem. Since there is no one-to-one correspondence between concepts and words, speakers need to cut up their messages into lexicalizable chunks. It is suggested that both LI and L2 speakers may follow an informed trial-and-error procedure based on their experiences with language(s) involved. Since there is no look-ahead, speakers do occasionally rum into lexical problems. In view of the matching principle, the only way to solve these problems is to go through the processes of conceptualization and chunking again.

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Micieta, Branislav, Jolanta Staszewska, Matej Kovalsky, Martin Krajcovic, Vladimira Binasova, Ladislav Papanek, and Ivan Antoniuk. "Innovative System for Scheduling Production Using a Combination of Parametric Simulation Models." Sustainability 13, no. 17 (August 24, 2021): 9518. http://dx.doi.org/10.3390/su13179518.

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The article deals with the design of an innovative system for scheduling piece and small series discrete production using a combination of parametric simulation models and selected optimization methods. An innovative system for solving production scheduling problems is created based on data from a real production system at the workshop level. The methodology of the innovative system using simulation and optimization methods deals with the sequential scheduling problem due to its versatility, which includes several production systems and due to the fact that in practice, several modifications to production scheduling problems are encountered. Proposals of individual modules of the innovative system with the proposed communication channels have been presented, which connect the individual elements of the created library of objects for solving problems of sequential production scheduling. With the help of created communication channels, it is possible to apply individual parameters of a real production system directly to the assembled simulation model. In this system, an initial set of optimization methods is deployed, which can be applied to solve the sequential problem of production scheduling. The benefit of the solution is an innovative system that defines the content of the necessary data for working with the innovative system and the design of output reports that the proposed system provides for production planning for the production shopfloor level. The DPSS system works with several optimization methods (CR—Critical Ratio, S/RO—Slack/Remaining Operations, FDD—Flow Due Date, MWKR—Most Work Remaining, WSL—Waiting Slack, OPFSLK/PK—Operational Flow Slack per Processing Time) and the simulation experiments prove that the most suitable solution for the FT10 problem is the critical ratio method in which the replaceability of the equipment was not considered. The total length of finding all solutions by the DPSS system was 1.68 min. The main benefit of the DPSS system is the combination of two effectively used techniques not only in practice, but also in research; the mentioned techniques are production scheduling and discrete computer simulation. By combining techniques, it is possible to generate a dynamically and interactively changing simulated production program. Subsequently, it is possible to decide in the emerging conditions of certainty, uncertainty, but also risk. To determine the conditions, models of production systems are used, which represent physical production systems with their complex internal processes. Another benefit of combining techniques is the ability to evaluate a production system with a number of emerging problem modifications.

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Gladkikh, T. D. "Power supply reliability models of oil production facilities." Omsk Scientific Bulletin, no. 177 (2021): 59–63. http://dx.doi.org/10.25206/1813-8225-2021-177-59-63.

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This paper presents power supply systems reliability models of oil production facilities. There are two types of electrical complexes: an electrical network with a consumer sensitive to voltage dips and an electrical network with a consumer with technological redundancy. A comprehensive analysis of the power supply system and the power consumer allowed us to clarify the reliability indicators and determine the direction of improving the power supply reliability to oil and associated petroleum gas production facilities

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Filho, João C. V. Hohendorff, and Denis J. Schiozer. "Effect of reservoir and production system integration on field production strategy selection." Oil & Gas Science and Technology – Revue d’IFP Energies nouvelles 73 (2018): 44. http://dx.doi.org/10.2516/ogst/2018042.

