Three Ways the IIoT Drives Speed and Collaboration in Continuous Improvement

Almost every industrial company has its own “flavor” and definition of Operational Excellence, and some even have backing from the most senior leadership.But for Operational Excellence to be successful, the market has firmly shown us that companies must align people, process, and technology resources. These pillars should also reflect the C-suite's stated Strategic Objectives for the business, and functional leaders must collaborate seamlessly to achieve the company’s vision of Operational Excellence.People, process, and technology alignment isn’t a new concept, and Continuous Improvement (CI) professionals are, without a doubt, well-versed in collaborative tactics.

Still, industry data collected by LNS Research shows that collaboration is the number one roadblock to companies missing the mark on Strategic Objectives. Inefficient processes, data silos, and disparate systems also block efficient collaboration.

 

A digital continuous improvement ecosystem that provides insights to the right people at the right time can boost collaboration and fuel Operational Excellence. It requires IT and operational technology (OT) data, supported by an Industrial Internet of Things (IIoT) platform with advanced analytics. There are many CI flavors, tactics, and approaches available to companies, and many organizations use several in tandem, choosing those that best fit their unique combination of industry, products, manufacturing mode, culture, and resources.  Let’s examine just three to get a sense of the kinds of benefits applying digital technologies to CI can yield.

Accelerate Continuous Flow with Digital Twin and Advanced Analytics

The traditional approach to continuous flow calls for adding value at each stage of production, and minimizing waste and cycle time as work-in-progress (WIP) parts move along the production line.In other words, when an operator discovers a backup of incoming parts, s/he identifies bottlenecks, and suggests procedures to improve the flow.

Advanced digital technologies – the IIoT – has significant potential to provide operators with vastly better information at precisely the right time, AND brings real-world real-time data with what has traditionally been disconnected and static production line simulations. The IIoT allows operators to anticipate backlogs ahead of time and engineer optimal procedures to improve flow. Digital continuous flow is about rhythm, coordination, and collaboration among the people in the shop floor but armed with the right information.

 

Five Whys Packs a Bigger Punch with Big Data Analytics

“Five whys” is arguably one of the most straightforward lean principles. Lean practitioners ask “why” about the problem at hand to reveal the underlying reason and repeat the question five times to arrive at the root cause. Sometimes the root cause isn’t simply a single item; in fact, it’s frequently a combination of several small issues, even spanning different departments. The time needed to discover the root cause naturally increases with complexity.

In a digital CI environment, however, five whys becomes more powerful with access to IT and OT data through a robust architecture and advanced analytics. Machine learning algorithms have the potential to analyze thousands of data points and prescribe insights much faster than humans, especially in the case of more complex problems.

One of the most extensive rail systems in Europe looked to advanced digital technologies to improve maintenance and repair. It analyzed an assortment of structured and unstructured data from social media, asset performance and geospatial data sources and discovered uneven wear because the trains always ran the same routes in the same orientation. The agency simply turned its trains around and ended up saving more than 8% on its €1B maintenance budget.

Thus the IIoT brings to the table new ways to analyze data from wildly disparate sources and correlate factors Lean practitioners may not have considered to reveal actionable insights.

A Faster, Better Gemba Walk

Gemba is the process of plant managers walking the shop floor to collaborate with operators and solve problems together at ground zero. One of the significant challenges with Gemba is that people might not have the full context to understand what is happening right in front of them, or they may even have conflicting values for the same metrics, depending on the data source.

When companies use advanced digital technologies like augmented reality / virtual reality (AR/VR) with Gemba walk, they see metrics as an overlay on assets, and run analytics on mobile devices.This approach allows the manager and operators to address time-sensitive issues with more reliable, robust information.Adding a Digital Twin lets them simulate processes and view them from different perspectives, depending on proposed changes – all without line disruption.Ultimately, Gemba becomes a power walk to resolve issues quickly and with better results.

Taking Steps to Step Up CI with Digital

We don’t expect Lean and CI practitioners to disappear any time soon.On the contrary, this is yet one more group of professionals that will become even more effective as companies continue on their Digital Transformation journeys.The IIoT will help them collaborate more effectively, will serve them with a holistic view of IT and operations data, and give them greater strength to solve problems with well-informed insights.Any company with a Digital Transformation underway should examine how to extend the benefits to its CI team, and companies considering Digital Transformation can certainly use their CI programs as a high-value entry point.

Learn how industrial companies are using advanced technologies to drive speed and collaboration in their continuous improvement programs by downloading the LNS Research e-book, “Improving Continuous Improvement: Reinvent Lean Today with Digital Technology.”To learn how PTC software can support your CI program visit here.

About the Author:

Vivek Murugesan, Research Associate LNS Research

Vivek Murugesan is a Research Associate with LNS Research; where he conducts market data analysis and creates data models that span the breadth of LNS coverage areas including Digital Transformation and the Industrial Internet of Things (IIoT), along with Manufacturing Operations Management, Asset Performance Management, Quality Management, and Environment Health and Safety. Vivek holds a Masters of Science degree in industrial engineering from Northeastern University, and earned a Bachelor of Engineering (BE) in mechanical engineering from Anna University in Chennai, India. Prior to LNS, Vivek worked with ARRIS where he focused on supply chain analysis, and co-founded Namma Café, a social and collaborative learning environment for young professionals to develop their skills in the areas of creating and building data models, interactive dashboards, and business intelligence reports.

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