Proceedings of International Conference on Applied Innovation in IT
2018/03/13, Volume 6, Issue 1, pp.67-75

The Use of Optimal Management Tasks for Verification and Adjustment of New Product Release Planning in Discrete Production Systems


Leonid Mylnikov, Dmitrii Vershinin, Daniil Fatkhullin


Abstract: The present paper investigates a modern issue of predictive models for optimal management used to enhance the performance of production system management that can be achieved by a joint consideration and synchronization of internal and external processes of an examined system. Volume planning task is considered as a task that helps verify the results of business planning and take into account the interrelation of subsystems of a production system and foreign market impact based on forecasting data. The article draws on the example of release of leading-edge vacuum pumps in an engineering company in order to define the prospects of this market and estimate manufacturing capabilities. The analysis was carried out based on the data of an approximate business plan and statistical data of vacuum pump market. As a result, it suggests production schedule for vacuum pumps that can be taken as a background for making feasibility decisions on the release of new products and adjusting production activities of an enterprise. The obtained business planning data can be used in practice by solving the tasks of production management that help perform preliminary estimates of enterprise potentiality for market needs and improve the objectivity of strategic decision making by enhancing the formalization level of describing processes and preparing objective data. The synchronization of production processes described in the paper is relevant as it is connected with the current trends, i.e. the reduction of time production, the depreciation of human factor in production processes, all that triggers increased requirements to the quality of management in production processes.

Keywords: Lot-Scheduling Planning, Optimal Management, Discrete Production, Project, Production System, Engineering Company, Forecast, Prediction, Business Plan, Smart Manufacturing

DOI: 10.13142/kt10006.27

Download: PDF

References:

  1. C. Kaiser, S. Schlick, and F. Bodendorf, “Warning system for online market research ? Identifying critical situations in online opinion formation,” Knowl.-Based Syst., vol. 24, no. 6, pp. 824–836, Aug. 2011.
  2. C. Arnold, D. Kiel, and K.-I. Voigt, “How the industrial internet of things changes business model in different manufactoring industries,” Int. J. Innov. Manag., vol. 20, no. 08, pp. 1640015-1-1640015–25, Dec. 2016.
  3. L. Mia and L. Winata, “Manufacturing strategy and organisational performance: The role of competition and MAS information,” J. Account. Organ. Change, vol. 10, no. 1, pp. 83–115, Feb. 2014.
  4. L. Mylnikov, “Particularities of Solving the Problems of Support for Managerial Decision Making in Production and Economic Systems Using the Statistical Data,” Int. J. Econ. Financ. Issues, vol. S8, no. 6, pp. 1–11, 2016.
  5. L. Mylnikov, “Risk Evaluation in Manufacturing Organization Tasks for Product Technological Projects and Establishment of Project Portfolio for Production Systems,” in Proceedings of the 2016 International Conference on Applied mathematics, simulation and modelling, Beijing, China, 2016, pp. 399–402.
  6. M. Cheng, N. J. Mukherjee, and S. C. Sarin, “A review of lot streaming,” Int. J. Prod. Res., vol. 51, no. 23–24, pp. 7023–7046, Nov. 2013.
  7. H. Jalali and I. V. Nieuwenhuyse, “Simulation optimization in inventory replenishment: a classification,” IIE Trans., vol. 47, no. 11, pp. 1217–1235, Nov. 2015.
  8. F. T. S. Chan, N. Li, S. H. Chung, and M. Saadat, “Management of sustainable manufacturing systems-a review on mathematical problems,” Int. J. Prod. Res., vol. 55, no. 4, pp. 1210–1225, Feb. 2017.
  9. M. Díaz-Madroñero, J. Mula, and D. Peidro, “A review of discrete-time optimization models for tactical production planning,” Int. J. Prod. Res., vol. 52, no. 17, pp. 5171–5205, Sep. 2014.
  10. J. A. Anderson, Discrete mathematics with combinatorics. Upper Saddle River, N.J: Prentice Hall, 2001.
  11. L. Mylnikov and M. Kuetz, “The risk assessment method in prognostic models of production systems management with account of the time factor,” Eur. Res. Stud. J., vol. 20, no. 3, pp. 291–310, 2017.

    Home

    PARTICIPATION

       - Timetable of reports
       - Photos (ICAIIT 2018)
       - Committee


    PROCEEDINGS

       - Volume 1 (ICAIIT 2013)
       - Volume 2 (ICAIIT 2014)
       - Volume 3 (ICAIIT 2015)
       - Volume 4 (ICAIIT 2016)
       - Volume 5 (ICAIIT 2017)
       - Volume 6 (ICAIIT 2018)

    ETHICS IN PUBLICATIONS

    ACCOMODATION

    CONTACT US

 


           ISSN 2199-8876
           Copyright © 2013-2017 Leonid Mylnikov. All rights reserved.