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In petroleum engineering studies, the integration of reservoir and production system models can improve production forecasts. As the integration increases computation time, it is important to assess when this integration is necessary and how to choose a suitable coupling methodology. This work analyzes the influence of this integration, for a petroleum field in the development phase, evaluating the effects on the production strategy parameters. We tested a benchmark model based on an offshore field in Brazil so we could validate the solution in a reference known model. This work continues the research of Von Hohendorff Filho and Schiozer (2014, 2017) and aims to improve step 11 of the 12-step reservoir development and management methodology by Schiozer et al. (2015). The solution is tested in a reference model. Using the integrated production system and reservoir models from step 11 of the methodology, we re-optimize the production strategy of a standalone production development, while evaluating net present value as the objective function. We adapted an assisted workflow to include the optimization of new variables, such as pipe diameters of the well systems and gathering systems, platform positions, and artificial lift application, and compared these with the production strategy obtained from the same benchmark in a standalone approach. Comparing the integrated standalone and integrated production strategies, we observed important changes that indicate the need to integrate reservoir and production models. The optimized integrated systems resulted in significantly increased net present values, maintaining the same oil recovery factor while requiring lower initial investment. We implemented the best integrated production strategy and the integrated production strategy derived from the standalone case in the reference model which, in this case, represents a real field (emulating a real situation). Integration in the implementation step impacted the production forecast more than the optimization step, demonstrating the benefits of integrating reservoir and production systems to increase project robustness.

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Rietman, E. A., D. J. Friedman, and E. R. Lory. "Pre-production results demonstrating multiple-system models for yield analysis." IEEE Transactions on Semiconductor Manufacturing 10, no. 4 (1997): 469–81. http://dx.doi.org/10.1109/66.641489.

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Windmark, Christina, and Carin Andersson. "Cost models of inbound logistics activities: supporting production system design." International Journal of Supply Chain and Operations Resilience 1, no. 2 (2015): 181. http://dx.doi.org/10.1504/ijscor.2015.069927.

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21

Kuehnle, Hermann. "A system of models contribution to production network (PN) theory." Journal of Intelligent Manufacturing 18, no. 5 (July 3, 2007): 543–51. http://dx.doi.org/10.1007/s10845-007-0062-4.

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Eckard, R. J., V. O. Snow, I. R. Johnson, and A. D. Moore. "The challenges and opportunities when integrating animal models into grazing system models for evaluating productivity and environmental impact." Animal Production Science 54, no. 12 (2014): 1896. http://dx.doi.org/10.1071/an14551.

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The intensification of livestock production has highlighted the importance of balancing production and the environmental impact in grazing systems. With the advent of more distributed computing power we have seen more complex models being developed, capable of simulating most aspects of a livestock production system. Where the modelling objective includes prediction of both productivity and environmental impacts, it is imperative to include appropriate consideration of the grazing animal in the simulation. This raises numerous challenges with respect to environmental impact modelling, including explicit treatment of nutrients in dung and urine, the prediction of grazing behaviour, dry matter intake and associated enteric methane loss. This paper discusses these challenges and opportunities when integrating animal models into grazing system models for evaluating productivity and environmental impact.

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Ouassou, Jabir Ali, Julian Straus, Marte Fodstad, Gunhild Reigstad, and Ove Wolfgang. "Applying Endogenous Learning Models in Energy System Optimization." Energies 14, no. 16 (August 7, 2021): 4819. http://dx.doi.org/10.3390/en14164819.

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Conventional energy production based on fossil fuels causes emissions that contribute to global warming. Accurate energy system models are required for a cost-optimal transition to a zero-emission energy system, which is an endeavor that requires a methodical modeling of cost reductions due to technological learning effects. In this review, we summarize common methodologies for modeling technological learning and associated cost reductions via learning curves. This is followed by a literature survey to uncover learning rates for relevant low-carbon technologies required to model future energy systems. The focus is on (i) learning effects in hydrogen production technologies and (ii) the application of endogenous learning in energy system models. Finally, we discuss methodological shortcomings of typical learning curves and possible remedies. One of our main results is an up-to-date overview of learning rates that can be applied in energy system models.

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Syrový, O., and V. Podpěra. "Simulation mathematical model of expert system for working processes management." Research in Agricultural Engineering 55, No. 1 (February 11, 2009): 1–9. http://dx.doi.org/10.17221/12/2008-rae.

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The elementary simulation mathematical models presented in this article are related with the sub-system Crop production of the expert system for the decision support in technological and working processes management and their optimisation. Along with this sub-system, the expert system also involves the sub-systems Livestock production and Material handling which is further divided into the parts Transport and Storage. The boundary between the individual parts of the expert system is usually a short-term or long-term material storage. The relative individual sub-systems are mutually connected through the information flow. For each of the sub-systems, specific simulation models are created. The simulation models in the expert system investigated replace the complex of general standards and norms used in other expert systems. The simulation models allow to take into consideration the concrete natural and production conditions (area, plots shape and inclination, soil type, transport routes length and surface, fertilisers doses, crops yields etc.) and also the technological systems utilised during the realisation of operations in working processes (technical, exploitation, energy, economical or energy means, attached vehicles, machines and equipment and method of their work) and the calculation of the parameters utilised. The simulation models also allow the creation of suitable working, and transport sets to choose their optimal variants for the given conditions. In comparison with the utilised standards and norms, the parameters computed through the simulation models significantly improve the data which represent the output from the expert system.

