Digitalisation is boosting the market for increasingly sophisticated manufacturing automation technology. Neli Ivanova, Sales Manager, Industrial Equipment at Siemens Financial Services in the UK examines how integrated finance helps OEMs and their customers capture the benefits of automation in a financially sustainable way.
Automation has been commonplace in the manufacturing sector for decades and can now be found in nearly every sector of industry. Automated systems that reliably perform repetitive, standardised tasks continue to enable manufacturers to operate with greater efficiency.
This is evidenced not only by speedier production rates but also aspects such as reduced factory lead times, more efficient use of materials, and increased control over product quality and consistency. And yet, compared to other advanced economies, the UK invests relatively little in industrial automation and robotics.
This is surprising, as around 92 per cent of UK manufacturers are convinced that ‘Smart Factory’ technologies will help them increase their productivity levels. But manufacturers are often, unsure where to begin when modernising their production process, concerned about ongoing costs, and worried that their products and processes are too bespoke to automate. Private sector finance can help relieve some of these pressures when investing in new technology by offering flexible financing solutions that are tailored to the needs of manufacturers.
One example of digitalisation in the manufacturing sector is the introduction of cloud platforms. By using cloud-based, open IoT operating systems such as Siemens Mindsphere, manufacturers can connect their products, plants, systems, and machines to collect, analyse and harness data from every area of the factory floor.
Cloud-based systems can also allow manufacturers to connect to customers and suppliers in order to understand their supply and demands, and tailor production processes to the requirements of the entire supply-chain. Moreover, these operating systems enable manufacturers to analyse real-time digital data such as vibration indicators and quality analysis, in order to make them aware of alerts and impending faults that cannot be identified by humans. This kind of predictive maintenance allows manufacturers to spot warning signs of problems before they occur, preventing damage to the machine and saving the cost of repair and machine downtime.
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