What is a Smart Factory?

smart factory

Smart factories empower production with intelligence, IoT, and other technologies. They increase asset efficiency, reduce costs and improve safety.

As a result, smart factory implementation can be a major driver of business growth and revenue generation. It’s also a crucial factor in employee engagement.

Visibility

Smart factories are built with real-time visibility into the entire production process. This includes connections of machinery, tooling and materials to offer operators a clear picture of their production chain.

This allows for asset usage and intra-factory logistics optimization as well as employee safety. In addition, visibility can be used for monitoring equipment performance, enabling proactive maintenance plans and better estimates of life expectancy.

Visibility is also a critical component of business planning, forecasting and projections. It can help businesses determine the future of their business and its ability to maintain or increase profitability.

A smart factory is a cloud-based system that relays data in real time to provide greater optimization abilities. This includes the ability to track production, automate and digitize processes. This leads to increased agility, faster production and issue resolution at speed.

Connectivity

Smart factories connect machines and devices across the entire factory through a cyber-physical system to collect data and improve processes. This enables the factory to proactively address issues and respond to new demands. 스마트공장

With the rise of consumer expectations for faster delivery, more customization options, and better transparency, there has never been a better time to make your factory more digital. By collecting and analysing data, a smart factory can optimise processes from procedural improvements to inspection and maintenance, logistics, staff utilisation, and more.

A smart factory has the capability to utilise sensors, which provide the real-time visibility required to monitor machine conditions and detect disruptions that can impact production. These can include optical sensors that use image capture to identify issues with materials or machinery, as well as pressure, vibration, proximity, and contact sensors to detect abnormalities within production.

Getting the most out of smart factory technology requires a robust infrastructure that allows for real-time connectivity through cloud, edge computing and 5G. Without these, manufacturers won’t have a true “smart” factory.

Autonomy

A smart factory is a highly digitized and connected production facility. The result of the fourth industrial revolution, Industry 4.0, it uses technology such as automation, AI, robotics, big data and analytics to run largely autonomously with the ability to self-correct.

In the first phase of smart manufacturing, equipment and systems function mainly on their own but are controlled by humans when necessary. In the second phase, automation becomes more prevalent and machines become even more autonomous.

The third and final stage of the move towards autonomy is to give machines and cyber-physical systems (CPS) full independence from centralized control. This means empowering CPS to make production process decisions independently, if they don’t violate high-level business goals.

Analytics

Smart factory data analytics are the backbone of the digital manufacturing revolution. They provide real-time operational visibility and insights that enable a highly automated production system, dramatically improving business performance.

Using data from sensors, motors and robotics, smart factories can identify and predict machine failures, and schedule preventive maintenance to avoid downtime and increase productivity. They also use predictive quality monitoring to detect quality issues before they lead to expensive returns or recalls.

The resulting high level of automation also helps factories achieve real-time response to shifts in demand, so they remain competitive and responsive.

At the next level, smart factories can apply AI and machine learning to ingest historical data from equipment and processes to make “what-if” predictions. These prescriptive algorithms can then help optimize production resources by recommending actions to address any upcoming manufacturing challenges. 스마트공방

As industrial IoT and smart factory technologies become more common, they are generating vast amounts of operations data that need to be unlocked in novel ways. That means next-generation analytics systems must be able to find meaningful trends and correlations across multiple industrial IoT touch points.