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Статті в журналах з теми "Discrete production system"

Автор: Grafiati

Опубліковано: 28 травня 2022

Оновлено: 31 липня 2025

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1

Ding, Xiang Qian, Wei Dong Zhang, and Rui Chun Hou. "Research of Discrete Manufacturing Industry Production Control System Based on RFID Technology." Advanced Materials Research 926-930 (May 2014): 1493–96. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.1493.

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Анотація:

In view of the current discrete manufacturing workshop production process control problem of poor real-time performance, reliability, this paper proposes a discrete manufacture based on rfid technology workshop production process control system solutions. For discrete manufacturing enterprise workshop layer of the production process control system emphasizes the manufacturing process of real-time data acquisition, validity and enforceability of the production plan. Developed a discrete manufacturing process control system based on RFID, provides the foundation for just-in-time production of di

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2

Hu, Ju Fang, and Chun Ru Xiong. "A Manufacturing Execution System for Discrete Industry." Applied Mechanics and Materials 519-520 (February 2014): 1585–88. http://dx.doi.org/10.4028/www.scientific.net/amm.519-520.1585.

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Manufacturing Execution System (MES) is widely used in enterprise production scene. But most manufacturing execution systems are expensive and mostly for the continuous production-oriented enterprises. Thus, they are hardly applied to a large number of existing discrete manufacturing enterprises. For discrete manufacturing companies, on-site processing is complex such as the planning and scheduling. This paper proposes a concept that is the use of advanced enterprise information management and designs a CIMS technology for discrete industry. The system is capable of real-time monitoring of dis

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3

Yamaba, Hisaaki, and Shigeyuki Tomita. "A Design Support System for Discrete Production Systems with AGVs." KAGAKU KOGAKU RONBUNSHU 36, no. 2 (2010): 127–35. http://dx.doi.org/10.1252/kakoronbunshu.36.127.

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4

Hu, Qing, Yu Ping Qui, and Lian Shi Lin. "Discrete Enterprise Data Acquisition System Based on RFID Technology." Advanced Materials Research 338 (September 2011): 743–47. http://dx.doi.org/10.4028/www.scientific.net/amr.338.743.

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Анотація:

Considering the discrete enterprise manufacturing process and the production management problems caused by information and management gaps between enterprise planning and field process control，RFID was introduced into the manufacturing production for discrete enterprise，in which tags were used to track work in process．Proposed an discrete enterprise production process data acquisition system design method based RFID technology. Analysis the data acquisition system basic components of production actual information offered by the system, System structure and major functional modules were charact

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5

Abyshev, O. A., E. I. Yablochnikov, and D. A. Zakoldaev. "Service-oriented architectural model of discrete production system." Izvestiâ vysših učebnyh zavedenij. Priborostroenie 66, no. 1 (2023): 43–55. http://dx.doi.org/10.17586/0021-3454-2023-66-1-43-55.

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6

Zhang, Yangyang, Haiting Xu, Dong Wang, and Bo Xu. "Design of Universal Platform Architecture for Complex Discrete Storage System." Journal of Electronic Research and Application 9, no. 1 (2025): 209–17. https://doi.org/10.26689/jera.v9i1.9451.

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The flexible satellite batch production line is a complex discrete production system with multiple cross-disciplinary fields and mixed serial parallel tasks. As the source of the satellite batch production line process, the warehousing system has urgent needs such as uncertain production scale and rapid iteration and optimization of business processes. Therefore, the requirements and architecture of complex discrete warehousing systems such as flexible satellite batch production lines are studied. The physical system of intelligent equipment is abstracted as a digital model to form the underly

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7

Cai, Hu, Jiafu Wan, and Baotong Chen. "Digital Twin-Driven Multi-Factor Production Capacity Prediction for Discrete Manufacturing Workshop." Applied Sciences 14, no. 7 (2024): 3119. http://dx.doi.org/10.3390/app14073119.

