An Experimental Diagnostic Procedure to Identify the Source of Defects in Multi-Stage and Multi-Component Production Processes

被引:7
|
作者
Vandebroek, Martina [1 ]
Lan, Lan [1 ]
Knapen, Koen [2 ]
机构
[1] Katholieke Univ Leuven, Naamsestr 69, B-3000 Leuven, Belgium
[2] SAS Inst Belgium, Luxembourg, Luxembourg
关键词
Cluster Detection; Ljung-Box Statistic; Problem Detection; Quality Control; Scan Statistic; SCAN STATISTICS;
D O I
10.1080/00224065.2016.11918162
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Many production processes consist of successive steps in which things can go wrong without notice because the problem is only detectable in the final product. For instance in steel manufacturing, the coils undergo melting, hot rolling, annealing and pickling, and defects in one of these stages only become visible after the final process. In other production processes, an output issue may only be detected during final testing after the different parts have been assembled. In all these cases, it is hard to determine which part of the production process is responsible for an unusually high defect rate. We describe a simple procedure based on cluster detection to identify the problematic step if the following conditions are satisfied: the production of defects tends to occur clustered in time and it is feasible to (partially) reorder the part or batch processing sequence in each stage of the production process. Even if reordering is not required for the production, the diagnostic information that can be obtained can well outweigh the potential extra costs involved.
引用
收藏
页码:213 / 226
页数:14
相关论文
共 50 条
  • [1] A multi-stage multi-component transfer rate morphological population balance model for crystallization processes
    Shu, Yi D.
    Liu, Jing J.
    Zhang, Yang
    Wang, Xue Z.
    CRYSTENGCOMM, 2019, 21 (28) : 4212 - 4220
  • [2] Experimental and numerical study on multi-stage heat release induced by sequential combustion of multi-component fuel
    Ren, Shuo-Jin
    Wang, Zhi
    Wang, Jian-Xin
    Kung Cheng Je Wu Li Hsueh Pao/Journal of Engineering Thermophysics, 2015, 36 (08): : 1820 - 1825
  • [3] DYNAMIC BEHAVIOUR OF MULTI-COMPONENT MULTI-STAGE SYSTEMS - NUMERICAL METHODS FOR THE SOLUTION
    MAH, RSH
    MICHAELSON, S
    SARGENT, RWH
    CHEMICAL ENGINEERING SCIENCE, 1962, 17 (08) : 619 - 639
  • [4] Simulation of Multi-component Multi-stage Separation Process ——An Improved Algorithm and Application
    李春山
    张香平
    张锁江
    谭心舜
    项曙光
    过程工程学报, 2006, (02) : 247 - 254
  • [5] Workload balancing in multi-stage production processes
    Tazari, Siamak
    Mueller-Hannemann, Matthias
    Weihe, Karsten
    EXPERIMENTAL ALGORITHMS, PROCEEDINGS, 2006, 4007 : 49 - 60
  • [6] COST CONTROLS IN MULTI-STAGE PRODUCTION PROCESSES
    KLOOCK, J
    DORNER, E
    OR SPEKTRUM, 1988, 10 (03) : 129 - 143
  • [7] Development of a Component for Production on a Multi-Stage Press.
    Sieber, Karl
    1975, : 320 - 343
  • [8] Solution procedure for the multi-item and multi-stage production planning problem
    Tamura, Takayoshi
    Nippon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C, 1988, 54 (504): : 1974 - 1982
  • [9] Strategies for the simulation of multi-component hollow fibre multi-stage membrane gas separation systems
    Binns, Michael
    Lee, Sunghoon
    Yeo, Yeong-Koo
    Lee, Jung Hyun
    Moon, Jong-Ho
    Yeo, Jeong-Gu
    Kim, Jin-Kuk
    JOURNAL OF MEMBRANE SCIENCE, 2016, 497 : 458 - 471
  • [10] Multi-stage heat release of multi-component fuels: Insights and implications for advanced engine operation
    Zhang, Shannon
    Lee, Matthew
    Goldsborough, S. Scott
    Cheng, Song
    FUEL, 2023, 332