In an effort to make products better, faster and stronger, the manufacturing process has grown significantly more complex in recent years. Technology and automation play much larger roles. The supply chain is longer and more diverse. Measuring processes with an eye on improving performance, finding efficiencies and increasing the bottom line has become all consuming.
Consider the fact that one Boeing 737 engine generates 10 terabytes (TB) of data every 30 minutes in flight. With two engines on a 737, an eight-hour transatlantic flight produces 320 TB of data. By comparison, today’s autonomous cars generate 2.5 TB every hour or 4 TB in a typical 1.5-hour round trip commute.
What are manufacturers doing with all this data? In short, incredible things that revolutionize manufacturing.
A Siemens manufactured locomotive contains no less than 900 sensors and uses the data those sensors generate to understand why equipment on the locomotive fails. With the knowledge gained from that data, Siemens can take steps to prevent the failures from occurring in the future. This doesn’t just help Siemens make better locomotives in the future. It’s helping their customers correct problems before they’ve occurred. By sharing this data with Amtrak, one of their customers, the transit company was able to reduce the number of delays by 33% last year from 2015.
In addition to Industrial IoT, robotics, artificial intelligence (AI) and predictive analytics are all proliferating in the manufacturing process and creating lots of data. In order to learn from and monetize this data, it must be parsed, analyzed and measured. Inevitably, this means sharing it and collaborating on it. Who would benefit from Siemen’s locomotive data? At Siemens, that could include product managers, assembly line workers and executives. At Amtrak, that could include engineers and technicians. Third parties could include authorized mechanics, design and efficiency consultants, other manufacturers who build parts for the locomotives, regulators with the DOT and/or EPA and likely others.
How do you safely and securely share and distribute all of this data?
While manufacturers can, and have, deployed many different security solutions and capabilities, such as antivirus, data-loss protection, identity management, multi-factor authentication and encryption, to prevent a data breach, sharing information with authorized external users becomes so cumbersome that users turn to consumer-oriented “shadow IT” solutions like Dropbox and thumb drives that are more functional but less secure and not approved by IT.
Increasingly, manufacturers are deploying content-collaboration solutions to ensure their sensitive manufacturing data and other proprietary content is shared securely and efficiently with internal employees as well as external partners. The better solutions can accommodate a customer’s network architecture, whether it includes on-prem systems or private/hybrid/public cloud configurations and provide the customer with total flexibility and scalability to meet evolving needs.
A content-collaboration solution should provide a comprehensive set of security protections. Content encryption in transit and at rest, role-based access, file/folder locking and expiration, integration with existing antivirus and data loss prevention solutions, and watermarking are a few examples of security features that can mitigate the risk of data loss.
Because user adoption is critical when the alternative is employees using shadow IT solutions, a content collaboration solution should also be intuitive for users. Ideally, it should look and feel like e-mail. A killer capability is bidirectional integration with existing content systems like SharePoint, OpenText and Box so that manufacturers don’t have to migrate content and disrupt existing workflows.
The terabytes of data at manufacturers’ disposal can be a blessing or a curse. To help ensure it is the former, consider employing content-collaboration solutions to nip use of shadow IT solutions in the bud.