Look beyond the factory walls – why the perfect plant is not sufficient to deliver perfect quality

It’s all about the outcomes

The focus of most IOT projects in the mill industries is on the manufacturing and plant maintenance processes in the mill. This seems like a natural fit, but may actually jump too short.
The industrial internet of things, industry 4.0, is not about technology – it is all about better outcomes.

I would like to focus in this blog on less waste – aka less cost, and more reliable product quality – aka higher customer satisfaction.

More quality. less scrap

The industrial internet of things provides the tools and technology for taking product and process quality to the next level:

• It can enable, on one hand, superior quality (or specifications) not achievable before.
• Alternatively, it can reach a “normal” product quality through more stable processes either with less or lower grade input material, lower energy usage, or with a lower scrap factor.

The perfect plant is not sufficient: the limitations of predictive quality and advanced process

Several mill products companies I have talked to, apply IIOT methodology in quality control. They look at sensor values across multiple manufacturing steps, consider raw material characteristics, and include as well some environmental factors like humidity or temperature.

Companies explore previously unknown correlations between root causes that led in the past to quality problems, and apply machine learning to train models to predict and prevent quality deviations in the future.

My POV: Do not just look at predictive maintenance. Predictive quality can be another powerful capability to further increase OEE through better, more reliable quality and less scrap.

Will this automatically increase customer satisfaction? Not necessarily.
Why is this?

Many customer complaints are related to scratches or dents in the metal surface – and those are often not caused in production, but in logistics.

Real end-to-end root-cause analysis

Steel coils and paper rolls are easily damaged. They require delicate handling, expert packaging and storage.

Real end-to-end root-cause analysis needs to take internal and external logistics into the picture:

• How often a coil was lifted
• With which acceleration and force was it moved and put-down
• Under which temperature and humidity conditions was it stored and transported

Cold chain logistics versus coil logistics

An unbroken cold chain is an uninterrupted series of refrigerated production, storage and distribution activities. Getting vaccines undamaged to their destination can be quite a challenge. Smart packaging and sensors help to proof that the cold chain was indeed unbroken.

Similarly, digital coil tracking may help to capture not only the geo position of a coil, but its entire handling history – through temperature, humidity, acceleration sensors in the package itself.

Steel and paper mill optimize warehousing and loading processes to minimize the necessary movements. What happens at the logistics service provider, on the truck or ship, and at the ports, is today not visible. But it probably has a much higher impact on the product quality at the customer.

How are the coils stored? Vertically, horizontally? Smaller on bigger?
Is the packaging leaking and salt water can enter and cause corrosion?

This is not a simple task. Check out this link with some advice on handling steel coils on a ship

Within the mill the sensor is usually online. On the truck, in the yard, on the road or ship, the sensors will be in many cases offline, and will need to capture and store data throughout the journey.

This creates a few complexities. In the event of a customer complaint, the logistical coil history and the in-plant quality history need to be linked, to execute an end-to-end root cause analysis, and influence future business decisions.

This may impact a preference for certain transportation routes over others, add to the rating and selection of  logistic service providers (beyond cost and service level), and many more.

Today steel cargo is carefully examined by surveyors before loading, at the discharge port to record any damage on rusting. At times, the surveyor can only check the packaging but not look inside.

Digital coil tracking may not only provide a clearer picture who damaged a specific coil on the journey, but it may actually help to identify root causes to reduce such incidents. Fewer damaged coils drive down cost, raise delivery reliability and customer satisfaction. They also reduce waste.

Violent whipping

Coil steel is both a beautiful and a dangerous material. A steel coil can weigh up to 15 tons. Coiled steel rolls easily, and there is also a hazard of violent whipping if the coil uncoils without restraint.
There is a great potential for serious injury and even fatal accident if coil steel is not handled and stored properly.

Digital coil tracking may be a means to create visibility into unsafe practices, thus not only saving cost, but also lifes.

Want to learn more about how to link sensor information, machine learning and big data analytics to drive more intelligent logistics?

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