Digital transformation in asset-driven industries such as manufacturing and utilities depends on operational technology (OT)—data from machines. However, extracting usable data with traditional manual or fixed sensing options can be a prohibitively expensive and time-consuming process. New agile sensing platforms like Spot help fill the gaps. This mobile sensing approach reliably automates data collection, with less burden on people or budgets. With this consistent, frequent data capture, predictive maintenance—one of the pillars of Industry 4.0—is a much more achievable goal.

Getting to Industry 4.0

The essence of digital transformation lies in using data to drive efficiencies at scale. Industry 4.0, digital transformation applied to manufacturing, promises to decrease downtime, an all-important key performance indicator (KPI). The premise is that machine learning systems can analyze data about equipment to predict when that equipment is likely to fail—and alert workers of the problem before a failure actually happens. This advance notice helps prevent expensive unplanned downtime and allows machines to run more reliably and predictably.

One approach to accessing data from machines is to fit them with IoT (Internet of Things)-based sensors. However, enterprise-wide sensorization and the associated infrastructure can be cost-prohibitive and require significant capital expenditures. As a result, many companies today are using a more selective process for data collection, fitting only a few critical machines with sensors. A manual inspection process is often put in place for the rest. However, these time-consuming and repetitive inspection rounds are often not conducted as frequently or as accurately as needed. As a result, data gathering becomes inconsistent and enterprises fall short of realizing the full potential of their Industry 4.0 initiatives.

Asset-heavy industries need a flexible approach that will more frequently and reliably deliver the data volume and consistency that Industry 4.0 needs.

How Agile Mobile Robots Help Fill the Data Gap

An agile mobile robot like Spot can help fill in the gaps left by a fixed sensor network. The robot acts as a dynamic sensor-loaded platform, traveling to the asset—on a set schedule or an as needed basis. With Spot, asset-intensive industries can access the data they need for predictive maintenance and Industry 4.0 initiatives without having to outfit every single machine with IoT sensors.

Gather data from older machines

Many brownfield facilities will stay active and operational for decades to come, filled with assets that aren’t connected to an IoT data ecosystem without extensive retrofitting. Using Spot as a sensing platform makes it easier to extract data from all assets, new and old.

Establish a routine of regular and reliable data collection

With labor shortages continuing to pose challenges, companies prioritize deploying talent selectively for their most pressing issues, while dull and repetitive data-gathering rounds are often delayed or put on hold. Spot solves the challenges of sporadic and inconsistent data collection, automating inspection tasks and performing the programmed routes in a reliable and uniform way.

Empower a customizable approach

A business’ data needs typically evolve over time. Using Spot as to dynamically collect data means you don’t have to reconfigure your sensor infrastructure to accommodate your new requirements. Simply create or edit Spot’s missions to add or replace equipment and points of interest from automated inspection rounds. You can also add new payloads to capture different types of information as needed. Spot can carry a variety of sensor payloads—including cameras (such as the Spot CAM+ and Spot CAM+IR) and a wide range of sensors for mapping radiation, detecting acoustic anomalies caused by air leaks, monitoring equipment vibrations, and more. 

Collect data remotely

Workers don’t need to be on the factory floor—or even on-site—to understand what’s happening in the field. They can log into Orbit, a fleet management software that can be used to drive the robot wherever it’s needed for data gathering. Such remote monitoring is especially advantageous for deployments in hazardous environments or in hard-to-reach areas where it’s difficult to quickly deploy personnel to troubleshoot problems.

Starting with a Dynamic Sensing Approach

To deploy the agile mobile robot for data collection tasks, businesses will first need to plan which KPIs they want to measure, which machines to monitor, and which sensors are required to capture that data. 

Using payloads from Boston Dynamics and our partner ecosystem, Spot can capture temperature profiles, check vibration, measure radiation, and more. The first step to deploying Spot is deciding which payloads are right for your specific use case. Then map out the route for Spot to access the assets you’re monitoring—this may replicate your current manual routes or be a new route designed to take advantage of Spot’s efficiencies. 

Finally, record a mission by driving Spot through the environment. Using the Spot Tablet, you can designate which data capture actions Spot should take at each point of interest. The robot stores this routine to collect the required data reliably and consistently. 

Putting Dynamic Data Collection into Practice 

Once you have your inspection route recorded, it’s easy to start autonomous operations. 

Spot remains on its docking station between inspection missions, which enables autonomous charging and offers a gigabit ethernet port for uploading the data Spot collects. On a preset schedule or an on-demand basis, Spot starts its autonomous mission, traveling to assets along the recorded path. The robot stops at the same location every time and collects the same kinds of data in the same manner for consistency and repeatability. 

Operators can follow along in real-time from Orbit and review the data to see how current asset conditions compare to previous captures. Spot can also be integrated with asset performance management (APM) software or machine learning systems to detect anomalies automatically and trigger follow up actions.

As needs change, maintenance workers and floor supervisors can reconfigure Spot, edit or add autonomous missions, or manually operate Spot for remote troubleshooting. No matter how vast your data collection needs may be, dynamic robotic industrial inspections can help fill in the data collection gaps left by fixed sensor deployments. They enable workers to focus on higher-value tasks without compromising their data needs for predictive maintenance and Industry 4.0 initiatives.

To learn more about getting started with robotic industrial inspections and see Spot in action, watch our on-demand webinar.