The digital factory: Where are we?
With data being the epicenter of industry 4.0 in the manufacturing industry, utilizing that data in the most effective way is essential. Industry leaders must work together to maintain transparency of data as well as ensure the equipment can handle new advancements. In this article from Manufacturing Engineering, find out where the industry stands today and where it still has to grow.
As OEMs and suppliers alike wrestle to convert Big Data to Smart Data, Industry 4.0 and digitalization, plus cloud-based technologies for production monitoring and management, how do manufacturers best work together with end-users to achieve today’s production targets and plan future facilities?
The rapid evolution of Industry 4.0 as a manufacturing mandate is progressing from a massive information gathering technology to the highly practical realm of predictive maintenance and overall equipment effectiveness (OEE). In something of a “perfect storm” scenario, the trend toward the “intelligent workcell” of tomorrow, with fast highly flexible changeovers, collaborative robots (cobots) and factory-wide communication platforms, is likewise running at rocket speed.
The seminal challenge for factory planners and production managers today is to take the Big Data convert it to Smart Data using analytical hierarchy of those information pieces and blend them into a transparent look at the overall operation. The focus is on incoming materials handling to tool management to workflow scheduling to part production in a fast, flexible way. Plus, this process must be accessible remotely, sometimes on different continents, all the while feeding a production schedule for customers and consumers alike. I often think this is why we in the automotive industry have such passion and commitment to keeping processes economically viable and globally competitive.
Take a quick example: If you track cycle time of 30 seconds for the production of 9- or 10-speed transmission parts such as planetary gears, sun gears and carriers, it becomes critical to have complete correlation of the production data in real time. Today, that involves data gathering from vertical turning machines, cobots, transfer mechanisms, ECM stations, laser welding equipment, even parts washers altogether for maximum efficiency. That data must transfer from the plant floor to the cloud, from the OEM to the Tier One or Two suppliers and, ultimately, to the machinery, equipment and controls vendors feeding those players. Controls suppliers on the equipment must be supplying devices that seamlessly communicate to the other machines, as well as to the cloud, to maximize the efficiency of tooling alerts, material feed, parts handling and, of course, the complete machine status for PM and OEE protocols.
When a production change or machine malfunction occurs, the daisy chain of controllers within the line must react in a coordinated way and in microseconds.
Another factor of importance in such a transparent and accessible production picture is cybersecurity. From the accidental or unauthorized change in a feed or speed to a compromised system-wide attack, the security on the communication system is critical for maintaining line viability and plant productivity. The emergence of the intelligent workcell mandates a comparable team of competent data security and IT personnel.
Finally, all this smart data will move through the personnel via app developments, customized to the needs of the individual production department or even the smaller shop, as this digital trend has value for all links in the supply chain. The key is prioritization of information. Simultaneously, we machine tool builders are equipping our units with more sophisticated sensors, inline measurement, encoders and communication devices to meet this challenge with our customers. A very exciting time in the industry.
This article was written by Peter Loetzner from Manufacturing Engineering and was legally licensed through the NewsCred publisher network. Please direct all licensing questions to legal@newscred.com.
