Estimation of Machining Sustainability Using Fuzzy Rule-Based System

被引:2
|
作者
Iqbal, Asif [1 ]
Zhao, Guolong [2 ]
Cheok, Quentin [1 ]
He, Ning [2 ]
机构
[1] Univ Brunei Darussalam, Fac Integrated Technol, Jalan Tungku Link, BE-1410 Gadong, Brunei
[2] Nanjing Univ Aeronaut & Astronaut, Coll Mech & Elect Engn, 29 Yu Dao St, Nanjing 210016, Peoples R China
关键词
cutting; fuzzy sets; fuzzy reasoning; sustainable machining; cutting fluid; EXPERT-SYSTEM; LOGIC;
D O I
10.3390/ma14195473
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Quantification of a highly qualitative term 'sustainability', especially from the perspective of manufacturing, is a contemporary issue. An inference mechanism, based on approximate reasoning, is required to tackle the complexities and uncertainties of the manufacturing domain. The work presents development of a fuzzy rule-based system to quantify sustainability of the most widely utilized manufacturing process: machining. The system incorporates the effects of key control parameters of machining on several sustainability measures, as reported in the literature. The measures are categorized under the three dimensions of sustainability and contribute to the sustainability scores of the respective dimensions with different weightages. The dimensions' scores are added up in different proportions to obtain the holistic sustainability score of the process. The categories of the control parameters incorporated into the system include type of the process, work material, material hardness, tool substrate and coating, tool geometry, cutting fluids, and cutting parameters. The proposed method yields sustainability scores, ranging between 0 and 100 of machining processes against the given values of their prominent control parameters. Finally, the rule-based system is applied to three different machining processes to obtain the measures of their accomplishment levels regarding economic, environmental, and societal dimensions of sustainability. The sustainability score of each process is then obtained by summing up the three accomplishment levels under the respective weightages of the dimensions. The presented approach holds immense potentials of industrial application as it can conveniently indicate the current sustainability level of a manufacturing process, leading the practitioners to decide on its continuation or improvement.
引用
收藏
页数:16
相关论文
共 50 条
  • [31] Fuzzy Clustering Rule-Based Expert System for Stock Price Movement Prediction
    Shakeri, Behnoush
    Zarandi, M. H. Fazel
    Tarimoradi, Mosahar
    Turksan, I. B.
    2015 Annual Meeting of the North American Fuzzy Information Processing Society DigiPen NAFIPS 2015, 2015,
  • [32] CONNECTIONISM FOR FUZZY LEARNING IN RULE-BASED EXPERT SYSTEMS
    FU, LM
    LECTURE NOTES IN ARTIFICIAL INTELLIGENCE, 1992, 604 : 337 - 340
  • [33] Fuzzy Rule-Based Design of Evolutionary Algorithm for Optimization
    Elsayed, Saber
    Sarker, Ruhul
    Coello Coello, Carlos A.
    IEEE TRANSACTIONS ON CYBERNETICS, 2019, 49 (01) : 301 - 314
  • [34] Input selection in fuzzy rule-based classification systems
    Nakashima, T
    Morisawa, T
    Ishibuchi, H
    PROCEEDINGS OF THE SIXTH IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS I - III, 1997, : 1457 - 1462
  • [35] A Fuzzy Rule-Based GIS Framework to Partition an Urban System Based on Characteristics of Urban Greenery in Relation to the Urban Context
    Cardone, Barbara
    Di Martino, Ferdinando
    APPLIED SCIENCES-BASEL, 2020, 10 (24): : 1 - 17
  • [36] Shipboard compressor system risk analysis by using rule-based fuzzy FMEA for preventing major marine accidents
    Ceylan, Bulut Ozan
    OCEAN ENGINEERING, 2023, 272
  • [37] FUZZY RULE-BASED CLASSIFICATION OF ATMOSPHERIC CIRCULATION PATTERNS
    BARDOSSY, A
    DUCKSTEIN, L
    BOGARDI, I
    INTERNATIONAL JOURNAL OF CLIMATOLOGY, 1995, 15 (10) : 1087 - 1097
  • [38] Flood vulnerability assessment using a fuzzy rule-based index in Melbourne, Australia
    Rashetnia, Samira
    Jahanbani, Heerbod
    SUSTAINABLE WATER RESOURCES MANAGEMENT, 2021, 7 (02)
  • [39] Fuzzy interpolative reasoning for sparse fuzzy rule-based systems based on the slopes of fuzzy sets
    Chen, Shyi-Ming
    Hsin, Wen-Chyuan
    Yang, Szu-Wei
    Chang, Yu-Chuan
    EXPERT SYSTEMS WITH APPLICATIONS, 2012, 39 (15) : 11961 - 11969
  • [40] Fuzzy rule-based modeling of machining parameters for surface roughness in turning carbon particle-reinforced polyamide
    Palanikumar, K.
    Rajasekaran, T.
    Latha, B.
    JOURNAL OF THERMOPLASTIC COMPOSITE MATERIALS, 2015, 28 (10) : 1387 - 1405