Emerson Exchange 365

Like most children, I enjoyed lying on my back and staring at the clouds with my friends and guessing what shapes we could see in them.

Fast forward to my professional life, I get to interact with digital clouds, and I have to admit, that’s way more fun!

In my previous blog, I mentioned that cloud connectivity of machines was bringing new improvement opportunities to industrial companies. This article explores the cloud topic further.

Connecting an industrial machine, or process, to the cloud is easy to do when using new edge control systems. This is thanks to the innovation of a PLC control system and a computer being merged into a single cyber secure device. Edge technology allows data from isolated elements to be accessed and gathers data from other business/internet constructs and consolidates the information.

Here are seven use cases that illustrate how industrial companies can gain benefit from connecting machines and processes to the cloud:

1. ASSET BENCHMARKING WITH FLEET DATA
   One of the easiest ways to identify an improvement opportunity is to compare similar assets from different locations and to benchmark their performance. An under performing asset is easy to identify using basic KPI’s and raising its performance level can bring quick improvement. A good example was a mining customer who told me about how they were comparing fuel consumption of various types of haul trucks. They noticed one site had very high fuel consumption per ton. An investigation on site revealed that the loading platform was lower than other sites which meant that the loading equipment couldn’t fill the haul trucks to their maximum load capacity. By raising the platform they were able to fill the trucks and gain savings on fuel.
   
   
2. ASSET INSIGHT FROM DESIGN PHYSICS
   Designers of machines understand the material science and mechanical models of their creations. The physics from the design phase proved that the machine would work in the real world. Warranties are issued based on the calculated and predicted design performance. Collecting data from sensors on the machine gives a long-term picture of the performance of the machine against the original design theory. This helps to improve future designs and brings competitive advantages for the OEM. The physics is also able to determine failure modes of the machine. By monitoring sensor data you can identify when key variables approach failure mode thresholds and early warning can be provided of impending equipment failure.
   
   
3. IDENTIFYING ASSET ANOMALIES USING STATISTICAL DATA
   While the physics models of machine performance tend to remain the intellectual property of the machine designers, an alternative method to understand machine performance is using statistical models. Sensor data from the machine, the environment and the production process build a digital history of performance. Time windows of good performance, bad performance and breakdown conditions can be identified and associated with the appropriate data sets. This gives a data scientist an opportunity to identify and build statistical models of machine health. A unique “fingerprint” algorithm that typifies good performance can be built and trained. This means as soon as real-time sensor data starts to deviate from the “good performance pattern”, alerts can notify a remote domain expert to verify if there is a cause for concern. The domain expert could be located anywhere in the world as the data is in the cloud.
   
   
4. DIGITAL ENABLEMENT FOR MULTI-ORGANIZATION COLLABORATION
   Consider Vendor Managed Inventory as an example. Many large manufacturers have chosen to outsource the supply of their raw materials to vendors. A service agreement binds the supplier to ensure 100% availability of chemicals, fuel or materials on site. With the new edge controllers, the control system can now not only measure the amount of inventory in a tank or silo and request it to be replenished timeously, but it can also easily connect to various systems such as the off-site supply chain systems as well the MES or ERP on site. This provides an easy way to digitally collaborate between different organisations and ensure transparency of raw material supply and the quality thereof.
   
   
5. OPTIMISATION THROUGH OFFSITE ALGORITHMS
   It’s not only possible to send data to a cloud. There is also tremendous value in receiving data from the cloud. A cloud-based algorithm can collect data from multiple sites and use powerful centralized processing to run the master algorithm of the company. The result can send data to a controller that can improve production or reduce costs. We experience this in our personal lives when we use mapping software to plot the optimal route to our destination. The central system gathers data from many sources and process your request and sends the result to your phone. There are various industrial applications that could function similarly.
   
   For example, a wastewater treatment plant could interface to regional weather data to adjust chemical dosing during rainstorms.
   
   Another example could be to choose to run pumps or motors when the cost of energy is the lowest. The cloud algorithm can check live energy tariffs and send a message to the controller to run the pump when the energy price is lowest.
   
   Using this concept in manufacturing supply chains with centralized product demand algorithms could derive powerful benefits.
   
   
6. SELF DIAGNOSIS AND SERVICE REQUESTS
   The edge computer and control system can work together to self-diagnose the machine health or status. A message can be sent to a cloud solution to alert service technicians of the need for repair. Using GPS and geofencing, a mobile device can become a powerful tool in ensuring an appropriately skilled technician that’s closest to site can repair the problem as quickly as possible.
   
   
7. NEW BUSINESS MODELS
   When you combine some of the functionalities described in the various use cases above, ideas for new business models quickly emerge.
   ** OEMs can create new value from their customers by offering new types of service agreements.
   ** Raw Material Suppliers can differentiate themselves by accepting stricter contractual terms with their customers as a result of effective real-time business critical information.
   ** Automation System Integrators can expand their businesses by offering new and differentiated cloud-based services.
   ** Industrial Plant Monitoring Centers could become a new industry as more and more machines get connected.

This list goes on.

Ultimately, the end user and consumer win as these new technology innovations change the way industrial companies operate and drive productivity improvements.

More information on how edge technology can help plants optimize their operations can be found in this "Edge Technology" white paper.

If you are interested in improving your operations, but you are unsure where or how, the Emerson team can help you develop an industrial information strategy.

This post previously appeared on LinkedIn