Big Data and Data Modelling for Manufacturing Information Systems

Big Data and Data Modelling for Manufacturing Information Systems

Norman Gwangwava (Botswana International University of Science and Technology, Botswana), Khumbulani Mpofu (Tshwane University of Technology, South Africa) and Samson Mhlanga (National University of Science and Technology, Zimbabwe)
Copyright: © 2016 |Pages: 23
DOI: 10.4018/978-1-4666-9840-6.ch007
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Abstract

The evolving Information and Communication Technologies (ICTs) has not spared the manufacturing industry. Modern ICT based solutions have shown a significant improvement in manufacturing industries' value stream. Paperless manufacturing, evolved due to complete automation of factories. The chapter articulates various Machine-to-Machine (M2M) technologies, big data and data modelling requirements for manufacturing information systems. Manufacturing information systems have unique requirements which distinguish them from conventional Management Information Systems. Various modelling technologies and standards exist for manufacturing information systems. The manufacturing field has unique data that require capturing and processing at various phases of product, service and factory life cycle. Authors review developments in modern ERP/CRM, PDM/PLM, SCM, and MOM/MES systems. Data modelling methods for manufacturing information systems that include STEP/STEP-NC, XML and UML are also covered in the chapter. A case study for a computer aided process planning system for a sheet metal forming company is also presented.
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Background

Industry has evolved from traditional factories dominated by mechanical production facilities powered by steam and water, through mass production based on division of labor, to introduction of electronics and IT, and currently cyber-physical systems (CPS). Koren (2010) categorized the industrial revolution into four phases namely industry 1.0, industry 2.0, industry 3.0, and industry 4.0. Industry 4.0 is the current stage which is driven by cyber-physical production systems. Rajkumar, et al (2010) defined Cyber-physical systems (CPS) as physical and engineered systems, whose operations are monitored, coordinated, controlled and integrated by a computing and communication core. CPS can be considered to be a confluence of embedded systems, real-time systems, distributed sensor systems and controls. CPS is leading towards smart future factories with a network of intelligent objects linking products and assets with information from the internet, as well as capturing context information.

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