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Traditional capacity forecasting algorithms lack effective data interaction, leading to a disconnection between the actual plan and production. This paper discusses the multi-factor model based on a discrete manufacturing workshop and proposes a digital twin-driven discrete manufacturing workshop capacity prediction method. Firstly, this paper gives a system framework for production capacity prediction in discrete manufacturing workshops based on digital twins. Then, a mathematical model is described for discrete manufacturing workshop production capacity under multiple disturbance factors. Fu

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8

Zheng, Jun Jia, Hong Jun Liu, and Shao Yong Zeng. "The Application of Particle Swarm Optimization Algorithm in the Production Scheduling Modeling of ERP-Based." Applied Mechanics and Materials 130-134 (October 2011): 4092–97. http://dx.doi.org/10.4028/www.scientific.net/amm.130-134.4092.

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Job shop scheduling in the production management module is one of the core of ERP system. To solve the problem, that is, to discretely manufacture the multi-process routes and the multi-objective job shop scheduling, this paper propose an optimized algorithm of the improved particle swarm that is used to establish the mathematical model which turns in the direction of the production scheduling system of ERP-based. And with the example of an engineering machinery manufacturing enterprise, it deduces a model’s realization process in the multi-objective shop scheduling in the discrete manufacturi

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9

Wang, Xihong, Mitsuhiro Nakamura, and Takahiro Nakajima. "1105 Development of production scheduling system with batch-discrete hybrid system." Proceedings of Manufacturing Systems Division Conference 2007 (2007): 15–16. http://dx.doi.org/10.1299/jsmemsd.2007.15.

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10

Zitnikov, Anton, Abdullah al Noman, Aaron Heuermann, and Klaus-Dieter Thoben. "Resource-efficient condition determination through discrete production system monitoring." IFAC-PapersOnLine 58, no. 19 (2024): 325–30. http://dx.doi.org/10.1016/j.ifacol.2024.09.208.

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11

Prno, I., and J. Kníže. "System Modelling of Discrete Production Processes in Woodworking Industries." IFAC Proceedings Volumes 19, no. 12 (1986): 59–63. http://dx.doi.org/10.1016/s1474-6670(17)59589-0.

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12

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

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Анотація:

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

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13

Novika, Nadya, Suroto Suroto, and Bambang Hendriya Guswanto. "MASALAH NILAI EIGEN ATAS ALJABAR MAX-PLUS PADA SISTEM PRODUKSI BULU MATA." Prismatika: Jurnal Pendidikan dan Riset Matematika 6, no. 1 (2023): 1–14. http://dx.doi.org/10.33503/prismatika.v6i1.3348.

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A discrete event system is a system whose behavior is determined by events and their events change at discrete times. The eyelash production system at PT Bio Takara Purwokerto is a discrete event system problem and can be expresses in a max-plus linear problem. By using the power algorithm, it is determined eigen values and eigen vectors over max-plus algebra which will be used as production time periodization. The results obtained that the periodic time for the eyelash production system at PT Bio Takara Purwokerto is 78.488 minutes. Based on this periodic time, we can then obtain the time e

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14

Chai, Shu Feng, Su Jun Luo, and Li Jie Zhang. "Study On Simulation Of The Main Shaft Production Line." Advanced Materials Research 472-475 (February 2012): 2076–79. http://dx.doi.org/10.4028/www.scientific.net/amr.472-475.2076.

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Since modern production system is a highly complicated discrete manufacturing system, it is very difficult to design the production line by traditional means. However, through building model of production system in virtual environment, analyzing and evaluating production system performance based on system simulating technology, the production system’s parameter and configuration can be optimized ahead of production plan to optimize production process and improve production efficiency. In this paper, the main shaft production line simulation model is constructed based on the object oriented dis

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15

Cao, Yan, Li Wei Jia, Sen Cao, and Yu Bai. "Visualized Modeling and Simulation of Manufacturing Execution System in Dynamic Job-Shop Scheduling." Applied Mechanics and Materials 496-500 (January 2014): 1498–501. http://dx.doi.org/10.4028/www.scientific.net/amm.496-500.1498.