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Dyson, J. E. "Theoretical models of Herbig-Haro objects." Symposium - International Astronomical Union 122 (1987): 159–72. http://dx.doi.org/10.1017/s0074180900156293.

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A brief overview of the observational characteristics of HH objects is given. Current models for their production by the interaction of stellar winds and jets with interstellar gas are critically discussed. Models for two specific systems of HH objects, namely, the Orion HH objects and the HH46-47 system are described with reference to the general production mechanisms.

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Sciutto, S. J. "Air showers, hadronic models, and muon production." EPJ Web of Conferences 210 (2019): 02007. http://dx.doi.org/10.1051/epjconf/201921002007.

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We report on a study about some characteristics of muon production during the development of extended air showers initiated by ultra-high-energy cosmic rays. Using simulations with the recent new version of the AIRES air shower simulation system, we analyze and discuss on the observed discrepancies between experimental measurements and simulated data.

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Perry, David, and Benny Levikson. "Continuous production/inventory model with analogy to certain queueing and dam models." Advances in Applied Probability 21, no. 01 (March 1989): 123–41. http://dx.doi.org/10.1017/s0001867800017225.

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We consider two storage/production systems in which items are produced continuously over time with fixed rate. In the first system items have infinite lifetime, while in the second system the lifetime of the items are finite and fixed. The inventory level distributions and other important functionals associated with these storage systems are derived. This derivation is accomplished by an analogy existing between the storage systems and certain queueing systems and a finite dam model. Optimization problems connected with these systems are also considered.

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Perry, David, and Benny Levikson. "Continuous production/inventory model with analogy to certain queueing and dam models." Advances in Applied Probability 21, no. 1 (March 1989): 123–41. http://dx.doi.org/10.2307/1427200.

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We consider two storage/production systems in which items are produced continuously over time with fixed rate. In the first system items have infinite lifetime, while in the second system the lifetime of the items are finite and fixed. The inventory level distributions and other important functionals associated with these storage systems are derived. This derivation is accomplished by an analogy existing between the storage systems and certain queueing systems and a finite dam model. Optimization problems connected with these systems are also considered.

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Hanigan, Mark D., and Veridiana L. Daley. "Use of Mechanistic Nutrition Models to Identify Sustainable Food Animal Production." Annual Review of Animal Biosciences 8, no. 1 (February 15, 2020): 355–76. http://dx.doi.org/10.1146/annurev-animal-021419-083913.

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To feed people in the coming decades, an increase in sustainable animal food production is required. The efficiency of the global food production system is dependent on the knowledge and improvement of its submodels, such as food animal production. Scientists use statistical models to interpret their data, but models are also used to understand systems and to integrate their components. However, empirical models cannot explain systems. Mechanistic models yield insight into the mechanism and provide guidance regarding the exploration of the system. This review offers an overview of models, from simple empirical to more mechanistic models. We demonstrate their applications to amino acid transport, mass balance, whole-tissue metabolism, digestion and absorption, growth curves, lactation, and nutrient excretion. These mechanistic models need to be integrated into a full model using big data from sensors, which represents a new challenge. Soon, training in quantitative and computer science skills will be required to develop, test, and maintain advanced food system models.

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Mishchenko, A. V., and A. V. Pilyugina. "Dynamic Models of Research and Manufacturing System Management." Herald of the Bauman Moscow State Technical University. Series Instrument Engineering, no. 2 (125) (April 2019): 56–75. http://dx.doi.org/10.18698/0236-3933-2019-2-56-75.

