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How to build a smart factory for small and medium manufacturers

In the swarm of buzzwords surrounding today’s manufacturing sector, the “Smart Factory” or “Factory of the Future” buzz is especially prominent. In this white paper featuring experts from Siemens Digital Industries Software, we’ll unpack the meaning of the term, examine key considerations in understanding its value and explore a few important takeaways for small and medium businesses (SMBs) to take advantage of these technologies.

The benefits of a flexible manufacturing approach

A smart factory is a manufacturing facility that uses advanced technologies such as artificial intelligence and digital twins along with the Internet of Things (IoT), to improve efficiency and productivity. In a smart factory, machines and other equipment are connected to each other and to a central network, allowing them to communicate and share data in realtime. This enables the factory to respond quickly to changing conditions and customer demands. Smart factories also incorporate automation and robotics to perform tasks more accurately, consistently and efficiently than humans could. “The cost of breaking a tool digitally is zero. The cost of breaking that tool on the machine is pretty huge.” Rahul Garg says.

Leveraging Industrial Internet of Things and predictive maintenance

One of the challenges that manufacturers face as they begin to collect equipment monitoring data is what exactly to do with it. High-frequency data such as vibration or temperature readings can quickly stack up to massive quantities of digital data. Without the tools and strategies in place to parse it, it’s useless and may even become a hindrance.

The smart factory brings intelligence to that data collection. A sensor can tell you that a vibration of a motor housing is increasing, but smart analytics can tell you which bearing needs to be replaced. That’s the gap between data collection and actionable data.

Use a digital twin to build your factory of the future

A digital twin is a virtual representation of a physical object or system. It is created by using data from sensors, computer-aided design (CAD) models and other sources to create a detailed, real-time simulation of the object or system. In manufacturing, a digital twin can help optimize processes and identify potential problems before they occur.

For example, as Garg mentioned, a digital twin of a factory floor could be used to simulate and test different production scenarios, allowing manufacturers to identify bottlenecks and inefficiencies before they occur in the real world. Digital twins can also be used to monitor and control the performance of a physical object or system.

Simulation software has been used for many years in manufacturing for applications such as robot programming, product design and CNC toolpath programming. But advances in computing power and data access have vastly improved the value and quality of simulations to the point where, according to Garg, even the commissioning process of a machine on the shopfloor can be simulated. Every step of a process can be simulated, avoiding costs such as line stoppages and mistakes

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