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Manufacturing Execution System (MES) is a job-shop production oriented management information system and the bridge between production plan management layer and job-shop control layer in an enterprise. Job-shop scheduling is the core module of MES, which direct affects the efficiency of production and management in the enterprise. According to the characteristics of discrete production management, a job-shop production scheduling system is presented that adapts to multi-variety small-batch production. A MES architecture for dynamic discrete production and its core modules are presented. Then,

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16

Butusov, N. O., M. N. Buza, and A. G. Alekhin. "DEVELOPMENT OF AN AUTOMATED PRODUCTION MANAGEMENT SYSTEM OF DISCRETE TYPE." Izvestia Volgograd State Technical University, no. 1 (2022): 51–53. http://dx.doi.org/10.35211/1990-5297-2022-1-260-51-53.

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17

Haller, Julian, Bharath Kumar, Amon Göppert, and Robert H. Schmitt. "A System Dynamics Stability Model for Discrete Production Ramp-Up." Systems 12, no. 12 (2024): 575. https://doi.org/10.3390/systems12120575.

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Анотація:

Manufacturing companies are increasingly challenged to deliver customizable products with shorter time to market and higher quality while adhering to sustainability requirements. To meet these challenges, the frequency and importance of production ramp-ups will increase in the future. However, most ramp-ups still fail to meet targets due to unpredictable equipment failures, operator errors, and system complexity. We propose a system dynamics model that captures the unique dynamics of ramp-up phases by integrating stability and disturbance factors that influence the key performance indicators o

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18

Kim, Bokang, and Sooyoung Kim. "Application of genetic algorithms for scheduling batch-discrete production system." Production Planning & Control 13, no. 2 (2002): 155–65. http://dx.doi.org/10.1080/09537280110069658.

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19

Caramihai, S. I., and H. Aila. "Supervisory Synthesis Optimization for Timed Discrete Event Systems - Application to a Production System." IFAC Proceedings Volumes 30, no. 19 (1997): 179–85. http://dx.doi.org/10.1016/s1474-6670(17)42296-8.

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20

Anggara Purba, Reno Dias, M. Iqbal Sabit, and Joko Sulistio. "Evaluation of SME (Small Medium Enterprise) production system with discrete system simulation method." MATEC Web of Conferences 154 (2018): 01067. http://dx.doi.org/10.1051/matecconf/201815401067.

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Анотація:

Like manufacturing companies that have flowshop production lines, SME facing the amount of flow time and makespan. Unfulfilled production targets, buildup on some machines that result in other machines being idle, increasing waiting times across multiple machines, and poor performance of workers are a series of problems facing SME. This article uses a discrete system simulation method to analyze and evaluate SME production lines to improve performance. Simulation is an appropriate tool used when experiments are needed in order to find the best response from system components. From the results

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21

CHENGAR, O. V., V. I. SHEVCHENKO, A. A. MALITSKAYA, and D. D. SHEVCHENKO. "SYSTEM FOR SIMULATING THE OPERATION OF AN AUTOMATED WAREHOUSE IN DISCRETE PRODUCTION." Fundamental and Applied Problems of Engineering and Technology, no. 6 (2021): 150–60. http://dx.doi.org/10.33979/2073-7408-2021-350-6-150-160.

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The article discusses the functions of the warehouse subsystem of industrial production of a discrete type, describes the graph and simulation models of the functioning of an automated warehouse of a small–scale machine–building enterprise. The structure of the software implementation of the subsystem is proposed. As a result of a computer experiment, the adequacy of the presented models was verified. Variants of possible experimental studies of the modeling system to improve the efficiency of discrete production processes are proposed.

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22

Zhang, Qinglei, Yang Wei, Zhen Liu, Jianguo Duan, and Jiyun Qin. "A Framework for Service-Oriented Digital Twin Systems for Discrete Workshops and Its Practical Case Study." Systems 11, no. 3 (2023): 156. http://dx.doi.org/10.3390/systems11030156.

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To address issues in discrete manufacturing workshops, such as the difficulty for management personnel to coordinate workshop production and the challenge of visualizing and supervising a massive amount of temporary data, this paper proposes a service-oriented digital-twin-system framework for discrete workshops using the industrial IoT platform as the system-service platform to solve the problems of the opaque monitoring of operators in discrete workshops, the low interactivity of 2D monitoring systems, and the difficulty of the visual monitoring of workshop data. Firstly, the current situati

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23

Gu, Jian, and Wei Min Mao. "A Production Scheduling Framework Integrated with Simulation Module." Advanced Materials Research 602-604 (December 2012): 1831–34. http://dx.doi.org/10.4028/www.scientific.net/amr.602-604.1831.

