A framework for the prioritization of industry 4.0 and lean manufacturing technologies based on network theory

IF 7.3 2区 工程技术 Q1 ENGINEERING, INDUSTRIAL
Gabriel Bertholdo Vargas, Jefferson de Oliveira Gomes, Rolando Vargas Vallejos
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引用次数: 0

Abstract

Purpose

The purpose of this paper is to present a practical data-based framework for the prioritization of investment in manufacturing technologies, methods and tools, and to demonstrate its applicability and practical relevance through two case studies of manufacturing firms of different industrial segments.

Design/methodology/approach

The proposed framework is based on network theory applied on technology adoption. For this, the database of Industry 4.0 maturity assessments of SENAI was used to develop data visualization tools named “Technology Networks”. Thus, this study is descriptive research with correlational design. Besides, the framework was applied in two companies and semi-structured interviews were carried out with domain experts.

Findings

The technology networks highlight the technological adoption patterns of six industrial segments, by considering the answers of 863 Brazilian companies. In general, less sophisticated technologies were positioned in the center of the networks, which facilitates the visualization of adoption paths. Moreover, the networks presented a well-balanced adoption scenario of Industry 4.0 related technologies and lean manufacturing methods and tools.

Research limitations/implications

Since the database was not built under an experimental design, it is not expected to make statistical inferences about the variables. Furthermore, the decision to use an available database prevented the editing or inclusion of technologies. Besides, it is estimated that the technology networks given have few years for obsolescence due to the fast pace of technological development.

Practical implications

The framework is a tool that may be used by practicing manufacturing managers and entrepreneurs for taking assertive decisions regarding the adoption of manufacturing technologies, methods and tools. The proposition of using network theory to support decision making on this topic may lead to further studies, developments and adaptations of the framework.

Originality/value

This paper addresses the topics of lean manufacturing and Industry 4.0 in an unprecedented way, by quantifying the adoption of its technologies, methods and tools and presenting it in network visualizations. The main value of this paper is the comprehensive framework that applies the technology networks for supporting decision making regarding technology adoption.

基于网络理论的工业4.0与精益制造技术优先排序框架
本文的目的是为制造业技术、方法和工具的投资优先排序提供一个实用的基于数据的框架,并通过对不同工业部门的制造业企业的两个案例研究来证明其适用性和实际相关性。设计/方法/方法提出的框架是基于网络理论在技术采用中的应用。为此,利用SENAI的工业4.0成熟度评估数据库,开发了名为“技术网络”的数据可视化工具。因此,本研究为相关设计的描述性研究。此外,该框架应用于两家公司,并与领域专家进行了半结构化访谈。技术网络通过考虑863家巴西公司的答案,突出了六个工业部门的技术采用模式。一般来说,不太复杂的技术被放置在网络的中心,这有利于采用路径的可视化。此外,这些网络呈现了工业4.0相关技术和精益制造方法和工具的良好平衡采用场景。研究限制/意义由于数据库不是在实验设计下建立的,因此不期望对变量进行统计推断。此外,使用现有数据库的决定妨碍了技术的编辑或列入。此外,由于技术的快速发展,估计给出的技术网络在几年内就会过时。该框架是一种工具,可用于实践制造经理和企业家在采用制造技术、方法和工具方面做出自信的决策。使用网络理论来支持这一主题的决策的提议可能会导致该框架的进一步研究、发展和适应。原创性/价值本文通过量化其技术、方法和工具的采用,并以网络可视化的方式呈现,以前所未有的方式解决了精益制造和工业4.0的主题。本文的主要价值在于提供了应用技术网络支持技术采用决策的综合框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Manufacturing Technology Management
Journal of Manufacturing Technology Management Engineering-Control and Systems Engineering
CiteScore
16.30
自引率
7.90%
发文量
45
期刊介绍: The Journal of Manufacturing Technology Management (JMTM) aspires to be the premier destination for impactful manufacturing-related research. JMTM provides comprehensive international coverage of topics pertaining to the management of manufacturing technology, focusing on bridging theoretical advancements with practical applications to enhance manufacturing practices. JMTM seeks articles grounded in empirical evidence, such as surveys, case studies, and action research, to ensure relevance and applicability. All submissions should include a thorough literature review to contextualize the study within the field and clearly demonstrate how the research contributes significantly and originally by comparing and contrasting its findings with existing knowledge. Articles should directly address management of manufacturing technology and offer insights with broad applicability.
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