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A short Introduction

Factories are now in a privileged position because they can monitor every aspect of their production process in real time by connecting all pieces of equipment to the internet. Moreover, implementing smart algorithms will facilitate project and operations managers to control every aspect of the production process, to find out when a machine will need maintenance, and when they need to adjust production due to changes in demand which will lead to lower production costs and improved efficiency.

Factory equipment functions after well-established standards and norms. In many instances, monitoring all equipment is done via digital, analogue, or mechanical sensors mounted on a piece of equipment or products. Unfortunately, tracking many of these sensors requires human intervention; an operator physically reads the sensor output and records it in different Latest developments in hardware and software helped lower sensor and computing costs. Thanks to companies like Amazon, Microsoft, or Google, we now have unprecedented access to virtually infinite computing and storage power at reasonable prices. Furthermore, hardware components like gateways, microprocessors, and sensors have an excellent price-quality ratio. All these developments enable us to connect factory equipment via sensors and gateways to a centralised or distributed computing centre (that can be cloud-based or local).

Through this newly created network, sensors can transmit data to the preferred storage place in real time. Next, we can visualise all the data from every sensor as well as develop new statistical analyses to understand the production process better. Together, these operations lead to increased data visibility of all factory processes. Furthermore, we use these data to develop relevant metrics to evaluate factory performance, creating a method of monitoring KPIs in real time.

Possibly the most important advantage of this system is that it creates the possibility to access data about any equipment in real-time. This ability is crucial for making decisions on factory performance or for finding areas where to allocate the next investments.

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