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dynamic models, research and manufacturing systems, capacity, conveyor systems, uncertainty, marginal profitabilityThe paper considers dynamic models of resource management in manufacturing systems. Such system operating benefits largely depend on the rational use of resources such as the production apparatus, human resources, borrowed and own funds. The importance of scientific and practical problem of management manifests itself in the aspects of management automation based on the development of mathematical models optimizing the activity in accordance with the selected criteria and allowing obtaining well-founded decisions for the use of production and financial resources. The manufac-turing company management system based on the principles of conveyor processing applications is considered (applications in the broad sense are materials, work in progress, data, documents of computing and information centers, etc.). The equations describing the operation of conveyor systems are presented. The methods of resource allocation based on the criterion of maximizing the total volume of processed applications and the criterion of maximizing the marginal income for the policy period are considered. The application frame of these models for interval parameter settings in the conditions of initial data uncertainty with allowance for the attraction of debt financing is investigated. The analysis of stability of solutions is performed by means of economic and mathematical modeling

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Starikov, Evgeniy, Marina Evseeva, and Irina Tkachenko. "Digital Technologies in the Smart Production Management System." SHS Web of Conferences 93 (2021): 01024. http://dx.doi.org/10.1051/shsconf/20219301024.

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The article analyzes the possibility of using such digital technologies as the Industrial Internet of Things (IIoT), Big Data and the creation of models of digital twins in the formation of intelligent management systems for "smart" production within the framework of the concept of digital transformation of the manufacturing sector Industry 4.0. The essence and features of these technologies, problematic aspects of their implementation in real production enterprises are considered. The concept of the functional structure of the digital production management system of a "smart" enterprise based on the digital twin model is proposed. The conclusion is made about the integrating role of technologies for the development and application of digital twin models in the construction of intelligent control systems for "smart" production.

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Rak, Tomasz. "Modeling Web Client and System Behavior." Information 11, no. 6 (June 24, 2020): 337. http://dx.doi.org/10.3390/info11060337.

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Web systems are becoming more and more popular. An efficiently working network system is the basis for the functioning of every enterprise. Performance models are powerful tools for performance prediction. The creation of performance models requires significant effort. In the article, we want to present various performance models of customer and Web systems. In particular, we want to examine a system behaviour related to different flow routes of clients in the system. Therefore we propose Queueing Petri Nets, the new modeling methodology for dealing with performance issues of production systems. We follow the simulation-based approach. We consider 25 different models to check performance. Then we evaluate them based on the proposed metrics. The validation results show that the model is able to predict the performance with a relative error lower than 20%. Our evaluation shows that prepared models can reduce the effort of production system preparation. The resulting performance model can predict the system behaviour in a particular layer at the indicated load.

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Krenczyk, Damian. "Automatic Generation Method of Simulation Model for Production Planning and Simulation Systems Integration." Advanced Materials Research 1036 (October 2014): 825–29. http://dx.doi.org/10.4028/www.scientific.net/amr.1036.825.

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In the paper the method of integration of production planning and simulation systems has been presented. An automatic generation method of production systems models has been implemented to integrate the Production Order Verification System (SWZ) for multi-assortment, concurrent production planning) and Enterprise Dynamics simulation system. Submitted methodology allowed the direct generation of simulation models for production systems with the use of data obtained from PPC systems, regardless of the production system structure, flow topology of the production processes and the amount of resources and production orders. Generation of simulation models is performed automatically, allowing the omission of time-and labor-consuming process of building a simulation. In the process of generation of the simulation models, methods of data mapping, transformation and exchange, between heterogeneous computer systems (PPC/DES) using neutral formats and data storing (XML) in conjunction with an intermediate neutral data model have been used. The result of transformation is the input file for simulation systems, containing information about the production system model, together with control procedures. Based on the described methodology, operation algorithms have been developed and the computer software RapidSim, that integrates PPC and DES systems has been presented.

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Ilic, Oliver, and Milic Radovic. "Models of production runs for multiple products in flexible manufacturing system." Yugoslav Journal of Operations Research 21, no. 2 (2011): 307–24. http://dx.doi.org/10.2298/yjor1102307i.

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How to determine economic production runs (EPR) for multiple products in flexible manufacturing systems (FMS) is considered in this paper. Eight different although similar, models are developed and presented. The first four models are devoted to the cases when no shortage is allowed. The other four models are some kind of generalization of the previous ones when shortages may exist. The numerical examples are given as the illustration of the proposed models.

