IoT data: A new hope for the manufacturing industry’s future

IoT-in-manufacturing

Manufacturing executives are under the gun to hit production targets amid challenges that include a shortage of skilled workers, inefficient supply chains and a lack of insight into how enterprise assets are performing.

In order to make absolutely sure that production quotas and quality standards are met, operational technology (OT) teams tend to err on the side of caution, to overcompensate. They may stock more inventory than needed and conduct maintenance checks on equipment more often than necessary, which ends up costing the company money in the long run.

But there is new hope for the manufacturing industry. IoT-based data analytics can help manufacturers reduce downtime, improve product quality, increase efficiency and optimize asset performance on the plant floor. IoT for manufacturing is a wide-ranging solution that can also streamline and improve 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 that can be used to make products better.

Real-time analytics

Imagine being a plant manager and having the ability to use a laptop to monitor the real-time performance of every asset on the production line. Not only can you make sure everything is operating at peak performance, you can begin to conduct preventive and predictive maintenance. Asset performance management tools are able to 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 that asset.

Maybe a piece of robotic machinery has reached the end of its useful life and needs to replaced. Maybe it is expected to fail within 4-6 weeks at the current rate of usage. And maybe it’s slated for regularly 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 run at a slower rate of speed.

This type of actionable information gives OT execs options and enables them to conduct maintenance activities with surgical precision. And over time, machine learning and artificial intelligence can be brought to bear, so that the analytics systems gain an understanding of your business processes and begin to act as trusted advisors.

Sight and sound

The latest manufacturing systems not only collect and analyze IoT data generated by sensors embedded in machines, they can also provide insight based on visual inspections and even acoustic 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 correct the issue right then and there, rather than waiting for the problem to be spotted farther along in the production process and the car having to go back for a completely new paint job. This cuts costs and maximizes raw materials.

Similarly, on the acoustic front, 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 in order to correlate anomalies in acoustic signals with a potential problem in a motor vehicle engine or a turbocharger.

Integrating to value

Insight is great, but action is needed if value is to be generated. This may mean integrating an analytics model in line with a factory automation or supply chain management system, It could be a case of adjusting planning parameters over time, such as maintenance plans and schedules, economic order quantities and minimum stock levels, etc.  Or it could be a matter of presenting the key insights in a visible form so a worker can make better decisions, whether via a mobile application on a tablet, or integrating key information and instructions on a wearable device like smart glasses.

The transformative power of IoT data

IoT for manufacturing solutions have the potential to transform the industry, enabling companies to collect and analyze data from networked sensors, intelligent devices, legacy systems, customers and social media.

To leverage IoT technologies, an organization must take a holistic view of the process, evaluate and confirm the technologies to be implemented, identify the business value, the effects on business processes, the partners to help it reach its goals, and, of course, get buy-in from C-level executives and other business units.


Mozhi Habibi is IoT Sales Leader for DXC Emerging Solutions.

Comments

  1. Indeed, with the implementation of IoT in the manufacturing sector, many of the complex tasks are going to break down into simpler forms. This will bring a great revolution in the field of industrial segments.

    Like

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