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It is necessary to achieve high system performances in terms of throughput rate and service level in today’s business environment. This can be achieved by implementing efficient and effective production planning methods complemented with precise and fast scheduling predictions. A framework is proposed to integrate real-time production data, scheduling mechanisms and simulation for providing realistic scheduling policies that could be used for operational and tactical decision-making. The focus is on the use of discrete event simulation utilizing relevant shop floor data, provided by an ERP sys

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24

He, Hai, Jian Zhou, Wenqiang Hu, and Yuhui Wang. "Research on reconfigurable systems in discrete manufacturing workshops." Journal of Physics: Conference Series 2842, no. 1 (2024): 012071. http://dx.doi.org/10.1088/1742-6596/2842/1/012071.

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Abstract With the development of smart manufacturing, the demand for personalized production has made reconfigurable systems in the manufacturing industry a focal point of research and application in high-end manufacturing. The paper analyzes the current status of the manufacturing industry and the challenges of reconfigurable technology. Furthermore, it designs and develops a reconfigurable system for discrete manufacturing of automotive components. The paper focuses on issues such as creating reconfigurable models, designing adaptive reconfiguration algorithms, accomplishing the creation of

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25

Aulia, Lathifatul, Widowati Widowati, R. Heru Tjahjana, and Sutrisno Sutrisno. "MODELING PREDICTIVE TRACKING CONTROL FOR MAX-PLUS LINEAR SYSTEMS IN MANUFACTURING." Journal of Fundamental Mathematics and Applications (JFMA) 3, no. 2 (2020): 133–47. http://dx.doi.org/10.14710/jfma.v3i2.8605.

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Анотація:

Discrete event systems, also known as DES, are class of system that can be applied to systems having an event that occurred instantaneously and may change the state. It can also be said that a discrete event system occurs under certain conditions for a certain period because of the network that describes the process flow or sequence of events. Discrete event systems belong to class of nonlinear systems in classical algebra. Based on this situation, it is necessary to do some treatments, one of which is linearization process. In the other hand, a Max-Plus Linear system is known as a system that

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26

Wang, Hong Jun, Ting Dong, Jing Zhang, and Hai Yan Wang. "Simulation and Optimization of the Camshaft Production Line Based on Petri Net." Advanced Materials Research 139-141 (October 2010): 1506–9. http://dx.doi.org/10.4028/www.scientific.net/amr.139-141.1506.

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Анотація:

With the development of scientific and technology, the automotive industries competition is becoming more and tougher. The camshaft production system is an important part of the engine manufacturing. The production line productivity and characteristic are affected by many practical factors of the workshop. It’s a complex discrete manufacturing system somehow. In this paper, the production line model is presented based on Petri net. Then the mapping relationship is established between the Petri net model and the eM-Plant discrete system model. The discrete simulation model of production line is

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27

Chernik, Kristina Nikolaevna, and Vladimir Andreevich Lozovoy. "Analysis of the productivity of discrete action machines used for mechanized planting of seedlings." Agrarian Scientific Journal, no. 1 (February 6, 2024): 136–44. http://dx.doi.org/10.28983/asj.y2024i1pp136-144.

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Today in the world there are a large number of forest planters, devices and units. All of them perform one technological process - they prepare a seat for planting material, feed a seedling into it and close up the roots with soil. Mechanized landing technology can be divided into two types: discrete action and continuous action. One of the differences between these planting technologies is the implementation of the preparation of the seat: in the form of a continuous furrow (continuous action), or discretely located holes (discrete action). Since the need for mechanization of tree planting in

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28

Li, Wan Gao, Xiao Le Liu, and De Chang Sun. "Research on Visual Production Process Control System Oriented to Discrete Manufacturing." Key Engineering Materials 474-476 (April 2011): 1914–19. http://dx.doi.org/10.4028/www.scientific.net/kem.474-476.1914.

