Deriving essential components of lean and industry 4.0 assessment model for manufacturing SMEs

被引:35
|
作者
Kolla, Sri [1 ]
Minufekr, Meysam [1 ]
Plapper, Peter [1 ]
机构
[1] Univ Luxembourg, 6 Rue Richard Coudenhove Kalergi, L-1359 Luxembourg, Luxembourg
关键词
Industry; 4.0; lean; maturity model; self-assessment tool; digital transformation; MATURITY MODELS;
D O I
10.1016/j.procir.2019.03.189
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Quantifying lean and ICT architecture related to Industry 4.0 is a new challenge in Small and Medium Scale Enterprises (SMEs) that needs to be addressed by both research as well as enterprises themselves. Especially in the manufacturing sector, SMEs need to transform themselves into emerging trends such as industry 4.0 while practicing existing manufacturing philosophies such as Lean Production Systems (LPS) to be competitive in global markets. The major concern is that there are many assessment models available to measure the status of an enterprise related to either LPS or Industry 4.0. Often, these models are complex and don't fulfill the requirements of manufacturing SMEs. On the other hand, most of the models only consider either lean or industry 4.0 elements. The outcomes of this research help to develop a hybrid model including both lean and industry 4.0 features suitable for manufacturing SMEs. The main objective of this research is to provide state of the art literature on existing assessment models and consequently map lean and industry 4.0 components to the specific characteristics of manufacturing SMEs. The paper concludes with a summary and outlook for our future research. (C) 2019 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:753 / 758
页数:6
相关论文
共 50 条
  • [1] How to adapt lean practices in SMEs to support Industry 4.0 in manufacturing
    Mofolasayo, Adekunle
    Young, Steven
    Martinez, Pablo
    Ahmad, Rafiq
    [J]. 3RD INTERNATIONAL CONFERENCE ON INDUSTRY 4.0 AND SMART MANUFACTURING, 2022, 200 : 934 - 943
  • [2] Lean Manufacturing and Industry 4.0
    Anthony, Peter
    [J]. MANUFACTURING ENGINEERING, 2017, 159 (04): : 104 - 104
  • [3] Is lean manufacturing maturity a prerequisite for industry 4.0? Survey of SMEs in Japan and Brazil
    Tsukada, Osamu
    Ibusuki, Ugo
    Kuchii, Shigeru
    de Almeida, Anderson Tadeu de Santi Barbosa
    [J]. INTERNATIONAL JOURNAL OF LEAN SIX SIGMA, 2024, 15 (05) : 1102 - 1126
  • [4] Industry 4.0 Implies Lean Manufacturing: Research Activities in Industry 4.0 Function as Enablers for Lean Manufacturing
    Sanders, Adam
    Elangeswaran, Chola
    Wulfsberg, Jens
    [J]. JOURNAL OF INDUSTRIAL ENGINEERING AND MANAGEMENT-JIEM, 2016, 9 (03): : 811 - 833
  • [5] Industry 4.0 Enhanced Lean Manufacturing
    Lai, Nai Yeen Gavin
    Wong, Kok Hoong
    Halim, Dunant
    Lu, Jiawa
    Kang, Hooi Siang
    [J]. PROCEEDINGS OF 2019 8TH INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY AND MANAGEMENT (ICITM 2019), 2019, : 206 - 211
  • [6] Assessment by Lean Modified Manufacturing Maturity Model for Industry 4.0: A Case Study of Pakistan's Manufacturing Sector
    Sajjad, Ahmad
    Ahmad, Wasim
    Hussain, Salman
    Chuddher, Bilal Akbar
    Sajid, Muhammad
    Jahanjaib, Mirza
    Ali, Muhammad Khurram
    Jawad, Muhammad
    [J]. IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, 2023, 71 : 6420 - 6434
  • [7] Prerequisites for the Implementation of Industry 4.0 in Manufacturing SMEs
    Genest, Marie Charbonneau
    Gamache, Sebastien
    [J]. 30TH INTERNATIONAL CONFERENCE ON FLEXIBLE AUTOMATION AND INTELLIGENT MANUFACTURING (FAIM2021), 2020, 51 : 1215 - 1220
  • [8] Industry 4.0 in manufacturing SMEs of Argentina and Brazil
    Ascua, Ruben Andres
    [J]. JOURNAL OF THE INTERNATIONAL COUNCIL FOR SMALL BUSINESS, 2021, 2 (03): : 203 - 222
  • [9] A Lean Manufacturing Progress Model and Implementation for SMEs in the Metal Products Industry
    Huang, Chien-Yi
    Lee, Dasheng
    Chen, Shu-Chuan
    Tang, William
    [J]. PROCESSES, 2022, 10 (05)
  • [10] Lean Manufacturing in Industry 4.0: A Smart and Sustainable Manufacturing System
    Rahardjo, Benedictus
    Wang, Fu-Kwun
    Yeh, Ruey-Huei
    Chen, Yu-Ping
    [J]. MACHINES, 2023, 11 (01)