Unlocking smart manufacturing ROI
A system integrator explains six industrial data requirements for factories of the future using an apple-pie baking example.
Smart manufacturing provides a compelling return on investment (ROI) roadmap with appropriate attention to industrial data creation, flow and use.
Example: Chloe dreams of owning her own business and has the perfect product for it – her Aunt Marge’s apple pie. Baked to a traditional recipe, the pies are a family favorite, and Chloe has a taste for expanding that appeal on a large scale. She’s apprehensive because her friend Tim recently filed for Chapter 11 bankruptcy protection due to spiraling manufacturing costs at his chocolate factory. While Chloe has completed her groundwork and identified viable markets for her pies, she is wary. How can she proceed?
The answer may already be among worldwide discussions of smart manufacturing methods and the resulting return on investment (ROI) for new or existing manufacturers.
Smart manufacturing, automation efficiency opportunities
Smart manufacturing was pioneered by the process industries about a decade ago. It evolved as a technology-driven approach that leveraged internet-connected sensors in factories to monitor the production process in real time. The target was to identify new opportunities for automating operations and using data analytics to improve manufacturing performance.
This ability to extract insights from the rich real-time data stream generated by production machinery offers the prospect of minimizing potential plant downtimes, maximizing manufacturing efficiencies, and driving improvements in product quality to realize significant warranty cost savings. In light of these compelling benefits promised, smart manufacturing is finding widespread business adoption.
However, in the implementation rush, enterprises may fail to convert ambitious intentions into meaningful ROI. As ironic as it sounds, one of the most common pitfalls is businesses fail to first identify what the ROI would represent. Data capture alone isn’t enough to materialize payback (ROI).
Another common issue is the general misperception smart manufacturing only aggregates data on a desktop computer.
Six areas of data development for manufacturing automation ROI
Manufacturers need to realize raw data is of little value by itself. To reap meaningful returns, companies must adopt a more nuanced, multi-layered approach by mastering capabilities across six areas:
- Data collection: The foundation of smart manufacturing is engineered from the ground up around the premise of collecting real-time data from the plant machinery. An adequate implementation of smart sensors is therefore required to capture this data from the diverse ecosystem of connected equipment.
- Data preparation: The raw data captured by the sensors would need to be converted into actionable and usable formats. Consistency of the data set is vital for ensuring that the relevant machine learning algorithms can operate efficiently.
- Data processing: Streamlining the data processing methodology by creating secondary measures is another vital step towards unlocking returns from smart manufacturing practices. Bringing together multiple data streams can resolve previously unidentified inefficiencies and challenges related to performance and output while ensuring strong overall equipment effectiveness (OEE) results.
- Data monitoring: Data monitoring is often overlooked, but it is a major element of an effective smart manufacturing setup. With real-time performance monitoring, potential issues can be resolved through predictive maintenance before they snowball into bigger challenges.
- Leveraging analytics: By correlating outcomes with the anomalies, machine learning can help ensure adequate attention on the key performance indicators (KPIs) that have a significant impact on overall efficiency and production quality.
- Insights mapping: Beyond data tips 1 through 5, modern businesses seeking to optimize returns from smart manufacturing operations need to map results and insights obtained against the pre-defined KPIs. This would help ensure that the digital manufacturing journey is on track and make necessary course corrections should the need emerge.
Deep domain expertise needs to drive implementation of the whole process. Smart manufacturing initiatives that meet ROI targets are almost always guided by and from the factory floor, and not remote information technology (IT) specialists, even though manufacturing IT technologies likely will be part of the project. Combining engineering expertise with digital transformation capabilities is key to ensuring the algorithms receive the correct insights from the generated raw data. Appropriate real-time data analytics is only feasible after the physics of the process is understood.
The illustration shows six distinct areas in the smart manufacturing universe, where companies need to master their capabilities to reap the best returns. Courtesy: L&T Technology Services.
Weaving the digital thread for unlocking smart manufacturing ROI
Digital threads are a critical capability in model-based systems engineering. In a smart manufacturing setup, this is visualized as a communications network that facilitates a unified data flow across the connected ecosystem. Digital threads also provide an integrated overview of an asset’s lifetime data through various functional perspectives.
Smart manufacturers can look to leverage the coherence offered by the digital thread to unlock ROI from their activities. The process can be initiated by a renewed focus on ensuring enhanced OEE. Enhancing OEE involves leveraging data from factory floor smart sensors to identify existing and potential production bottlenecks. Automated analysis of historical data would further help identify key areas of improvement. Real-time diagnostics would minimize downtime.
Adoption of an effective asset condition monitoring (ACM) framework also could be beneficial in this direction. By implementing real-time analytics for ensuring the health and continued throughput of productive assets, an ACM can help reduce downtime, minimize reactive maintenance schedules and boost overall yield. All of these help boost the ROI of the smart factory of the future.
Improving batch productivity in a smart factory setup would further advance smart manufacturing ROI. Leveraging reproducible and scalable data engineering and batch configuration methodologies, the factory team can look to streamline the production operations while enhancing the level of visibility in decision making and reducing time lags. Effective identification and comparison against the ideal (or “Golden”) batch also would help enhance the production quality and output levels, while enabling the definition of operating standards that would maximize ROI.
This Golden Batch methodology of “performance-quality-cost,” which involves the effective mapping of performances against the quality achieved and the cost involved, would help optimize raw material consumption, increase quality consistency and drive down energy requirements.
How to implement smart manufacturing with ROI
The primary attraction for adopting smart manufacturing is it helps make firefighting issues a thing of the past. Plant engineers and production teams are now empowered to forecast, and forestall problems in a systematic manner, instead of reacting.
In the post-COVID era, businesses need to look at ways to minimize human interaction on the shopfloor, while maintaining and even exceeding previous production standards. Smart manufacturing, by leveraging its connected sensor ecosystem, has emerged as a major enabler in this direction. Not only can manufacturers continue to monitor their equipment effectiveness in real time, they can further ensure all human interventions are kept at a minimum. When they do happen, it’s in a planned manner that allows for social spacing norms to be met. By embracing smart manufacturing, factory operators are better prepared to meet the exacting standards of the new normal world order.
That does not mean smart manufacturing is a bolt-on solution for the many modern production method challenges. Sustained payback would still require a further streamlining of the collection of raw data from all vital points through smart sensors, a faster transformation of the data collected into implementable insights and leveraging them in better ways to unlock efficiencies throughout the production process.
With these considerations, Chloe’s promise to deliver Aunt Marge the first apple pie from her new factory will serve up a tasty manufacturing ROI.
Prabhakar Shetty is global head (digital manufacturing services), L&T Technology Services, a CFE Media content partner. Edited by Mark T. Hoske, content manager, Control Engineering, CFE Media and Technology, [email protected].