Manufacturers have more information available than ever before. The challenge is knowing what information matters, how to capture it and how to use it to improve performance.
A production line can tell you a lot when the right data is being collected. It can show torque values, cycle counts, fault history, part results, weld parameters, leak test readings, temperature changes, scrap trends and operator performance. It can help teams see why a machine is down, why parts are failing or why one shift is producing less than another.
Without that information, teams are often left guessing.
At Envision Automation, we help manufacturers use data acquisition systems to collect the right information from machines, processes and production environments, then turn that information into real-time insights operators, maintenance teams and managers can actually use.
What Is Data Acquisition in Manufacturing?
Data acquisition is the process of collecting information from machines, sensors, controls, inspection systems and production equipment so it can be displayed, tracked, stored and analyzed.
That information may come from many sources, including:
- Torque tools
- Vision systems
- Analog sensors
- Digital signals
- PLCs
- Barcode readers
- Leak testing equipment
- Weld systems
- Switches and cylinders
- Environmental sensors
- Operator inputs
The system may display information on an HMI, send alerts to maintenance, show trends on a computer monitor, store production records or tie specific process data to a unique part barcode.
Our goal in each customer scenario is to capture useful information that helps the facility improve quality, reduce waste, troubleshoot faster and make better production decisions.
The Problem: Too Much Production Happens Without Clear Visibility
Many facilities track some information, but they may not have a complete picture of what is actually happening inside the process.
For example, an assembly system may use screws to attach components. In that case, it may not be enough to simply know that the screw was installed. The manufacturer may need to know the torque and angle of the screw, including how many revolutions were required to reach specification.
That level of information matters because quality issues can become serious after the product leaves the plant. Parts that were not tightened correctly can lead to failures, warranty claims or recalls. When data is captured per part, the manufacturer has a clearer record of what happened during production.
The same applies to welding, leak detection and other process-critical applications. A facility may need to track time, temperature, probe distance, leak rate, air volume, helium detection or other measurable conditions. In some cases, even the room temperature at the time a part was welded may be relevant.
When that information is not tracked, the team may only see the result: scrap, rework, downtime or customer issues. Data acquisition helps reveal the conditions that caused the result.
Tying Data to the Part
One of the most valuable ways Envision Automation uses data acquisition is to tie process information to a specific part.
This is often done with a unique barcode on the part. As the part moves through production, the barcode follows it through the data acquisition system. Each step can add information to that part record, including inspection results, torque readings, weld data, leak test results or other process details.
That record can be valuable during production, but it can also be useful after the sale. If a customer has a question or a quality issue needs to be investigated, the manufacturer can look back at the data connected to that part instead of relying only on general production history.
Real-Time Insights for Better Production Decisions
Data acquisition gives manufacturers a clearer view of what is happening right now.
Information within Envision Automation systems can be displayed on an HMI, shown on a computer monitor, sent to maintenance personnel by email or used to trigger an alarm banner. The exact display depends on what the end user needs, but the purpose is the same: make important information visible at the right time.
For operators, that may mean seeing a fault, process value or part result immediately.
For maintenance teams, it may mean receiving alerts when equipment is trending toward a problem.
For managers, it may mean reviewing performance by shift, machine, part type or production run.
When the right data is visible, teams can move from reacting after the fact to identifying problems earlier.
How Data Acquisition Supports Quality
Quality problems for our customers often come down to process conditions. A part may be out of tolerance because something changed in the machine, tool, temperature, material, operator sequence or assembly process.
Data acquisition helps manufacturers connect the result to the conditions that created it.
For example, a facility may be scrapping too many parts. Without data, the team may only know that scrap is high. With data acquisition, the team may be able to see when the scrap occurs, which machine is involved, which shift is running, what faults happened before the scrap increased and which process values were outside the expected range.
That information makes troubleshooting more focused.
Instead of asking, “Why are we scrapping 15% of these parts?” the team can begin asking better questions:
- Did the problem start after a changeover?
- Is one shift seeing more faults than another?
- Did torque values drift before the failure?
- Was a weld temperature or leak test value outside the normal range?
- Did a specific operator sequence create the issue?
