Industry 4.0 technologies and managers’ decision-making across value chain. Evidence from the manufacturing industry

Q2 Engineering
Michał Młody, Milena Ratajczak-Mrozek, Maja Sajdak
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引用次数: 0

Abstract

Abstract The paper aims to identify how Industry 4.0 technologies affect the quality and speed of the managers’ decision-making process across the different stages of the value chain, based on the example of the manufacturing sector. The paper adopts qualitative research, based on nine in-depth interviews with key informants, to capture senior executives’ experiences with implementing Industry 4.0 technologies in their organisations. The research is focused on three manufacturing industries: the automotive, food and furniture industries. The research shows that depending on the stage of the value chain, different Industry 4.0 technologies are more suitable for the support of managers’ decisions. Various Industry 4.0 technologies support decision-making at different stages of the manufacturing value chain. In the Design stage, 3D printing and scanning technologies play a crucial role. In the case of Inbound Logistics, robotisation, automation, Big Data analysis, and Business Intelligence are most useful. During the Manufacturing stage, robotisation, automation, 3D printing, scanning, Business Intelligence, cloud computing, and machine-to-machine (M2M) integration enable quick decision-making and speed up production. Sensors and the Internet of Things (IoT) optimise distribution in the Outbound Logistics stage. And finally, Business Intelligence supports decisions within the Sales and Marketing stage. It is also the most versatile technology among all particular stages. The paper provides empirical evidence on the Industry 4.0 technology support in decision-making at different stages of the manufacturing value chain, which leads to more effective value chain management, ensuring faster and more accurate decisions at each value-chain stage. When using properly selected Industry 4.0 technologies, managers can optimise their production processes, reduce costs, avoid errors and improve customer satisfaction. Simultaneously, Industry 4.0 technologies facilitate predictive analytics to forecast and anticipate future demand, quality issues, and potential risks. This knowledge allows organisations to make better decisions and take proactive actions to prevent problems.
工业4.0技术与管理者跨价值链决策。来自制造业的证据
本文以制造业为例,探讨工业4.0技术如何影响价值链不同阶段管理者决策过程的质量和速度。本文采用定性研究,基于对关键线人的九次深度访谈,以捕捉高级管理人员在其组织中实施工业4.0技术的经验。这项研究主要集中在三个制造业:汽车、食品和家具行业。研究表明,根据价值链所处阶段的不同,不同的工业4.0技术更适合作为管理者决策的支持。各种工业4.0技术支持制造业价值链不同阶段的决策。在设计阶段,3D打印和扫描技术起着至关重要的作用。在入境物流的情况下,机器人化、自动化、大数据分析和商业智能是最有用的。在制造阶段,机器人化、自动化、3D打印、扫描、商业智能、云计算和机器对机器(M2M)集成使快速决策和加快生产成为可能。传感器和物联网(IoT)优化了出站物流阶段的配送。最后,商业智能支持销售和市场营销阶段的决策。它也是所有特定阶段中最通用的技术。本文提供了工业4.0技术在制造业价值链不同阶段的决策支持的实证证据,从而使价值链管理更有效,确保价值链各个阶段的决策更快、更准确。当使用适当选择的工业4.0技术时,管理人员可以优化生产流程,降低成本,避免错误并提高客户满意度。同时,工业4.0技术促进了预测分析,以预测和预测未来的需求、质量问题和潜在风险。这些知识使组织能够做出更好的决策,并采取积极的行动来预防问题。
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
Engineering Management in Production and Services
Engineering Management in Production and Services Business, Management and Accounting-Management Information Systems
CiteScore
3.40
自引率
0.00%
发文量
27
审稿时长
7 weeks
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