Manufacturing Optimization Based on Agile Manufacturing and Big Data

被引：1

作者：

Alam, Khan Md Ashikul ^{[1
]}

Mebrahtu, Habtom ^{[1
]}

Shirvani, Hassan ^{[1
]}

Butt, Javaid ^{[1
]}

机构：

[1] Anglia Rusk Univ, Chelmsford, Essex, England

来源：

ADVANCES IN MANUFACTURING TECHNOLOGY XXXI | 2017年 / 6卷

关键词：

Agile manufacturing (AM); Big Data (BD); Process Re-engineering (PR); Process Mapping (PM);

D O I：

10.3233/978-1-61499-792-4-345

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

This paper investigates Agile Manufacturing (AM) supported by Big Data for manufacturing optimization. The paper aims to identify the limitations of current manufacturing approaches such as just in time(JIT) and lean manufacturing and to map a process based on these limitations. The process works through a process re-engineering (PR) by eliminating and redesigning the steps that affect productions. The process will identify the key enablers that will assist in the design of an effective AM framework for process optimization.The paper also discusses the integration of Big Data (BD) as a major source of information to the manufacturing input. It will try to identify the extent the BD can be useful in manufacturing optimization. In the process, it will look at a specific kind of data like machine sensor data, Enterprise data, social network and website data and design a framework to bring all the information together for us in the manufacturing process.The paper will analyse and design an integration process framework of AM and BD as a new approach to manufacturing for optimal production.

引用

页码：345 / 350

页数：6

共 13 条

[1] An analysis of the direct and mediated effects of employee commitment and supply chain integration on organisational performance [J].