Moving up to the next level with AI

04 May 2018

Employing artificial intelligence within the manufacturing process is the key to taking a business to the next level in the era of Industry 4.0, says Tim Clark.

A fundamental requirement for all manufacturers is to achieve the highest revenues with the best margins and the lowest costs. Further products need to be of a consistently high quality when produced. There is also a requirement to ensure the product is shipped to the right place at the right time and you want to ensure you have as few product returns or failures while in service. 
Everyone will have seen the tree swing cartoon. It's been around for years, but still offers a good illustration of the importance of focus, data, insight and collaboration for manufacturers.

The level of complexity, speed and detail in modern manufacturing processes has become almost impossible to manage via manual or human effort alone. This complexity also increases the risk of the misunderstandings highlighted by the tree swing cartoon. Assistance from technology and engineering have been prevalent since the introduction of the steam engine, but as industry navigates into Industry 4.0, artificial intelligence (AI) is becoming a common theme.
Artificial means made by humans, especially in imitation of something natural. Intelligence is the ability to acquire and apply knowledge and skills. So, we have been applying AI for some time, but are now applying it to computers.
AI in manufacturing
When artificial intelligence is applied to the manufacturing process, it should be about understanding data, extracting insight and learning from the outputs. Analytics is about iteration and learning, and as we learn we change or influence the next step. This process can also be referred to as machine learning, meaning that the machine carries out this iterative process without the need for human intervention.
The benefits of machine learning are wide and varied, and in the right hands can add value to a business through high levels of automation. Machine learning can identify previously unseen relationships and influence processes or data sets, and extract insights quicker and in more detail than has been possible in the past. 
Proven results
Many software vendors will lay claim to having AI, cognitive and machine learning capabilities. While many can provide these to some extent, the evolution of any technology demonstrates that the more you focus on it, invest and develop it, the better you are at it. SAS has taken its knowledge to harness the Power to Know into the manufacturing world. It has connected processes and capabilities around monitoring machines, systems and data in the make process, and can join this to post-production analysis around forecasting and supply chain processes to aid future planning. This is paired with data driven analytical approaches to customer engagement and post-sale monitoring of product performance, service requirements and infield product satisfaction. 

All successful businesses invest in operational platforms like ERP, finance and billing systems. More recently business have seen extensive value in productivity platforms with office tools and CRM systems. Now the next wave is here - analytical platforms that encompass AI and machine learning to support the organisation beyond the traditionally used key performance indicators.
Tim Clark is head of manufacturing solutions at SAS.

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