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Smith, Terence R., W. A. V. Clark, and John W. Cotton. "Deriving and Testing Production System Models of Sequential Decision-Making Behavior." Geographical Analysis 16, no. 3 (September 3, 2010): 191–222. http://dx.doi.org/10.1111/j.1538-4632.1984.tb00810.x.

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Halim, K. A., B. C. Giri, and K. S. Chaudhuri. "Fuzzy production planning models for an unreliable production system with fuzzy production rate and stochastic/fuzzy demand rate." International Journal of Industrial Engineering Computations 2, no. 1 (January 1, 2011): 179–92. http://dx.doi.org/10.5267/j.ijiec.2010.05.001.

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Иванников, Valeriy Ivannikov, Сушков, Sergey Sushkov, Никонов, and Vadim Nikonov. "DEVELOPMENT OF MODELS OF TRANSPORT AND DISTRIBU-TIVE TASKS FOR VARIOUS CATEGORIES OF FOREST AREAS." Voronezh Scientific-Technical Bulletin 4, no. 2 (June 30, 2015): 57–61. http://dx.doi.org/10.12737/14385.

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In article the system of transport tasks (distributive, systems of drawing up balance of production and consumption of forest products), and also problems of optimization of planning of placement and concentration of production of forest products is considered. Various options of statement of tasks depending on power both the procuring, and processing productions are considered. As criteria of op-timization expensive indicators which need to be minimized are applied.

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Khabbazi, Mahmood Reza, Jan Wikander, Mauro Onori, Antonio Maffei, and De-Jiu Chen. "Module-based quality system functionality evaluation in production logistics." Journal of Industrial Engineering and Management 9, no. 2 (April 25, 2016): 310. http://dx.doi.org/10.3926/jiem.1509.

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Purpose: This paper addresses a comprehensive modeling and functionality evaluation of a module-based quality system in production logistics at the highest domain abstract level of business processes.Design/methodology/approach: All domain quality business processes and quality data transactions are modeled using BPMN and UML tools and standards at the business process and data modeling. A modular web-based prototype is developed to evaluate the models addressing the quality information system functionality requirements and modularity in production logistics through data scenarios and data queries.Findings: Using the object-oriented technique in design at the highest domain level, the proposed models are subject further development in the lower levels for the implementing case. The models are specifically able to manipulate all quality operations including remedy and control in a lot-based make-to-order production logistics system as an individual module.Practical implications: Due to the specification of system as domain design structure, all proposed BPMs, data models, and the actual database prototype are seen referential if not a solution as a practical “to-be” quality business process re-engineering template. Originality/value: this paper sets out to provide an explanatory approach using different practical technique at modeling steps as well as the prototype implementation.

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Oborski, Przemysław. "Integrated Monitoring System of Production Processes." Management and Production Engineering Review 7, no. 4 (December 1, 2016): 86–96. http://dx.doi.org/10.1515/mper-2016-0039.

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Abstract Integrated monitoring system for discrete manufacturing processes is presented in the paper. The multilayer hardware and software reference model was developed. Original research are an answer for industry needs of the integration of information flow in production process. Reference model corresponds with proposed data model based on multilayer data tree allowing to describe orders, products, processes and save monitoring data. Elaborated models were implemented in the integrated monitoring system demonstrator developed in the project. It was built on the base of multiagent technology to assure high flexibility and openness on applying intelligent algorithms for data processing. Currently on the base of achieved experience an application integrated monitoring system for real production system is developed. In the article the main problems of monitoring integration are presented, including specificity of discrete production, data processing and future application of Cyber-Physical-Systems. Development of manufacturing systems is based more and more on taking an advantage of applying intelligent solutions into machine and production process control and monitoring. Connection of technical systems, machine tools and manufacturing processes monitoring with advanced information processing seems to be one of the most important areas of near future development. It will play important role in efficient operation and competitiveness of the whole production system. It is also important area of applying in the future Cyber-Physical-Systems that can radically improve functionally of monitoring systems and reduce the cost of its implementation.

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Yakovyshin, O. A. "Improvement of management system of technological equipment for production of gasificable models." Litiyo i Metallurgiya (FOUNDRY PRODUCTION AND METALLURGY), no. 1 (April 10, 2019): 38–44. http://dx.doi.org/10.21122/1683-6065-2019-1-38-44.

