KNOWLEDGE BASE 16 HYDRAULICS & PNEUMATICS June 2023 www.hpmag.co.uk computing and understand how it can continue to make an impact in the future. While most manufacturers have embraced the cloud in some capacity, research suggests that some remain concerned about legacy integration and the performance of applications in the cloud. This indicates that there may still be some hesitancy to go ‘all-in’ and this could be a concern as the industry looks to thrive, not just survive, in the current business landscape. Cloud computing is not just the enabler of industry 4.0 but also wider digital transformation. It is the foundation in which most advanced technologies, such as the IoT and realtime data analytics, operate, and can be scaled up or down to manage shifting project workloads, react to demand and improve visibility across the business. In the context of the supply chain crisis, this can have a real positive impact. For instance, the shortage of cars has been a permanent fixture on the news agenda over the last two years, with long waiting times in production. For many original equipment manufacturers, the cloud has been a game-changing solution in maintaining levels of customer experience. It has facilitated greater end-to-end visibility of the supply chain, meaning faster and more accurate customer communications, as well as the capacity to forecast demand, plan in advance and improve the efficiency of the production line. The power of the Industrial Internet of Things At a time where the future of industry remains in flux, determined by the outcome of global events, the Industrial Internet of Things (IIoT) has a critical role to play in supporting manufacturers to be agile to change. Unlike the IoT which is commonly used as an umbrella term for connected consumer devices, like a smart watch, the IIoT uses connected machines, devices and sensors in industrial applications such as robotics. These devices produce large volumes of data that when analysed, can improve efficiency, productivity and visibility, both in manufacturing and along the supply chain. To explore this further, the IIoT is pioneering a concept called smart factories. While the concept of automation has been in use in manufacturing for decades with barcode scanners, cameras and digitised production equipment, those devices are rarely interconnected. Instead, the people, assets and data management often operate in isolation and must be processes at an exorbitant cost to read and analyse this data, but this is no longer necessary. During a crisis or business uncertainty, manufacturers need to move fast and make smart, accurate choices. Slow, costly data insights could be the difference between making the right or wrong choice. Through machine learning and real-time analytics platforms, manufacturers can accelerate connectivity across the business, collecting and analysing data at speed and scale. In practice, this means they can pivot faster to changes in trading conditions or identify and address issues before they reach the customer. This could be machines in need of repair, maintaining field equipment or adjusting their supplier based on the availability of chips or raw materials. Helping companies meet their sustainability targets Innovative companies are now able to drive comprehensive sustainability agendas while boosting their bottom line and market share – but how are they doing this? Conscious that all stakeholders, from investors to end users, are asking companies to reduce their carbon footprints, forward-thinking enterprises are specifically targeting manufacturing processes to make sustainability improvements. In fact, Industry 4.0 is specifically able to enable this by improving operating efficiency, optimising cost and eliminating sustainability issues right at the point of product design. By harnessing the power of automation, augmented reality, AI/Machine Learning and the IoT, Industry 4.0 can promise improved methods of production and enhanced business models. With Scope 3 emissions accounting for 80-90% of your total emissions, this can be a game-changer for organisations with their eye on the environment. Ultimately, the manufacturing industry has experienced greater disruption and challenge in the last decade than the previous three combined. As before, manufacturers looking to resurface ahead of competitors need to be bold and take a leap of faith on embracing new technologies and processes. It’s here that they must recognise the role of industry 4.0 technologies, in the cloud, IIoT and Big Data with real-time analytics, in helping them to successfully navigate the ongoing supply chain crises and geopolitical complexity, while maintaining business continuity and a level of service end-customers have come to expect. For further information please visit: https://www.sap.com/uk manually coordinated and integrated on an ongoing basis. Through the IIoT, manufacturers are able to build an interconnected factory by collecting disparate sets of useful data across the business and supply chain. This can then be stored and actioned to inform product development or quality control. Moreover, in the case of global challenges such as the blockage of the Suez Canal in 2021 or the start of the conflict in Ukraine, the IIoT allows manufacturers to be proactive, as opposed to reactive, to crises. Spotlighting the Suez Canal blockage, for instance, during the period of severe supply chain disruption - it was the IIoT that supported manufacturers with contingency planning, understanding where raw materials were and which suppliers had them, enabling them to mitigate against disruption. Managing the tide of data While large quantities of data at your fingertips is paramount, it can easily go to waste without the ability to effectively manage and analyse it in real-time. This is where Big Data management, machinelearning and real-time analytics play an important role in supporting industry leaders to glean the best insights from their data, and inform smart strategic choices. Typically, manufacturers will produce vast amounts of both structured data and unstructured data. Structured data is the simplest to organise and search, and can include financial information and machine logs, like an Excel sheet - that can be easily categorised and doesn’t require intensive resources to manage. Unstructured data, on the other hand, typifies the volume of information produced by connected machines, and isn’t as easily captured. Today, manufacturers still use laborious manual Greg Moyle
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