Robustness evaluation of production plans using Monte Carlo simulation

被引:1
|
作者
Franke, Susanne [1 ]
Franke, Felix [1 ]
Riedel, Ralph [1 ]
机构
[1] Tech Univ Chemnitz, Erfenschlager Str 73, D-09125 Chemnitz, Germany
关键词
production planning and control; robustness; Monte Carlo methods;
D O I
10.1016/j.promfg.2021.07.021
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In order to meet the challenges on the global market and to maximize productivity, production companies need to develop an effective production planning strategy. Production planning is a complex process that underlies a dynamic, fast-paced behavior: influences like machine failure, change of order or absence of employees regularly require an adaptation of the existing production plan. In this paper, we present a methodology that models phenomena influencing the production plan and evaluates their effects on the completion times via a Monte Carlo simulation. Focusing on short-notice incoming orders, the methodology provides statements on the robustness of the production plan by estimating the anticipated change in the completion times under the occurrence of uncertain events. (c) 2021 The Authors. Published by Elsevier B. V.
引用
收藏
页码:130 / 135
页数:6
相关论文
共 50 条
  • [31] Improving lead time of pharmaceutical production processes using Monte Carlo simulation
    Eberle, Lukas Gallus
    Sugiyama, Hirokazu
    Schmidt, Rainer
    [J]. COMPUTERS & CHEMICAL ENGINEERING, 2014, 68 : 255 - 263
  • [32] Simulation of production processes and associated costs in mining using the Monte Carlo method
    Mathey, M.
    [J]. JOURNAL OF THE SOUTHERN AFRICAN INSTITUTE OF MINING AND METALLURGY, 2022, 122 (12) : 697 - 703
  • [33] Applications of cluster analysis in Monte Carlo production simulation
    Huang, SR
    Lin, YW
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 1996, 11 (02) : 1052 - 1058
  • [34] Secondary Optimization of VMAT Plans Using Monte Carlo Beamlets
    Mathews, J.
    French, S.
    Bhagroo, S.
    Nazareth, D.
    [J]. MEDICAL PHYSICS, 2019, 46 (06) : E473 - E473
  • [35] Analyzing food production risk with Monte Carlo simulation
    Mahmudiono, Trias
    Yasin, Ghulam
    Jasim, Saade Abdalkareem
    Alghazali, Tawfeeq Abdulameer Hashim
    Kadhim, Mustafa Mohammed
    Iswanto, Acim Heri
    Majeed, Mohammed Sabeeh
    Sharma, Sandhir
    Al-Mawlawi, Zaid Shaker
    Panduro-Tenazoa, Nadia Masaya
    [J]. FOOD SCIENCE AND TECHNOLOGY, 2022, 42
  • [36] MONTE-CARLO SIMULATION OF COSMOGENIC NUCLIDE PRODUCTION
    MASARIK, J
    EMRICH, P
    POVINEC, P
    TOKAR, S
    [J]. NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION B-BEAM INTERACTIONS WITH MATERIALS AND ATOMS, 1986, 17 (5-6): : 483 - 489
  • [37] Monte Carlo simulation of 64Cu production
    Wang, Tianquan
    Zhang, Hu
    Zhang, Jiuhui
    Wang, Ruimin
    Zhang, Xiaofei
    Yin, Yongzhi
    Fan, Wei
    [J]. JOURNAL OF INSTRUMENTATION, 2023, 18 (09):
  • [38] A MONTE-CARLO SIMULATION OF A PRODUCTION PLANNING PROBLEM
    MUSK, FI
    [J]. COMPUTER JOURNAL, 1959, 2 (02): : 90 - 94
  • [39] Monte Carlo Simulation of Pathogen Reduced Platelet Production
    Blake, John T.
    McTaggart, Ken
    [J]. PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON SIMULATION AND MODELING METHODOLOGIES, TECHNOLOGIES AND APPLICATIONS (SIMULTECH), 2022, : 386 - 394
  • [40] Testing for robustness in Monte Carlo studies
    Serlin, RC
    [J]. PSYCHOLOGICAL METHODS, 2000, 5 (02) : 230 - 240