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In the article on the basis of the conducted researches and available technical documentation on modern non-contact electric devices the approach to perfect a control system of heating element of equipment for the production of gasified models. The thermophysical features and mode of operation of heating elements used in equipment for the production of gasified models is given. The numerical value of the working temperature of the spiral of heating element is determined. It is shown that application of three phase Solid State Relays (SSR) increased the life of heating elements by an average of 400–450 hours. SSR in the systems for controlling the heating of liquid heat carrier of plants for the production of gasified models are promising.

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May, Marvin Carl, Andreas Kuhnle, and Gisela Lanza. "Digitale Produktion und intelligente Steuerung/Digital Production and Intelligent Production Control – Integrating digital and real-world production for adaptive and automated control." wt Werkstattstechnik online 110, no. 04 (2020): 255–60. http://dx.doi.org/10.37544/1436-4980-2020-04-89.

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Im Rahmen der stufenweisen Umsetzung von Industrie 4.0 erreicht die Vernetzung und Digitalisierung die gesamte Produktion. Den physischen Produktionsprozess nicht nur cyber-physisch zu begleiten, sondern durch eine virtuelle, digitale Kopie zu erfassen und zu optimieren, stellt ein enormes Potenzial für die Produktionssystemplanung und -steuerung dar. Zudem erlauben digitale Modelle die Anwendung intelligenter Produktionssteuerungsverfahren und leisten damit einen Beitrag zur Verbreitung optimierender adaptiver Systeme.   In the wake of implementing Industrie 4.0 both integration and digitalization affect the entire production. Physical production systems offer enormous potential for production planning and control through virtual, digital copies and their optimization, well beyond purely cyber-physical production system extensions. Furthermore, digital models enable the application of intelligent production control and hence contribute to the dissemination of adaptively optimizing systems.

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Danilin, Vacheslav I. "The Compamy’s Power Growth Model System." Economics of Contemporary Russia, no. 4 (December 31, 2020): 62–75. http://dx.doi.org/10.33293/1609-1442-2020-4(91)-62-75.

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When calculating the company's business plan, in many cases there is a problem of lack of resources to fully meet the demand for the company's products. In article (Danilin, 2019) the system of models of coordination of decisions between the leading divisions of the company was offered: production department, sales department, department of, financial department. However, the production department was presented in this article only by one model, and technological services were absent. In this article more detailed system of models for production department when calculating the production program is offered, and agreeing on the decision with model of technological service. The calculation of the production program (the company's capacity) and its growth is possible due to several areas: a) the development by the technology departments of short-term projects aimed at the implementation of resource consumption standards; b) the development by technology departments of additional production methods for manufacturing products or services, along with the main; c) additional acquisition of resources through investment; d) outsourcing of domestic semi-finished products. There were special models for each area that would reduce the level of increase in the company's ability to meet the demand for its production. The purpose of the article was to show an opportunity to create a model system out of them, allowing them to maximize the capacity of the production company within the framework of the existing investment opportunities. The scientific novelty is to develop the meta-historical basis for the sequence of implementation of individual models and to harmonize them with each other to solve the problem. The example shows that the use of these directions in a certain sequence allows to increase the power of the company and as close as possible to 100% of the satisfaction of demand.

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Wazed, M. A., S. Ahmed, Nukman Yusoff, and Nader Ale Ebrahim. "Models for Component Commonality in Multistage Production." Applied Mechanics and Materials 110-116 (October 2011): 258–66. http://dx.doi.org/10.4028/www.scientific.net/amm.110-116.258.

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Use of common parts for different products (commonality) is important methods for managing product variety and preserving competitiveness in the age of mass customization and supply chain competition. In literature, the advantages of inclusion of common components in a product family are well established. Unfortunately, most of the works have been conducted via simulation or conceptual thinking. The mathematical models in the premises are not adequate for production, planning and control in multistage production. This paper focuses on the advancement of venerable manufacturing resources planning models by incorporating the part commonality concept in a multiproduct, multi-period and multistage manufacturing system under a deterministic situation. The models are validated with established MRPII models. The material requirement schedule for the basic MRP II and proposed models are compared. It is really a good matching shown between the two schedules. The later bearing additional information of the location where to be available the parts in a time frame. The effects of commonality on cost, capacity and requirement schedule are discussed based on the outcomes of the mathematical models executed with the available live data.

