In 2018 discrete manufacturing will be the third largest industry for spending on Artificial Intelligence (AI), with $2.0 billion[i] being invested worldwide into areas such as automated preventive maintenance. In addition, $189 billion will be spent on Internet of Things (IoT) solutions, continuing to make IoT the largest spending category in manufacturing[ii].

Traditionally, AI has been used to augment human capabilities and facilitate better decision-making, while IoT is leveraged to analyse, optimise, and automate business processes. However, such technologies can go a lot further in aiding manufacturers to build more customer-centric processes. By this, we mean building processes that create transformative experiences, adapt to evolving customer demands, and deliver a truly customer-centric vision. When it comes to Industry 4.0 implementations, manufacturers rank improving customer-facing operations as a top priority within the next three years. Half will focus on the removal of data silos, while 47% agree creation of open data exchange with their partner network is crucial[iii]. But how can technology be used to achieve all this?

Product Design
In a normal design process, feedback is usually interpreted through sales figures and any consumer complaints that arise. This tends to occur a long time after product development and production have taken place. Using IoT and AI, engineers can apply learnings from data analytics to inform decision making much earlier. Learning dynamically and in real time during early development cycles and applying iterative improvements based on these insights, can enhance the finished product, and ultimately customer satisfaction. The endless feedback loop from genuine in-life products is a gold mine. And knowing how and when your customers truly use their purchases, rather than working on assumptions, can be a game changer.

Streamlining Logistics

IoT sensor data presents one way manufacturers are seamlessly connecting their physical and digital logistics flow. By utilising the capabilities of innovative warehouse management systems as well as transportation and track and trace software, data can be viewed from IoT-enabled devices. This, in turn, facilitates supply chain activities such as immediate inventory checking, scheduling accurate delivery times, and sharing real-time data across your supply chain partner network. Manufacturers can gain real-time access to vehicles’ locations, without having to contact drivers for updates. This enables faster customer response, even in the event of extreme weather conditions or traffic delays. With a connected supply chain and logistics-specific automation, your customers get exactly what they want with accelerated order fulfillment and efficient delivery.

Predictive Maintenance and Prevention
By utilising predictive maintenance, manufacturers can boost equipment reliability and stay ahead of some of the unexpected issues that have the potential to derail production. Monitoring usage and capturing customer sentiment enables maintenance teams to analyse information, using machine learning algorithms. This enables the fine-tuning of processes and modifications to be made that improve product quality; ultimately increasing customer satisfaction.

General Electric is one such manufacturer leading the way with its Predix solution, an industrial-focussed IoT platform rolled out to its ‘Brilliant Factories’. The deep learning capabilities of General Electric’s data has already improved jet engine on-time delivery rate by 25%[iv] Predix will be standardised on Microsoft Azure in order to deeply integrate its portfolio with Azure’s native cloud capabilities. When it comes to helping industrial customers streamline digital transformation, the GE and Microsoft solution will combine GE Digital’s leading IIoT solutions that ingest, store, and analyse data to drive greater insight, with Microsoft’s huge cloud footprint – helping customers transform operations at enterprise level.

Going forward, manufacturers who embrace such technologies have a better chance of keeping customers happy, increasing sales, and acquiring greater knowledge of their entire business. When harnessed with the right solutions, IoT-driven data and AI deliver new levels of insight directly from customers. The result? Faster innovation and customer-driven design.

 

Sources:

[i] https://www.idc.com/getdoc.jsp?containerId=prUS43662418

[ii] https://www.i-scoop.eu/internet-things-spending-2018/

[iii] https://www.i-scoop.eu/industry-4-0/data-driven-customer-innovation-manufacturing/

[iv] https://www.techemergence.com/machine-learning-in-manufacturing/