Neli Ivanova, Sales Manager, Industrial Equipment at Siemens Financial Services in the UK, discusses how leveraging the data gathered by the Internet of Things (IoT) can make predictive maintenance and product optimisation possible.
The UK is the 9th largest manufacturer in the world by output. As a central pillar of the UK economy, the manufacturing industry relies upon technological innovation to remain competitive in the global market. The introduction of the Internet of Things (IoT), in particular, has propelled industry growth by making production processes more efficient, reducing operating cost and machine downtime and encouraging innovation and investment in the industry.
What does IoT mean to manufacturers?
For manufacturers, the biggest source of value in manufacturing IoT is in the vast amounts of data to be collected and analysed by IoT devices. What drives process improvement and cost reduction is the ability to analyse and utilise the collected data intelligently. Such data can automate decision-making making it faster than humans could ever achieve.
Other applications of IoT include using machine-learning to hone production levels in real-time without human intervention. Similarly, the ability of machines to perform predictive analytics, helping to prevent downtime and optimise performance, is of great potential value to manufacturers.
What benefits can manufacturers derive from predictive maintenance analytics?
The shift from reactive to predictive maintenance, prompted by fault detection, requires advanced machine learning capabilities. This is because it usually employs sound and vibration analysis to detect if a machine is working outside of normal conditions. This process involves examination of thousands of data points from multiple sensors in order to evaluate what might affect the functionality of a machine.
With the right data analytics tools, the advantages of predictive maintenance are substantial. For instance Siemens’ cloud-based IoT operating system, MindSphere, analyses real-time digital data streams from equipment and alerts manufacturers to impending faults that can’t be identified by humans.
By intelligently combining data analytics and predictive maintenance, technicians will know in advance what is wrong when fixing a problem and what parts may need replacing. In addition, predictive maintenance can prevent more serious issues occurring. For example, machines have the capability to slow production if there is a risk of overheating. Performance optimisation is another key area in which value can be created through the predictive use of IoT data analytics. Similar to running maintenance diagnostics, performance data can help create more efficient manufacturing operations. By analysing real-time data across the factory floor, decision-makers and machines can tweak processes in order to achieve greater efficiency and minimise waste.
How can finance support OEMs and their customers’ transition to IoT and data analytics?
The fast pace of innovation in manufacturing IoT means manufacturers are under growing pressure to invest in constantly evolving equipment and technology upgrades. This requires significant capital, which is often tied-up in operational and staff costs.
This gives OEMs the opportunity to create new business opportunities for themselves and for their customers. By working with a specialist financier, OEMs can offer financing solutions such as leasing and pay-for-outcomes agreements whereby the savings or gains made possible by newly acquired technology funds the customer’s monthly repayments. Such financiers have an in-depth understanding of the sector. They will consider the cost savings and/or expected benefits for the term of the agreement and factor that into the financing arrangement. In this way, manufacturers gain immediate access to the latest equipment and technology, without having to commit scarce capital or use traditional lines of credit.
Data has so far mainly been used in a reactive capacity, even though the real value to IoT is in pre-emptive data interpretation and analysis. Offering new equipment and technology as a service with flexible and tailored financing can enable OEMs to deliver intelligent solutions to their customers that cater to their specific needs. As such manufacturers can invest in the newest equipment and technology sustainably, make use of data analytics, and enter the next stage of Industry 4.0.
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new.siemens.com/global/en/products/financing.html
