IMPACT OF BIG DATA ANALYTICS ON DISTRIBUTED MANUFACTURING: DOES BIG DATA HELP?

M. Sazu, Sakila
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引用次数: 11

Abstract

Big data (BD) analytics has brought progressive improvement in the business environment. It provides businesses with optimized production, personalization and improvement in the way production is dispersed. Nevertheless, conflicts arise in the use of these methods in certain industries, like retail items, which usually basis on large-scale production and prolonged supply chain. The study develops a theoretical structure to investigate if big data coupled with different production solutions can provide for a dispersed production system. Through investigation of twenty-one buyer products business instances applying secondary and main data, the study investigated changing production processes, the inherent catalyst, the function of analytics, and its effect on distributed production. The study discovers several uses of distributed manufacturing principles to evaluate the current production processes worked for larger customer product solutions by using analytics and industry analysis. The evaluation’s suggested structure mentioned in this research has a deeper impact on planning, comprehension relationships, among factors of data analytics and distributed production.
大数据分析对分布式制造的影响:大数据有帮助吗?
大数据(BD)分析带来了商业环境的逐步改善。它为企业提供了优化的生产、个性化和生产分散方式的改进。然而,在某些行业中使用这些方法会产生冲突,例如零售业,这些行业通常基于大规模生产和长时间的供应链。该研究开发了一个理论结构,以调查大数据与不同的生产解决方案是否可以提供分散的生产系统。通过对21个买方产品业务实例的调查,运用次级和主要数据,研究了生产过程的变化、内在催化剂、分析的功能及其对分布式生产的影响。该研究发现了分布式制造原理的几种用途,通过使用分析和行业分析来评估为大型客户产品解决方案工作的当前生产过程。本研究提出的评价建议结构对数据分析和分布式生产要素之间的规划、理解关系有更深的影响。
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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