How AIM Recycling Reached 90% Equipment Utilization With Automated Machine Data

Equipment utilization has a direct effect on throughput, labor planning, customer commitments, and the amount of revenue a recycling operation can generate from the assets it already owns. AIM Recycling needed a more dependable way to measure equipment activity across a complex industrial environment. Delayed or inaccurate user entered data made it difficult to understand utilization and throughput while there was still time to respond.

AIM worked with SensFlo to automate production data collection through an Industry 4.0 system. The public AIM Recycling Success Story reports 90% equipment utilization, an average of 12 daily run hours, and more than 1,500 unique data points captured through the system.

Key takeaways

• AIM reached 90% equipment utilization.

• Equipment averaged 12 run hours per day.

• Automated collection produced more than 1,500 unique data points for operational review.

The visibility problem behind recycling equipment utilization

Recycling facilities depend on complex equipment working together. When one asset slows, stops, or waits, the effect can move through the rest of the operation. Reliable utilization data helps managers separate productive time from idle time and determine whether a throughput issue comes from equipment availability, operating conditions, or the way work is being coordinated.

AIM needed precise equipment utilization and throughput information. Its existing dependence on user input created delays and accuracy concerns. That made it harder to adjust operations using current information. SensFlo’s guide to machine monitoring for recycling operations explains why automated machine data is especially valuable in facilities where varied loads, demanding conditions, and connected processes make manual reporting difficult to maintain consistently.

Moving from manual entries to automated collection

AIM implemented an Industry 4.0 standard system with SensFlo. The system automated data collection and entry, then made the information available through a management console. This created a current view of equipment activity that managers could use for operational adjustments.

The implementation included hardware and firmware connections, controller and analog data, fault codes, WiFi and cellular connectivity, cloud based access, machine learning, and real time job profitability capabilities. These components supported a broader data path from the equipment to the people responsible for production decisions.

For manufacturers evaluating a similar starting point, the complete guide to machine monitoring explains how machine signals become utilization, downtime, cycle time, and production information inside a monitoring platform.

What 1,500 data points add to decision making

A large data set only creates value when it is organized around useful operational questions. AIM’s more than 1,500 unique data points gave the team a detailed source of machine information that did not depend on someone recording each event after it happened.

That structure supports several practical decisions. Managers can review whether equipment is running as expected, compare utilization with throughput, identify periods that deserve investigation, and respond using information captured directly from the operation. Over time, historical data can also provide a more reliable baseline for capacity planning and performance reviews.

FloControl is designed to organize these machine signals into information that plant leaders, supervisors, and operators can use. For AIM, the management console connected automated collection with real time operational review.

The business value of higher equipment utilization

The AIM results show how visibility can support both production performance and financial discipline. A 90% utilization result indicates that a large share of available equipment time was being converted into productive activity. A 12 hour daily run average also gave the team a clear measure of how much equipment time was being used each day.

Higher utilization can support top line capacity by helping a facility process more work with existing assets. Accurate data can also support bottom line savings by reducing the labor and uncertainty associated with delayed reporting. The AIM case study does not publish a revenue or cost savings figure, so the financial effect should be calculated using the facility’s own throughput value, machine costs, labor structure, and current utilization baseline.

The SensFlo ROAI Calculator helps manufacturers model the value of recovered productive time using their own operating inputs.

What other recycling operations can learn from AIM

The practical lesson from AIM is that accurate utilization begins with dependable data collection. When equipment activity is captured automatically, managers gain a clearer view of the relationship between machine time and throughput. That information can guide operational adjustments during the day and provide a stronger basis for longer term capacity decisions.

A recycling operation considering machine monitoring can begin with the assets that carry the most throughput risk. Once those machines are connected, the team can establish a baseline, review recurring idle periods or stops, and expand monitoring as the data becomes part of daily management.

Frequently asked questions

How did AIM Recycling improve equipment utilization?

AIM Recycling implemented an Industry 4.0 monitoring system with SensFlo that automated equipment data collection and made the results available through a management console. This reduced dependence on delayed or inaccurate user entered data. The published results report 90% equipment utilization and an average of 12 run hours per day.

What data did SensFlo capture for AIM Recycling?

The public case study reports more than 1,500 unique data points. The implementation included controller and analog data, fault codes, connectivity through WiFi and cellular networks, cloud based access, machine learning, and real time job profitability capabilities. The data was organized for operational review through a management console.

Why is automated equipment reporting useful in recycling operations?

Automated reporting gives managers current information about equipment activity without requiring every event to be entered manually. In a recycling facility, that supports faster review of utilization and throughput across connected equipment. It also creates a historical record that can support capacity planning, maintenance discussions, and performance comparisons.

How can a recycling company estimate the value of better utilization?

A recycling company can estimate the value by multiplying recovered productive hours by the financial value of equipment output, then accounting for labor, maintenance, and reporting savings. Since every facility has different throughput and cost structures, the most reliable estimate uses the operation’s own data. The ROAI Calculator provides a starting framework.

Manufacturers that want to compare their current monitoring needs with the available SensFlo levels can review FloControl pricing or contact SensFlo.