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Анотація:

Firstly, the requirements of production control and the features of discrete manufacturing process were researched , the production process control system architecture was built. Then, the key technologies used in the system realization were studied. Automatic identification technology was used in data acquisition; product tracking and event tracking technologies were used to implement production monitor, abnormal monitor respectivly in application server; Web technology was used in production statistics and analysis in presentation layer. Data acquisition and statement analysis implementation

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29

Sadeghi, Heibatolah, Hêriş Golpîra, and Syed Abdul Rehman Khan. "Optimal integrated production-inventory system considering shortages and discrete delivery orders." Computers & Industrial Engineering 156 (June 2021): 107233. http://dx.doi.org/10.1016/j.cie.2021.107233.

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30

Goo, Bongeun, Hyun Chung, and Soonheung Han. "Layered discrete event system specification for a ship production scheduling model." Simulation Modelling Practice and Theory 96 (November 2019): 101934. http://dx.doi.org/10.1016/j.simpat.2019.101934.

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31

YAMASHIRO, Mitsuo, and Guo Ya Zhen. "Analysis of Three Divergent-type Production System using Discrete Markov Process." Proceedings of Conference of Chugoku-Shikoku Branch 2004.I (2004): 249–50. http://dx.doi.org/10.1299/jsmecs.2004.i.249.

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32

Mamalis, A. G., V. S. Ganovsky, and V. Guenova. "System-based approach to the development of a CAPP-system for automated discrete production." International Journal of Advanced Manufacturing Technology 9, no. 3 (1994): 175–79. http://dx.doi.org/10.1007/bf01754595.

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33

Usenik, Janez. "SYSTEM CONTROL IN CONDITIONS OF FUZZY DYNAMIC PROCESSES." Journal of Energy Technology 8, no. 1 (2024): 35–50. https://doi.org/10.18690/jet.8.1.35-50.2015.

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Анотація:

In this article, a mathematical model of controlling the system in conditions of fuzzy processes is presented. Such a system can also be a power supply system. Analytical approaches that can be used to describe the mutual impact of output and stocks (additional capacities) on hierarchically distributed occurrence/usage/variation or demand already exist. We add dynamics to the system with the use of continuous and discrete dynamic processes, which are of a random (stochastic) form. The dynamic discrete model of control for this system is built with a system of difference equations, and the dyna

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34

CULDA, LOREDANA CAMELIA, EVA KASLIK, and MIHAELA NEAMŢU. ""A dynamic Cournot mixed oligopoly model with time delay for competitors"." Carpathian Journal of Mathematics 38, no. 3 (2022): 681–90. http://dx.doi.org/10.37193/cjm.2022.03.13.

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"This paper deals with the analysis of a discrete-time Cournot game with time delay, where the interactions of one public firm and n private firms on the market are considered. The production of the public firm is adjusted based on the past production levels of the private firms. At the same time, the productions of the private firms are updated with respect to the past production of the public firm. Two equilibrium points are determined for the discrete-time nonlinear mathematical model. The analysis of the stability reveals that the boundary equilibrium point is a saddle point, while the pos

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35

OYARBIDE, A., T. S. BAINES, J. M. KAY, and J. LADBROOK. "MANUFACTURING SYSTEMS MODELLING USING SYSTEM DYNAMICS: FORMING A DEDICATED MODELLING TOOL." Journal of Advanced Manufacturing Systems 02, no. 01 (2003): 71–87. http://dx.doi.org/10.1142/s0219686703000228.

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Анотація:

Discrete event simulation is a popular aid for manufacturing system design; however in application this technique can sometimes be unnecessarily complex. This paper is concerned with applying an alternative technique to manufacturing system design which may well provide an efficient form of rough-cut analysis. This technique is System Dynamics, and the work described in this paper has set about incorporating the principles of this technique into a computer based modelling tool that is tailored to manufacturing system design. This paper is structured to first explore the principles of System Dy

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36

Okubo, Yui, and Taiga Mitsuyuki. "Ship Production Planning Using Shipbuilding System Modeling and Discrete Time Process Simulation." Journal of Marine Science and Engineering 10, no. 2 (2022): 176. http://dx.doi.org/10.3390/jmse10020176.

