Performability analysis for the SPVC line system of leaf spring production plant using probabilistic approach

被引:0
|
作者
Parkash, Shanti [1 ]
Tewari, P. C. [1 ]
机构
[1] Natl Inst Technol Kurukshetra, Mech Engn Dept, Kurukshetra, India
关键词
Performability; Availability; Decision matrix; Markov method; RAMS;
D O I
10.1108/JQME-07-2023-0062
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
PurposeThis work ensures the higher performability of this complex system, which consists of five different subsystems, i.e. shearing machine, V-cutting machine, center hole punch, edge cutting burr and drilling machine. These subsystems are placed in combinations of both series and parallel arrangement. The concerned plant management must be aware of the failures that have the greatest/least impact on the system's performance.Design/methodology/approachPerformability analysis has been done for the Shearing, Punch and V- Cutting (SPVC) line system by using a probabilistic approach (i.e. Markov method). This system was further divided into five subsystems, and single-order differential equations are derived using the transition diagram. MATLAB software was used to determine the performability of the system for various combinations of repair and failure rates.FindingsIn this research work, performability analysis was done using different combinations of repair and failure rates for these subsystems. Further, a decision matrix (DM) has been developed that indicates that edge cutting burr is the most critical subsystem, which requires the top level of maintenance priorities among the various subsystems. This matrix will facilitate policymaking related to various maintenance activities for the respective system.Originality/valueIn this research work, a mathematical modeling based on a single differential equation using a transition diagram has been developed for the SPVC line system. The novelty of this work is to consider interaction among different subsystem, which generates more realistic situation during modeling. The purposed DM helps make future maintenance planning, which reduces maintenance costs and enhances system's performability.
引用
收藏
页码:508 / 520
页数:13
相关论文
共 50 条
  • [1] Performance modelling and analysis of the assembly line system of leaf spring manufacturing plant using Petri nets
    Parkash S.
    Tewari P.C.
    International Journal of Simulation and Process Modelling, 2022, 18 (03): : 237 - 243
  • [2] Analysis of the Vibration Characteristics of a Leaf Spring System Using Artificial Neural Networks
    Cetinkaya, Mehmet Bahadir
    Isci, Muhammed
    SENSORS, 2022, 22 (12)
  • [3] Mathematical Modeling and Availability Analysis of Leaf Spring Manufacturing Plant
    Tyagi, Sohan Lal
    Bansal, Shikha
    Agarwal, Priyanka
    Yadav, Ajay Singh
    PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY, 2021, 29 (02): : 1041 - 1051
  • [4] Upgrading of a 230 kV steel transmission line system using probabilistic approach
    Haldar, Asim
    2006 International Conference on Probabilistic Methods Applied to Power Systems, Vols 1 and 2, 2006, : 1133 - 1139
  • [5] Plant Leaf Recognition Using a Layered Approach
    Chaki, Jyotismita
    Parekh, Ranjan
    Bhattacharya, Samar
    2016 INTERNATIONAL CONFERENCE ON MICROELECTRONICS, COMPUTING AND COMMUNICATIONS (MICROCOM), 2016,
  • [6] Optimization of coal handling system performability for a thermal power plant using PSO algorithm
    Malik, Subhash
    Tewari, P. C.
    GREY SYSTEMS-THEORY AND APPLICATION, 2020, 10 (03) : 359 - 376
  • [7] Analytical Modelling and Performability Analysis for Cloud Computing Using Queuing System
    Kirsal, Yonal
    Ever, Yoney Kirsal
    Mostarda, Leonardo
    Gemikonakli, Orhan
    2015 IEEE/ACM 8TH INTERNATIONAL CONFERENCE ON UTILITY AND CLOUD COMPUTING (UCC), 2015, : 643 - 647
  • [8] A leaf recognition algorithm for plant classification using Probabilistic Neural Network
    Wu, Stephen Gang
    Bao, Forrest Sheng
    Xu, Eric You
    Wang, Yu-Xuan
    Chang, Yi-Fan
    Xiang, Qiao-Liang
    2007 IEEE INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND INFORMATION TECHNOLOGY, VOLS 1-3, 2007, : 120 - +
  • [9] Analysis of composite leaf spring using ANSYS software
    Ali, K. S. Ashraff
    Manuel, D. Joseph
    Balamurugan, M.
    Murugan, M. Sangili
    MATERIALS TODAY-PROCEEDINGS, 2021, 37 : 2346 - 2351
  • [10] Probabilistic approach to geometric hashing using line features
    IBM Zurich Research Lab, Ruschlikon, Switzerland
    CVIU Comput Vision Image Undersanding, 1 (182-195):