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Mobil – Plastics Guide 2018


2 Changing industrial landscape


Industry 4.0 – the emergence of the ‘smart factory’ and the use of big data – is changing the manufacturing landscape. The aim of this process is to better utilise a plant’s resources by connecting the devices and analysing production data and equipment use.


2.1 Why care about Industry 4.0? The smart factory, also called ‘Industrie 4.0’ from a German government project to promote the use and integration of computing in manufacturing, is claimed to be the Fourth Industrial Revolution. However, as with the others, it will be more of an evolution (see below). Computers and machine controllers have a long


The Four Industrial Revolutions


1 Industrial revolution Enablers: Coal, water


2 Mass production Enablers: Steel, oil, electricity


3 Computers and automation Enablers: Hardware, software


4 Cyber-physical networks


Enablers: Sensors, learning systems, intelligent networks, Machine-machine data, Big data


history in manufacturing but the smart factory concept is bigger than this. It is about getting machines not only to talk to one another but also to communicate across the site and upwards into the organisation – all the way from the production process to business planning and logistics (and back again). In the smart factory, these layers will all transfer data across, upwards and downwards to give greater control of the company and – hopefully – to get greater information out of what will become


4 Data are not the same thing as


information. Data are a collection of numbers whereas information is what allows management (or machine) action to be taken


mountains of data. In the smart factory, these layers will all transfer data across, upwards and downwards to give greater control of the company and – hopefully – to get greater information out of what will become mountains of data.


The smart factory layers – from the process to the business and back again


Business planning and logistics


Basic production schedule, material use, delivery and inventory levels. Time: Months, weeks, days


Data Manufacturing operations management


Work flow, production details, product controls. Records to optimise the process. Time: Shifts, hours, minutes, seconds


Data Manufacturing control


Monitoring, supervising and process control. Sensing and controlling the process. Time: Hours, minutes, seconds


Data


Production process The physical production process. Time: Minutes, seconds


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