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Анотація:

Production planning is an important factor for production efficiency in the shipyard. However, planning is currently executed by manual operations based on the experience of field workers because of the complexity of the target shipbuilding project. This paper proposes a method of creating a realistic production plan automatically by modeling the complex shipbuilding project and using the developed process simulation. Specifically, we propose a method to represent the target shipbuilding process by four system models—Product, Workflow, Workplace, and Team. By executing the developed process si

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37

SCHLEY, DAVID, and MARTIN A. BEES. "A DISCRETE SLUG POPULATION MODEL DETERMINED BY EGG PRODUCTION." Journal of Biological Systems 10, no. 03 (2002): 243–64. http://dx.doi.org/10.1142/s0218339002000585.

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Анотація:

Slugs are significant pests in agriculture (as well as a nuisance to gardeners), and it is therefore important to understand their population dynamics for the construction of efficient and effective control measures. Differential equation models of slug populations require the inclusion of large (variable) temporal delays, and strong seasonal forcing results in a non-autonomous system. This renders such models open to only a limited amount of rigorous analysis. In this paper, we derive a novel batch model based purely upon the quantity of eggs produced at different times of the year. This mode

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38

APAK, Sinan, and Sami ERCAN. "Simulation Based Optimization for World Line Card Production System." An International Journal of Optimization and Control: Theories & Applications (IJOCTA) 2, no. 2 (2012): 95–104. http://dx.doi.org/10.11121/ijocta.01.2012.00107.

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Анотація:

Simulation based decision support system is one of the commonly used tool to examine complex production systems. The simulation approach provides process modules which can be adjusted with certain parameters by using data relatively easily obtainable in production process. World Line Card production system simulation is developed to evaluate the optimality of existing production line via using discrete event simulation model with variaty of alternative proposals. The current production system is analysed by a simulation model emphasizing the bottlenecks and the poorly utilized production line.

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39

Standridge, C., and M. Wynne. "Validation of production system throughput potential and simulation experiment design." International Journal of Production Management and Engineering 9, no. 1 (2021): 15. http://dx.doi.org/10.4995/ijpme.2021.14483.

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Анотація:

<p>The throughput potential of a production system must be designed and validated before implementation. Design includes creating product flow by setting the takt time consistent with meeting customer demand per time period and the average cycle time at each workstation being less than the takt time. Creating product flow implies that the average waiting time preceding each workstation is no greater than the takt time. Kingman’s equation for the average waiting time can be solved for the variation component given the utilization, and the cycle time. The variation component consists of th

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Hu, Zhenhua, and Wen Chen. "Modeling of Macroeconomics by a Novel Discrete Nonlinear Fractional Dynamical System." Discrete Dynamics in Nature and Society 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/275134.

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We propose a new nonlinear economic system with fractional derivative. According to the Jumarie’s definition of fractional derivative, we obtain a discrete fractional nonlinear economic system. Three variables, the gross domestic production, inflation, and unemployment rate, are considered by this nonlinear system. Based on the concrete macroeconomic data of USA, the coefficients of this nonlinear system are estimated by the method of least squares. The application of discrete fractional economic model with linear and nonlinear structure is shown to illustrate the efficiency of modeling the ma

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Syabira, Zahrayna Shebina, Muhammad Almaududi Pulungan, and Yudha Prambudia. "Perancangan Sistem Produksi Ekstrak Lemon dengan Discrete Event Simulation." JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI 9, no. 2 (2024): 129. http://dx.doi.org/10.36722/sst.v9i2.2695.

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Анотація:

<p><strong>XYZ Company is a Micro, Small, and Medium Enterprise (MSME) that is engaged in the production of fruit juice drinks with the type of production produced being lemon extract. Unfulfilled demand for lemon extract products is the main problem faced by XYZ Company. This study aims to optimize the production system and provide suggestions for improvements to increase production capacity to achieve production targets using discrete event simulation. Production target planning is determined using demand forecasting. The results of model simulations that have been verified and v

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42

Katzorke, I., and A. Pikovsky. "Chaos and complexity in a simple model of production dynamics." Discrete Dynamics in Nature and Society 5, no. 3 (2000): 179–87. http://dx.doi.org/10.1155/s1026022600000510.

