Lean Manufacturing Concepts Apply to Digital, Too
Lean methodologies are fundamentally entrenched in manufacturing — not only because their roots date back to Toyota and vehicle manufacturing, but because lean has enabled manufacturing to become a business beyond margins. Like anything else occurring within the confines of a factory, the digital migration of manufacturing concepts also falls under the realm of lean. Just like you track material processes, waste, and rules, digital manufacturing is subject to this same scrutiny.
As we move into Industry 4.0, data organization has become something of a Wild West. Manufacturers scramble to build out their Internet of Things (IoT) and process copious amounts of data … but are they doing it in an organized, efficient way?
With data comes disorganization
Massive data streams are inherently disorganized — it’s why we’ve developed apps and ecosystems for dealing with them. Software takes all the Input/Output readings we get from sensors and parses it into easy-to-understand metrics. But there’s much more data beyond a single, simple IoT sensor. Factories are home to numerous data-sourcing digital streams, including:
- IoT sensors and beacons.
- Aggregated data from employee inputs.
- Wireless data transmitted between workstations.
- Manufacturing cloud data.
The larger an operation, the more data that comes with it. Without exaggerating, a factory could have thousands of data streams flowing at any given time. The possibilities for disorganization aren’t just probable, they’re inherent.
Apply the same lean principles
Data may not be tangible, but it’s subject to the same principles as lean manufacturing in the physical sense. Data is still process-based, which makes lean methodologies and philosophies viable. You can still trim waste from data streams or orchestrate better collection methods. Using automation, it’s possible to speed up data collection and reporting. Kaizen. Jidoka. Poka-Yoke. They’re all applicable.
Manufacturers need to be extremely cognizant about how they’re collecting, managing, organizing, and improving upon their many data streams. Chaotic, disorganized data is much worse than unhelpful — it’s an active hindrance to operations. Data confusion can cause everything from poor decision-making to overstress of critical production elements, causing setbacks manufacturers can’t afford.
In the same way lean dictates continuous process improvement for manufacturing real goods, it’s the system bringing order to the digital realm. Manufacturers just need to embrace what they already know and apply it to the uncharted territory of Industry 4.0.
Getting ahead in Industry 4.0
As factory IoT systems grow and the prevalence of data rises, organization becomes imperative. It’s much easier to build a lean framework from early, small-scale experiments than it is to untangle a great weave of data systems. Manufacturers need to subject their growing data collection practices to lean from the get-go.
Forethought to lean data practices also has peripheral positives. Organized data without gaps in the handling process equates to better cybersecurity. Streamlined data organization promotes business agility. Rapid data processing lends itself to just-in-time (JIT) production and Heijunka concepts. Lean concepts perpetuate excellence — not just in physical manufacturing, but in the data-driven environment of Industry 4.0.