July 2019

www.smartmachinesandfactories.com July 2019 | 23 | | STRATEGIES | journey can apply what they have learned to their systems and products to bring the benefits of smart automation to customers, carrying out experiments in smart automation and learning where bottlenecks occur. In the end, only by performing this research in real factories can the real value be uncovered. Human-machine interaction Building on data collection and analysis, smart automation can be extended into the realm of human- machine interaction. Nowadays robots have the capabilities to become budding ping-pong champions – as just one example – capable of observing the motion of an opponent facing it on the other side of the table, along with cameras that watch the ball’s movement. Analysing data from sensors, it can calculate movement very precisely and quickly, to anticipate how the opponent will hit the ball and its trajectory. How difficult or easily they return the ball gives a clue as to one way this smart machine can be used to general advantage. By being able to assess how its opponent plays, it can determine their skill level. Robots can modify their own playing level to get the best from an opponent, if playing at a slightly better level, the opponent will have a challenging game without becoming frustrated. Hence, smart machines can also be used to train people. On-the-job training This training aspect can be applied to all kinds of machine applications and is ideal for the manufacturing industry. Smart robots can assess the operator’s level of expertise when interacting either with the robots themselves or with the systems being assisted by the robots – such as heavy lifting where the robot takes the weight of the object, but the operator makes fine adjustments for placement. In this case, the robot uses its appraisal of the operator’s ability to help train them or make the task easier by giving them more guidance. With an increasing focus on data, machines equipped with artificial intelligence are becoming one of the most promising technologies of the fourth industrial revolution. In the coming years, AI is likely to further revolutionise science across all sectors. However, before such time it is vital that manufactures use their machines integrated with AI to transform production. While this provides benefits such as smart automation and improved efficiency, this can now make it far more joyous to work all smart machines, particularly robots . For example, they have the ability to provide unique interactions, personalised to specific workers, recognising who is working on the assembly line, while providing meaningful tips and advice on the job in hand. With data providing such a key role in smart factories, learning from human- interaction, this is able to boost efficiency and productivity. There would be no interactive and integrated machines today without traditional engineering, this is vital to remember when moving into digitalised industrial future. It only takes data, lots and lots of data science, to harness machines full potential and make them ‘smart’, this is important with the need to digitalise the lifecycle of any automotive solution.