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We consider complex dynamical behavior in a simple model of production dynamics, based on the Wiendahl’s funnel approach. In the case of continuous order flow a model of three parallel funnels reduces to the one-dimensional Bernoulli-type map, and demonstrates strong chaotic properties. The optimization of production costs is possible with the OGY method of chaos control. The dynamics changes drastically in the case of discrete order flow. We discuss different dynamical behaviors, the complexity and the stability of this discrete system.

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HASEGAWA, Kensuke, Kouji TAKAHASHI, and Paulo Eigi MIYAGI. "Application of the Mark Flow Graph to Represent Discrete Event Production Systems and System Control." Transactions of the Society of Instrument and Control Engineers 24, no. 1 (1988): 69–75. http://dx.doi.org/10.9746/sicetr1965.24.69.

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44

Korneev, A. M., T. A. Smetannikova, A. V. Maksimov, and M. N. Pantyushin. "MODULES OF DIGITAL TWIN OF MULTISTAGE PRODUCTION PROCESS." Vesti vysshikh uchebnykh zavedenii Chernozem ya 20, no. 2 (2024): 30–38. https://doi.org/10.53015/18159958_2024_20_2_30.

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Анотація:

In this paper, the modules of the digital twin of a multistage production process are considered. The module for optimizing the functioning of complex systems contains a set of methods for determining optimal modes and their adaptation in complex production systems. Discrete optimization methods select the optimal technological modes for any type of product. The methods of modeling the technological process carry out the construction of linear and non-linear models of the dependence of product quality indicators on technological factors. The in-formation and configuration display module is des

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45

Kalinowski, Krzysztof, Cezary Grabowik, Iwona Paprocka, and Wojciech M. Kempa. "The Model of Discrete Production Scheduling System in UML Notation - Classes Diagrams." Advanced Materials Research 837 (November 2013): 416–21. http://dx.doi.org/10.4028/www.scientific.net/amr.837.416.

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The modeling phase of the computer system development is one of the most important elements affecting the final success of the created software. Structures developed at this stage are the basis for the design and implementation of computer program code. The paper presents the general model of static structures (main classes and their relationships) of production scheduling system supporting discrete and multiassortment production. In the description of the object-oriented model a graphical systems and specifications modeling language notation UML was used.

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YAMASHIRO, Mitsuo, Takayuki TAKAGI, and Yorimasa KUBA. "Analysis of Divergent Type of Production System by the Discrete Markov Process." Proceedings of Conference of Tohoku Branch 2003.38 (2003): 70–71. http://dx.doi.org/10.1299/jsmeth.2003.38.70.

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Venkateswaran, J., and Y. J. Son *. "Hybrid system dynamic—discrete event simulation-based architecture for hierarchical production planning." International Journal of Production Research 43, no. 20 (2005): 4397–429. http://dx.doi.org/10.1080/00207540500142472.

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Allah Taleizadeh, Ata, Hadi Samimi, Biswajit Sarkar, and Babak Mohammadi. "Stochastic machine breakdown and discrete delivery in an imperfect inventory-production system." Journal of Industrial & Management Optimization 13, no. 3 (2017): 1511–35. http://dx.doi.org/10.3934/jimo.2017005.

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Napitupulu, Humala L. "Discrete system simulation application on determining the optimal amount of weekly production." IOP Conference Series: Materials Science and Engineering 801 (June 3, 2020): 012137. http://dx.doi.org/10.1088/1757-899x/801/1/012137.

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S. Ashwin, J., and N. Manoharan. "Impacts of Average Power Factor Management Into Sharing System with Discrete Production." Indonesian Journal of Electrical Engineering and Computer Science 8, no. 3 (2017): 698. http://dx.doi.org/10.11591/ijeecs.v8.i3.pp698-699.

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Анотація:

<p>Electrical frameworks are definitely influenced by power misfortunes, predominantly because of the present moving through lines and transformers. Streams rely on upon end-clients' energy ingestion and are entirely identified with the general power calculate, coming about because of burdens, remunerating units and conveyed era. The powers consider administration affects organize control misfortunes and voltage profiles along conveyance lines. Previously, before the appropriated era dissemination, the system misfortunes minimization could be acquired by requiring a high normal influence

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