A new hope for the future of manufacturing

DXC Technology’s Mozhi Habibi explains how insights from internet of things devices can reduce downtime, streamline supply chains, improve product quality, optimise asset performance on the plant floor and more

By Guest on 09 May 2019
A new hope for the future of manufacturing

This article was originally published in the Spring 2019 issue of The Record. Subscribe for FREE here to get the next issue delivered directly to your inbox. 

Manufacturing companies are under pressure to hit production targets amid challenges that include a shortage of skilled workers, inefficient supply chains and a lack of insight into the performance and health of their assets. To ensure that production quotas and quality standards are met, operational technology (OT) teams tend to err on the side of caution. They may stock more inventory than needed and conduct maintenance checks on equipment more often than necessary, which costs the company money in the long run. But there is new hope for the manufacturing industry.

Data analytics based on internet of things (IoT) can help manufacturers reduce downtime, improve product quality, increase efficiency and optimise asset performance on the plant floor. IoT for manufacturing can also streamline processes such as supply chain, inventory management, scheduling, quality control and compliance. It can even help companies turn data collected from consumer devices like cars and smartphones into actionable information in the product development process.

Imagine being a plant manager and having the ability to use a handheld tablet to monitor the real-time performance of the assets on the production line. You would be able to ensure everything is operating at peak performance, using preventive and predictive maintenance. Asset performance management tools can pull in contextual information, such as the age of a particular piece of equipment, its maintenance history, product data from the manufacturer and plant specific environmental variables, like temperature and humidity, to provide a detailed health assessment of the asset.  

Enabling this capability means the plant manager will know if a part in a large robotic machinery has reached the end of its useful life and needs to be replaced. Or maybe it is expected to fail within four weeks at the current rate of usage, but it’s slated for scheduled maintenance in two weeks, so the plant supervisor can wait until the maintenance window. Or maybe it’s expected to fail within one week, but it can last until the two-week maintenance window if it’s operated with a lower workload. This type of actionable information enables OT executives to conduct maintenance activities with surgical precision. Over time, machine learning and artificial intelligence and augmented reality can be brought to bear, so that the analytics systems gain an understanding of your business processes and begin to act as trusted advisors.

The latest manufacturing systems not only collect and analyse IoT data generated by sensors embedded in machines, they can also provide insight based on visual inspections, acoustic and vibration analytics. Cameras mounted along the production line can pinpoint product defects, classify them and help companies identify emerging quality trends. For example, cameras can spot a defect in the paint job of a new car, raise a red flag and enable the manufacturer to instantly correct the issue to prevent the car from having to be completely repainted later in the production process. This cuts costs and maximises raw materials. Similarly, IoT sensors can listen for all types of sounds, including those not audible to humans, like ultrasonic waves or vibrations. Cognitive IoT analytics systems can apply machine learning to correlate anomalies in acoustic signals with a potential problem in a motor vehicle engine or a turbocharger.

Insights are great, but action is needed if they are to be valuable. Companies may integrate an analytics model in line with a factory automation or supply chain management system. Alternatively, they could adjust planning parameters over time, such as maintenance schedules, economic order quantities and minimum stock levels. Or they could present the key insights in a visual format to help workers make better decisions – for example a mobile app that provides key information or smart glasses that provide instructions.

IoT for manufacturing solutions have the potential to transform the industry, enabling companies to collect and analyse data from networked sensors, intelligent devices, legacy systems, customers and social media. To leverage IoT technologies, an organisation must take a holistic view of the process by evaluating and confirming the technologies they want to implement and identifying the business value, the effects on business processes and the partners to help it reach its goals. Of course, they must also get buy-in from C-level executives and other business units. 

Mozhi Habibi is the leader for IoT and Enterprise Asset Management at DXC Technology, Emerging Solutions

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