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Abdikeev, Niyaz Mustjakimovich, Anton Alekseevich Losev, and Andrey Ivanovich Gaydamaka. "THE CONCEPT OF COMPETITIVE VALUE CHAINS IN PRODUCTION SYSTEMS AS AN INSTITUTIONAL STRUCTURE OPERATING ON NETWORK PRINCIPLES." Computational nanotechnology 6, no. 3 (September 30, 2019): 61–67. http://dx.doi.org/10.33693/2313-223x-2019-6-3-61-67.

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The Concept of competitive value chains in production systems, as an institutional structure operating on network principles, was the impetus for the development of a system of models of inter-industry digital platform for the management and optimization of cooperation of high-tech network production systems. The article describes the ways of integration into business processes of production systems of simulation and cognitive models. The practical implementation of the system of these models is a separate software product - an interdisciplinary digital platform for participants in the creation of new high-tech products and their components.

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Kelley, D. I., I. Colin Prentice, S. P. Harrison, H. Wang, M. Simard, J. B. Fisher, and K. O. Willis. "A comprehensive benchmarking system for evaluating global vegetation models." Biogeosciences Discussions 9, no. 11 (November 9, 2012): 15723–85. http://dx.doi.org/10.5194/bgd-9-15723-2012.

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Abstract. We present a benchmark system for global vegetation models. This system provides a quantitative evaluation of multiple simulated vegetation properties, including primary production; seasonal net ecosystem production; vegetation cover, composition and height; fire regime; and runoff. The benchmarks are derived from remotely sensed gridded datasets and site-based observations. The datasets allow comparisons of annual average conditions and seasonal and inter-annual variability, and they allow the impact of spatial and temporal biases in means and variability to be assessed separately. Specifically designed metrics quantify model performance for each process, and are compared to scores based on the temporal or spatial mean value of the observations and a "random" model produced by bootstrap resampling of the observations. The benchmark system is applied to three models: a simple light-use efficiency and water-balance model (the Simple Diagnostic Biosphere Model: SDBM), and the Lund-Potsdam-Jena (LPJ) and Land Processes and eXchanges (LPX) dynamic global vegetation models (DGVMs). SDBM reproduces observed CO2 seasonal cycles, but its simulation of independent measurements of net primary production (NPP) is too high. The two DGVMs show little difference for most benchmarks (including the inter-annual variability in the growth rate and seasonal cycle of atmospheric CO2), but LPX represents burnt fraction demonstrably more accurately. Benchmarking also identified several weaknesses common to both DGVMs. The benchmarking system provides a quantitative approach for evaluating how adequately processes are represented in a model, identifying errors and biases, tracking improvements in performance through model development, and discriminating among models. Adoption of such a system would do much to improve confidence in terrestrial model predictions of climate change impacts and feedbacks.

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Kurdve, Martin, Mats Zackrisson, Magnus Wiktorsson, and Ulrika Harlin. "Lean and green integration into production system models – experiences from Swedish industry." Journal of Cleaner Production 85 (December 2014): 180–90. http://dx.doi.org/10.1016/j.jclepro.2014.04.013.

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Shekarian, Ehsan, Ezutah Udoncy Olugu, Salwa Hanim Abdul-Rashid, and Eleonora Bottani. "A Fuzzy Reverse Logistics Inventory System Integrating Economic Order/Production Quantity Models." International Journal of Fuzzy Systems 18, no. 6 (January 21, 2016): 1141–61. http://dx.doi.org/10.1007/s40815-015-0129-x.

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van Noord, Michiel, Tomas Landelius, and Sandra Andersson. "Snow-Induced PV Loss Modeling Using Production-Data Inferred PV System Models." Energies 14, no. 6 (March 12, 2021): 1574. http://dx.doi.org/10.3390/en14061574.

