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    Smart Factories

    12 May 2022, 9:03 AM
    Smart Factories

    What are Smart Factories?

    Smart factories bring together digital and physical systems with a range of cutting-edge production, information and communication technology. They are a concept expressing the end goal of the digitisation of manufacturing.  The highly digitised factory floor continuously collects and shares data through connected machines, devices and production systems. The data shared can then be used to proactively address issues, improve processes and respond to demands.

     

    What technology do they use?

    • Sensors

      • They can be attached to devices and machines help collect distinct data points at specific stages during a process and can provide instant visibility into various layers of the factory floor. The data collected through these sensors can also be used in self-correcting processes using AI or by alerting the relevant people.

    • Cloud Computing

      • It enables factories to store, process and share data with greater flexibility at lower costs than traditional on-premises alternatives like servers.

    • Industrial Internet of Things

      • IIoT uses interconnected devices, machines and/or processes linked by data communication systems to facilitate exchange and use of data between people and machines.

    • Blockchains

      • They increase transparency and trust as they can record the origin and movement of a digital asset in decentralised distributed ledgers. They are largely unproven on the factory floor, but they could be able to address key issues like monitoring supply chains, counterfeit detection, asset tracking, quality assurance and regulatory compliance.

    • Additive Manufacturing

      • This uses machines or robots to 3D print components or parts by depositing material, usually in layers.

     

    Other Technology:

    • Data Collection Programmes

    • Artificial Intelligence

    • Augmented Reality

    • Simulations

    • Machine Learning

    • Collaborative Robots

    • Industrial Robots

    • Wireless Connections

     

    What are levels of Smart Factories?

    Level 1 – Available Data

    This is the level that is likely the status of most factories currently. They have the data available, but it is not accessible as it requires sorting and analysing before it can be of any use as it is stored in different systems. It is incredibly time consuming to sort as a manual task which adds more inefficiencies to the production improvement processes. Problem solving is possible at this level when issues arise with machinery or product quality however, the engineers must gather data from the various systems before they can determine how to fix it. This makes it costly and time-consuming while draining resources.

     

    Level 2 – Accessible Data

    At this level the data is presented in a more digestible form as it is structurally organised in one location, with systems and dashboards that help engineers visualise it. The systems also track production data and can perform proactive analysis, which still requires some time, effort and engagement from engineers. Proactive analysis enables factories to make improvements before issues occur. Engineers can solve issues faster, increasing productivity, and allowing them to focus on addressing high-value issues like improving a product.

     

    Level 3 – Active Data

    Using machine learning and AI insights can be generated without much human supervision by proactively analysing data. The system can start generating insights in as little as 3 months. At this level, the system can identify key issues and anomalies to predict failures with high accuracy and inform the relevant people at the right time. This enables engineers to be able to carry out preventative repairs and reduce the downtime of the equipment.

     

    Level 4 – Action Oriented Data

    Level 4 uses machine learning to generate recommended actionable solutions to identified issues, from machines and devices that are connected to the system. The system can carry out the changes with no human intervention needed and the time taken to carry out an insight is minimal. The datasets required for this level need to be large enough and have enough validated cases to provide the information needed for the system to know the impacts of change.

     

    What are the benefits of implementing a Smart Factory?

    Smart factories reduce losses in profits caused by unplanned downtime by using AI and machine learning to predict when maintenance is needed. Machine learning makes the manufacturing process more adaptable as it helps to optimise production and can better react to production demands.

    Waste can be minimised as processes become more accurate. Constant monitoring from the software can reduce production processes costs and time while helping to improve the environments safety. As the environment is made safer, the workplace injury rate and physical demands on workers are reduced. Consistent monitoring also enables better quality control of products.

    The systems installed provide improved predictability, boosts to productivity by extending the capabilities of manufacturing devices, and opportunities for growth without investing in additional physical resources.

     

    What are the disadvantages of implementing a Smart Factory?

    The initial costs of implementation are normally incredibly expensive which small and maybe even medium sized companies will not be able to afford. Even though the amount of staff required is reduced the amount of energy usage and therefor cost will increase. The technology used is complex to develop and set up, so if the system is poorly designed or there is a small glitch it could affect overall profits. How the system works also needs to be known by more than one person in case any issues arise. Cyber security needs to be enhanced which could be expensive. If the cyber security is not adequate and it does get breached it could cause major issues with machines, their output products or their safety.


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