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)
DOI: 10.4018/978-1-4666-8505-5.ch013
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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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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.

Key Terms in this Chapter

Supply Chain Management (SCM): An integrated approach to planning, implementing and controlling the flow of information, materials and services from raw material and component suppliers through the manufacturing of the finished product for ultimate distribution to the end customer. It includes the systematic integration of processes for demand planning, customer relationship collaboration, order fulfillment/delivery, product/service launch, manufacturing/operations planning and control, supplier relationship collaboration, life cycle support, and reverse logistics and their associated risks.

Manufacturing Information Systems: A management information system designed specifically for use in a manufacturing environment. The role of manufacturing information systems is to support manufacturing operations by providing relevant and timely information for decision making at different levels of the company hierarchy. It also automates and secures the sequencing of manufacturing and business processes.

Product Data Management (PDM)/ Product Life-Cycle Management (PLM): PDM is a category of computer software used to control data related to products. PDM creates and manages relations between sets of data that define a product, and store those relationships in a database. It is an important tool in product lifecycle management. PLM is a strategic business approach that applies a consistent set of business solutions that support the collaborative creation, management, dissemination, and use of product definition information throughout the lifecycle of the product.

Manufacturing Execution Systems (MES): A control system for managing and monitoring work-in-process on a factory floor. An MES keeps track of all manufacturing information in real time, receiving up-to-the-minute data from robots, machine monitors and employees.

XML: Stands for “Extensible Mark-up Language. XML is used to define documents with a standard format that can be read by any XML-compatible application. It is a file format-independent language, designed primarily to enable different types of computers to exchange text, data, and graphics by allowing files to be shared, stored and accessed under different application programs and operating systems.

Unified Modelling Language (UML): UML is a standard language for specifying, visualizing, constructing, and documenting the artefacts of software systems. It is also used to model non software systems as well like process flow in a manufacturing facility.

Enterprise Resource Planning (ERP): Automation and integration of a company's core business to help them focus on effectiveness & simplified success. ERP software applications can be used to manage product planning, parts purchasing, inventories, interacting with suppliers, providing customer service, and tracking orders. ERP can also include application modules for the finance and human resources aspects of a business.

STEP/STEP-NC: STandard for the Exchange of Product model data, a comprehensive ISO standard (ISO 10303) that describes how to represent and exchange digital product information. STEP is a means by which graphical information is shared among unlike computer systems around the world. It is designed so that virtually all essential information about a product, not just CAD files, can be passed back and forth among users.

Machine-to-Machine (M2M): A term used to describe any technology that enables networked devices to exchange information and perform actions without the manual assistance of humans. M2M is considered an integral part of the Internet of Things (IoT) and brings several benefits to industry and business in general as it has a wide range of applications such as industrial automation, logistics, Smart Grid, Smart Cities, health, defence etc. mostly for monitoring but also for control purposes.

Manufacturing Operations Management (MOM): The subsequent system to Manufacturing Execution System (MES) software which expands focus from a single facility to the entire supply network and monitors a variety of aspects of the manufacturing process, including production capacity analysis, Work-in-Process (WIP), inventory turns and standard lead times.

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