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Three things you need to know about Industry 5.0
While manufacturers are still getting accustomed to methods for interconnecting new technologies to improve efficiency and productivity – the guiding principle behind Industry 4.0, the next phase of industrialisation is already on the horizon, says Richard Mount, director of sales at ASIC design supply specialist Swindon Silicon Systems
t’s pretty well understood that Industry 4.0 refers to the integration of automation and data exchange in manufacturing. Underpinning the era are an enhanced use of data and connected devices, advanced analytics and machine learning, a deeper human-machine connection and advanced engineering technologies such as 3D printing. Industry 5.0 takes these qualities a step further. Broadening the concepts of Industry 4.0, this new industrial revolution is described by the European Union as providing “a vision of industry that aims beyond efficiency and productivity as the sole goals, and reinforces the role and the contribution of industry to society”. Talking about Industry 5.0 right now may appear
I
hasty. After all, we’re still very much in the midst of Industry 4.0. However, given the rapid rate of technological advancements such as AI and machine learning, it’s helpful to start considering how the next industrial era could take form.
Hyper personal
There are many instances where personalisation already succeeds – no two Netflix homepages look the same depending on the user’s preferences, and the menus of some of the world’s biggest restaurant chains allow diners to add and subtract meal components to their liking. But what about in a manufacturing context – how can it embrace the mass customisation era?
Mass customisation sounds like something of an oxymoron. However, with the principals of
Industry 5.0, it will become possible to bespoke manufacture at scale. Advanced technologies, like 3D printing and computer aided design, will certainly be central to its development. Production techniques aside, mass personalisation relies on gathering and using data to understand individual preferences and deliver customised products. Manufacturing companies can leverage big data analytics, AI and machine learning to process vast amounts of data. By analysing customer preferences, purchasing patterns and demographic information, manufacturers can tailor products to meet individual needs. This data-driven approach helps in creating personalised product configurations, packaging, branding and pricing.
At a manufacturing level, data is also crucial to making personalisation happen. For instance, through digital systems and databases, manufacturers can access the specifications of individual customers to guide the manufacturing process and ensure that the personalised products are produced according to the desired configurations.
Data also enables real-time monitoring of production processes. By integrating data from sensors and IoT devices, manufacturers can track the progress of personalised products throughout the production line. This real-time monitoring helps in identifying and addressing any deviations or issues that may arise, ensuring that the personalised products are manufactured accurately and efficiently.
Man and machine Where Industry 4.0 has focused on ensuring consistency of quality, flow and data collection, Industry 5.0, while still focused on these goals, puts more attention on highly-skilled people and robots working side-by-side. Naturally, this will further ignite the presence of collaborative robots, or cobots, on factory floors.
While historically cobots have not been as popular as industrial robots, several drivers have been proposed to accelerate their adoption, including Industry 5.0. However, as robots become free of their cages and work closer to humans, it is vital that robots have accurate control over their movements.
Cobots use a number of sensors to choose paths, perceive changes in the environment and make correct judgements in complex situations. For example, torque sensors give robots a sense of ‘touch’, enabling them to interact safely with their environment. Most torque sensors employ strain gauges, which convert applied pressure into an electrical signal that can be measured. By combining multiple gauges, the torque sensor can determine the intensity and direction of the force. This allows cobots to delicately handle and assemble fragile items without causing damage. To help cobots successfully distinguish between inanimate objects and their human colleagues, tactile sensors such as piezoelectric, piezoresistive, capacitive and elastoresistivity types are used. Piezoelectric technologies can gather
16 ELECTRICAL ENGINEERING • JULY/AUGUST 2023
electricalengineeringmagazine.co.uk
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