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Snow-induced photovoltaic (PV)-energy losses (snow losses) in snowy and cold locations vary up to 100% monthly and 34% annually, according to literature. Levels that illustrate the need for snow loss estimation using validated models. However, to our knowledge, all these models build on limited numbers of sites and winter seasons, and with limited climate diversity. To overcome this limitation in underlying statistics, we investigate the estimation of snow losses using a PV system’s yield data together with freely available gridded weather datasets. To develop and illustrate this approach, 263 sites in northern Sweden are studied over multiple winters. Firstly, snow-free production is approximated by identifying snow-free days and using corresponding data to infer tilt and azimuth angles and a snow-free performance model incorporating shading effects, etc. This performance model approximates snow-free monthly yields with an average hourly standard deviation of 6.9%, indicating decent agreement. Secondly, snow losses are calculated as the difference between measured and modeled yield, showing annual snow losses up to 20% and means of 1.5–6.2% for winters with data for at least 89 sites. Thirdly, two existing snow loss estimation models are compared to our calculated snow losses, with the best match showing a correlation of 0.73 and less than 1% bias for annual snow losses. Based on these results, we argue that our approach enables studying snow losses for high numbers of PV systems and winter seasons using existing datasets.

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FARIA, JOSE, and EUSEBIO NUNES. "RELIABILITY ENGINEERING OF LARGE JIT PRODUCTION SYSTEMS." International Journal of Reliability, Quality and Safety Engineering 19, no. 03 (June 2012): 1250011. http://dx.doi.org/10.1142/s0218539312500118.

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This paper introduces the rationale and the fundamental elements and algorithms of a reliability engineering methodology combining analytical and simulation tools, and discusses its application to the design of a large, multi-cell and heterogeneous production system with just-in-time (JIT) deliveries. In order to cope with the inherent complexity of such analysis, a two level hierarchical modeling and evaluation framework was developed. Local models are first obtained from the failure and repair processes of the manufacturing equipment. Then, these models are combined with the failure propagation delays introduced by the work-in-process buffers in order to obtain the system level model. The evaluation algorithm is able to deal with reliability models containing stochastic processes with generalized distributions. This fundamental requirement comes from the fact that repair and failure propagation processes typically present hyper-exponential distributions, e.g., lognormal distributions, that cannot be assessed using the conventional reliability techniques. The second part of the paper addresses several design issues of the production system that directly impact the reliability of the deliveries, and explains how the behavioral and structural characteristics of JIT production systems were explored in order to implement effective evaluation algorithms.

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Kelley, D. I., I. C. Prentice, S. P. Harrison, H. Wang, M. Simard, J. B. Fisher, and K. O. Willis. "A comprehensive benchmarking system for evaluating global vegetation models." Biogeosciences 10, no. 5 (May 17, 2013): 3313–40. http://dx.doi.org/10.5194/bg-10-3313-2013.

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Abstract. We present a benchmark system for global vegetation models. This system provides a quantitative evaluation of multiple simulated vegetation properties, including primary production; seasonal net ecosystem production; vegetation cover; composition and height; fire regime; and runoff. The benchmarks are derived from remotely sensed gridded datasets and site-based observations. The datasets allow comparisons of annual average conditions and seasonal and inter-annual variability, and they allow the impact of spatial and temporal biases in means and variability to be assessed separately. Specifically designed metrics quantify model performance for each process, and are compared to scores based on the temporal or spatial mean value of the observations and a "random" model produced by bootstrap resampling of the observations. The benchmark system is applied to three models: a simple light-use efficiency and water-balance model (the Simple Diagnostic Biosphere Model: SDBM), the Lund-Potsdam-Jena (LPJ) and Land Processes and eXchanges (LPX) dynamic global vegetation models (DGVMs). In general, the SDBM performs better than either of the DGVMs. It reproduces independent measurements of net primary production (NPP) but underestimates the amplitude of the observed CO2 seasonal cycle. The two DGVMs show little difference for most benchmarks (including the inter-annual variability in the growth rate and seasonal cycle of atmospheric CO2), but LPX represents burnt fraction demonstrably more accurately. Benchmarking also identified several weaknesses common to both DGVMs. The benchmarking system provides a quantitative approach for evaluating how adequately processes are represented in a model, identifying errors and biases, tracking improvements in performance through model development, and discriminating among models. Adoption of such a system would do much to improve confidence in terrestrial model predictions of climate change impacts and feedbacks.

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Journal articles on the topic 'Production system models'

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