- Is a machine component nearing the end of its expected cycle life?
The better the data, the easier it becomes to investigate the real cause of the quality issue.
Using Data to Improve Preventative Maintenance
Data acquisition is not only useful for part quality. It can also help with maintenance planning.
Manufacturers can monitor the life cycles of switches, cylinders and other components by tracking how many times they have been actuated. Instead of waiting for a component to fail, maintenance teams can use that cycle count to plan service before downtime occurs.
This can be especially useful on equipment that runs continuously or across multiple shifts. A machine may be operating normally today, but the data may show that a cylinder, switch or actuator is approaching a maintenance threshold.
That information helps our customers’ teams make smarter decisions and reduce unexpected downtime.
Where Ignition Fits In
Included in Envision Automation systems, Ignition is a strong software platform for data acquisition, visualization and control system information.
It runs on a PC and can display information on a standard monitor or touchscreen monitor. It can show multiple screens, dashboards, trends, alarms and production information. Ignition is especially well known for data tracking, but it can also be used for HMI needs. In some applications, it can replace traditional HMI hardware by using a touchscreen monitor connected to the system.
For manufacturers that want better visibility across equipment, Ignition can serve as the central place where production information is collected, displayed and organized.
How Ignition Connects to Equipment & Legacy Systems
Ignition is tag-based. In automation and controls systems, programs use tags to represent information from the equipment. Those tags may include digital signals, analog values, status information, counts, alarms and process data.
With the right integration from Envision Automation, that information can be brought into a PC over Ethernet. As Ethernet speeds continue to improve, systems can transmit large amounts of data quickly. That makes it possible to collect and display information from multiple pieces of equipment.
This is especially helpful in facilities with a mix of newer equipment, older machines, PLCs and process systems. The data acquisition system can help bring that information together so the plant has a clearer view of performance.
The First Win: Knowing What Is Performing Well & What Is Not
One of the first benefits Envision Automation customers often notice is better performance visibility.
When data is being collected correctly, teams can see what is performing well and what is performing poorly. They can track production, downtime, faults, scrap and process values. They can investigate a drop-off instead of guessing at the cause.
That kind of visibility can be especially helpful for overall production management. When a line is underperforming, the data can show where the issue is happening and when it started. When a machine is running well, the data can help establish a baseline for what good performance looks like.
Data Revealing the Real Cause of Downtime
In one past application of data systems, a machine was running across three shifts. First shift and third shift were producing nearly identical volumes, but second shift was significantly behind and had more downtime.
Without data, it may have been easy to blame the machine. But the data showed how many times the machine faulted and when those faults occurred. After reviewing the information, the issue was narrowed down to operator error.
The operator was moved to a different machine and performed fine there. The original machine then returned to expected production levels across all shifts.
That is the value of data acquisition. It gives teams evidence. It helps separate machine issues from process issues, training issues, maintenance issues or operator fit. The result is a more accurate fix.
The Biggest Barrier: Knowing What Data Actually Matters
One of the biggest challenges with data acquisition is deciding what to track.
Many of our customers know they want more information, but they’re not always sure what information they need. With Industry 4.0 and the Industrial Internet of Things, there is a lot that can be tracked. That doesn’t mean everything should be tracked.
Trying to capture everything can bog the system down and overwhelm the people using it. Too much data can make it harder to see what actually matters.
The better approach is to define the critical information first.
- What problem are you trying to solve?
- What quality issue are you trying to reduce?
- What downtime event keeps happening?
- What process value affects whether the part passes or fails?
- What information would help maintenance act sooner?
- What information needs to be tied to each part for traceability?
A good data acquisition project starts by identifying the useful data, not by collecting every possible value.
How Manufacturers Should Start
For companies early in digital transformation, the best starting point is the production problem they already know they have.
Maybe the facility is scrapping too many parts. Maybe a machine has unexplained downtime. Maybe one shift performs differently than another. Maybe there is a process-critical step that needs better documentation. Maybe the company wants better traceability after parts leave the facility.
The first step is to identify the struggle.
From there, Envision Automation can help determine what information should be collected, where it should come from, how it should be displayed and how it should be used. Every system is custom and one-off because every production process is different.