How Singapore’s Manufacturing Small and Medium Size Enterprises Embrace Industry 4.0

T. Menkhoff, Gopalakrishnan Surianarayanan
{"title":"How Singapore’s Manufacturing Small and Medium Size Enterprises Embrace Industry 4.0","authors":"T. Menkhoff, Gopalakrishnan Surianarayanan","doi":"10.54941/ahfe1003516","DOIUrl":null,"url":null,"abstract":"Industry 4.0 adoption is expected to profoundly impact the entire spectrum of industries, especially in manufacturing. By using a confluence of automation, data, and digitalisation, Industry 4.0 aims to radically transform how organisations operate presently while increasing productivity, enhancing flexibility, reducing costs, and improving efficiency. More companies are strategically embracing Industry 4.0 approaches to leverage opportunities arising from newly connected computers and increasingly autonomous automation systems (e.g., robotics), equipped with intelligent machine learning algorithms that control the robotics without much human input. In these 'smart' factories, cyber-physical systems (i.e., independently operating systems that self-optimize and communicate with each other, and ultimately optimize production) monitor the physical manufacturing processes and play an increasingly important role in terms of decision-making. Industry 4.0 signifies three mutually interconnected factors, namely digitisation and integration of any technical-economic networks, digitisation of products and services, and new market models. At the core of this new smart manufacturing paradigm is the Internet of Things that drives the conversion of traditional factories into a 'smart' manufacturing environment called \"Industry 4.0\", resulting in an increasingly intelligent, connected, and autonomous factory with dynamic capabilities. Smart manufacturing technologies include big data processing, machine learning, advanced robotics, cloud computing, sensors technology, additive manufacturing, and augmented reality. By using predictive big data analytics, deep learning, or sentiment/image analysis, business leaders can identify patterns and trends in vast reams of big data. It allows them to make 'smarter' decisions (e.g., about the loss of customers or the necessary service inspection of equipment) and potentially to become more competitive in real-time. Based on case study research on small manufacturing firms in Singapore, we explore how local SMEs adopt Industry 4.0 solutions. We shed light on the drivers and barriers of Industry 4.0 adoption to better understand current business dynamics, potential human issues, focus areas, and initiatives to smoothen this implementation. The study is part of a wider Industry 4.0 study of key specialists and decision-makers across Government agencies, Institutes of Higher Learnings, suppliers of Industry 4.0 technology, business associations, etc. Technology push by the Government with robust funding and training support, skilled labour shortages including imported labour dependence, productivity issues and the pressure to innovate business models due to increased competition are propelling SMEs to adopt Industry 4.0. Some challenges include high investment costs, ROI concerns as well as capability and mindset issues. The paper contributes to the minimal Asian management literature about Industry 4.0 matters in Asian SMEs.","PeriodicalId":363648,"journal":{"name":"Human Aspects of Advanced Manufacturing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Aspects of Advanced Manufacturing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54941/ahfe1003516","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Industry 4.0 adoption is expected to profoundly impact the entire spectrum of industries, especially in manufacturing. By using a confluence of automation, data, and digitalisation, Industry 4.0 aims to radically transform how organisations operate presently while increasing productivity, enhancing flexibility, reducing costs, and improving efficiency. More companies are strategically embracing Industry 4.0 approaches to leverage opportunities arising from newly connected computers and increasingly autonomous automation systems (e.g., robotics), equipped with intelligent machine learning algorithms that control the robotics without much human input. In these 'smart' factories, cyber-physical systems (i.e., independently operating systems that self-optimize and communicate with each other, and ultimately optimize production) monitor the physical manufacturing processes and play an increasingly important role in terms of decision-making. Industry 4.0 signifies three mutually interconnected factors, namely digitisation and integration of any technical-economic networks, digitisation of products and services, and new market models. At the core of this new smart manufacturing paradigm is the Internet of Things that drives the conversion of traditional factories into a 'smart' manufacturing environment called "Industry 4.0", resulting in an increasingly intelligent, connected, and autonomous factory with dynamic capabilities. Smart manufacturing technologies include big data processing, machine learning, advanced robotics, cloud computing, sensors technology, additive manufacturing, and augmented reality. By using predictive big data analytics, deep learning, or sentiment/image analysis, business leaders can identify patterns and trends in vast reams of big data. It allows them to make 'smarter' decisions (e.g., about the loss of customers or the necessary service inspection of equipment) and potentially to become more competitive in real-time. Based on case study research on small manufacturing firms in Singapore, we explore how local SMEs adopt Industry 4.0 solutions. We shed light on the drivers and barriers of Industry 4.0 adoption to better understand current business dynamics, potential human issues, focus areas, and initiatives to smoothen this implementation. The study is part of a wider Industry 4.0 study of key specialists and decision-makers across Government agencies, Institutes of Higher Learnings, suppliers of Industry 4.0 technology, business associations, etc. Technology push by the Government with robust funding and training support, skilled labour shortages including imported labour dependence, productivity issues and the pressure to innovate business models due to increased competition are propelling SMEs to adopt Industry 4.0. Some challenges include high investment costs, ROI concerns as well as capability and mindset issues. The paper contributes to the minimal Asian management literature about Industry 4.0 matters in Asian SMEs.
新加坡制造业中小企业如何拥抱工业4.0
工业4.0的采用预计将深刻影响整个行业,尤其是制造业。通过使用自动化、数据和数字化的融合,工业4.0旨在从根本上改变组织目前的运作方式,同时提高生产力、增强灵活性、降低成本和提高效率。越来越多的公司正在战略性地采用工业4.0方法,以利用新连接的计算机和日益自动化的自动化系统(例如机器人)所带来的机会,这些系统配备了智能机器学习算法,无需大量人工输入即可控制机器人。在这些“智能”工厂中,网络物理系统(即,自我优化和相互通信并最终优化生产的独立操作系统)监控物理制造过程,并在决策方面发挥越来越重要的作用。工业4.0意味着三个相互关联的因素,即任何技术经济网络的数字化和集成,产品和服务的数字化以及新的市场模式。这种新的智能制造范式的核心是物联网,它推动传统工厂向“智能”制造环境的转变,称为“工业4.0”,从而产生具有动态能力的日益智能,互联和自主的工厂。智能制造技术包括大数据处理、机器学习、先进机器人、云计算、传感器技术、增材制造和增强现实。通过使用预测性大数据分析、深度学习或情感/图像分析,企业领导者可以识别大量大数据中的模式和趋势。它使他们能够做出“更明智”的决定(例如,关于客户流失或设备必要的服务检查),并有可能在实时中变得更具竞争力。本文通过对新加坡小型制造企业的案例研究,探讨了新加坡中小企业如何采用工业4.0解决方案。我们阐明了采用工业4.0的驱动因素和障碍,以更好地了解当前的业务动态、潜在的人为问题、重点领域和平滑实施的举措。该研究是一项更广泛的工业4.0研究的一部分,研究对象包括政府机构、高等院校、工业4.0技术供应商、商业协会等的关键专家和决策者。政府大力推动科技发展,提供充足的资金和培训支持,技术工人短缺(包括依赖进口劳工),生产力问题,以及竞争加剧带来的创新商业模式的压力,正推动中小企业采用工业4.0。一些挑战包括高投资成本、ROI问题以及能力和心态问题。本文是亚洲关于工业4.0对亚洲中小企业影响的管理文献的一部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信