Manufacturing - a ballet choreographed by the flow of making things

Profile picture for user Jason Prater By Jason Prater April 21, 2016
Summary:
Jason Prater, Plex VP of development, shares his perspective on how new technologies such as mobile, Internet of Things (IoT) and Big Data/analytics will shape the manufacturing industry in the coming years.

Jason Prater, VP of development, Plex Systems 250px
Jason Prater, Plex Systems

Today’s technology trends are helping manufacturers find new ways to improve shop floor efficiency, provide better product quality, and discover the insight required for more informed business decisions.

I like to think of the manufacturing shop floor as a mobile, fluid environment characterized by movement — moving materials to the shop floor, moving materials along the assembly line to create a product, and moving finished goods out the door. To keep things flowing smoothly, people’s interaction needs to follow that movement — in what can be described as a ballet, choreographed by the flow of making things.

Here are five examples of how today’s technologies support the complex choreography of manufacturing at our customers.

1. Cloud flows everywhere

Our customers want to make it where they sell it, avoiding currency fluctuations, which is one reason why Plex customers operate in 22 different countries around the globe. A cloud-based information system provides a single, transparent view of the business across the globe, so their users can make data-driven decisions at the inflection point.

Beyond that, on the manufacturing shop floor, a true cloud solution is fluid and flexible and provides a completely different experience. The user can leverage innovation without going through disruptive version upgrades. We can modify user experience to match today’s modern toolsets, providing the right tool to help our customers make the product better and cost less.

2. Mobile moves on the shop floor

The fluidity of the shop floor lends itself to mobile technologies. Many companies use mobile devices to get better visibility and control over manufacturing operations. Operators can collect data in real-time as they move around the shop floor, rather than being forced to use PCs placed at fixed locations. The availability of more robust, more “industrial strength” mobile devices is helping drive this trend.

3. Wearables help information flow

Our customers are very interested in wearables. Fisher & Company (a tier-one auto supplier) uses Google Glass so supervisors can see status reports “hands-free” as they pass each work center. Fisher’s materials handlers use Google Glass for barcode scanning, replacing a manual process and storing data in the Plex cloud.

Taking an agnostic approach to wearables, we also see a role for other devices including the Microsoft HoloLens. Connecting any of these devices through a RESTful API framework provides the flexibility and choice to collect or present the most appropriate information for each device.

4. Analytics unlock new value

Intelligent analytics provide a unique value to customers. When data is automatically collected from many sources — machine-to-machine — it replaces time-consuming and error-prone manual processes. Prepackaged and custom reports identify trends across the business — manufacturing, sales and finance — to provide prescriptive intelligence and insight that can be used to make meaningful business decisions.

Fisher is also using analytics in its seat assemblies. The company automatically streams, collects, and records sound data from the seats. In recall situations, the recorded data is analyzed looking for variations in seat sounds between recalls and normal seats. This helps to isolate potential problems and improve product quality.

5. Data creates new revenue streams

More and more businesses are selling data as a service, turning collected data into a source of revenue by offering customers access to their data. This trend is being driven by the vast amount of data collected and stored on inexpensive commodity storage in public cloud platforms such as Amazon AWS and Microsoft Azure.

Here’s an interesting historical example. Back in 2003 during the steel crisis, a materials manager figured out how to make money selling scrap. He studied data and trends to determine the right price and the right market.  Today, businesses have so many more sources of both historical and real-time data and better tools to access and analyze data. Businesses are using that information today to create new business models based around selling data-as-a-service.