Machine Monitoring
Machine monitoring gives you a real-time view of what your equipment is actually doing. Machine monitoring software and hardware systems are designed to deliver real-time production visibility with minimal disruption to existing processes.
When production data is collected automatically - directly from the machine - assumptions disappear. You see where time is being lost, where performance is slipping, and where capacity can be recovered.
Accurate data creates alignment. Operators, supervisors, and plant managers work from the same numbers, which makes improvement straightforward and measurable.
What Is Machine Monitoring?
In manufacturing, machine monitoring is the method of using sensors to collect data from key pieces of equipment in your manufacturing process - usually the constraint - and converting those signals into usable production metrics.
Instead of relying on handwritten logs or end-of-shift summaries, machine monitoring captures activity as it happens. A small number of inputs can generate OEE, TEEP, the Six Big Losses, and other core metrics that expose downtime, slow cycles, quality loss, and so much more.
The value is not in collecting more data for data's sake. The value is in making performance visible while there is still time to respond.
When implemented correctly, machine monitoring often reveals untapped capacity that can be recovered without additional labor, overtime, or new equipment.
Modern machine monitoring systems combine purpose-built industrial hardware with integrated analytics in a single platform designed specifically for the plant floor.
How Does Machine Monitoring Work?
The ultimate goal of machine monitoring is to gain a deep understanding of all aspects of your manufacturing process, enabling you to view in-depth production data at the machine, plant, and enterprise levels. After signals are captured and translated into production data, the system organizes that information into a format your team can easily understand and use.
- Performance becomes visible in real time.
- Losses are categorized instead of guessed.
- Trends emerge instead of isolated incidents.
Instead of sorting through spreadsheets or waiting for end-of-shift summaries, your team can see what is happening while the shift is still running.
That visibility changes behavior.
With only two or three sensors, data for over 100 actionable and meaningful metrics can be generated and distilled into easily digestible reports, and even more importantly, a foundation for action.
- Plant managers can monitor overall performance and measure progress over time.
- Supervisors can focus improvement efforts where they will have the greatest impact.
- Operators can respond immediately to slow cycles or unexpected downtime.
When the data is structured and visible, the process becomes easier to manage - and easier to improve.
The Role of the Plant Manager
During Planning and Preparation
The plant manager reviews top-level business objectives to determine which manufacturing KPIs should be prioritized.
We recommend the plant manager align business objectives to the KPIs monitored.
The key question is straightforward:
Which KPI, if improved, will create the greatest business impact?
The plant manager also defines the policies and standards that govern the machine monitoring system. These standards ensure consistency and accuracy in the data. For example:
- Capture a reason for every down event.
- Capture a comment for every down event longer than 15 minutes.
- Measure changeover time as last good piece (previous part) to first good piece (next part).
Clear standards create reliable data. Reliable data supports better decisions.
After Implementation
The plant manager monitors top-level KPIs such as OEE and TEEP.
The emphasis should be placed on trends over time rather than isolated values. The rate of improvement is often more important than the number itself.
If the desired rate of improvement is not being achieved, adjustments to strategy or priorities may be necessary.
The Role of Line Supervisors
During Planning and Preparation
Supervisors determine where automated data should be captured — typically at the constraint.
They also ensure that any required manual inputs are standardized and clearly defined. Consistency is critical. For example, vague or inconsistent downtime reasons limit the ability to improve.
We recommend that line supervisors determine the best points of the manufacturing process from which to capture automated data (usually the constraint of the process), as well as whether there are any critical lines that warrant extra attention. There may also be some data that should be captured manually, such as explanatory comments from operators regarding truly unusual circumstances like very long down events or changeovers that are well beyond their target time. In such cases, we recommend that the line supervisor create standardized work procedures and train operators on these procedures so that all data is consistently captured.
After Implementation
Line supervisors translate strategy into daily action.
One of the most important roles of line supervisors is to analyze the data collected and make adjustments to tactics to improve specific metrics. We also recommend that line supervisors pay close attention to engaging with and motivating plant-floor operators, especially in the context of meeting or exceeding targets, or as we like to refer to it, “winning the shift.”
The Role of Plant Floor Operators
During Planning and Preparation
Operators are trained on new processes and procedures associated with the system.
Beyond procedural training, it is important that operators understand how their actions affect overall plant performance. Understanding purpose increases engagement.
We recommend that operators are trained on any new processes. Beyond learning procedures, ensuring that operators understand why their work is important in relation to the company’s greater strategy is crucial to obtaining buy-in and a sense of purpose. It can be difficult to adapt to changes in work procedures, so ensuring operators understand how and why their contributions matter will help keep them engaged and motivated.
After Implementation
Operators use real-time machine data to make adjustments during the shift.
The role of plant floor operators is to use real-time data from their line to make decisions and adjustments during their shift. For the best results, we recommend a plant floor scoreboard be hung within view of operators to show real-time production data and provide operators with a direct visual feedback loop on their actions. After all, real-time machine monitoring is only helpful if the data collected is readily available so action can be taken to make improvements.
In advanced systems, operators can interact directly with the monitoring device to enter downtime reasons, review performance, and adjust targets in real time. Immediate visual feedback - and in some cases audible reinforcement - helps sustain focus throughout the shift.
Why Is Machine Monitoring Important?
Machine monitoring replaces assumption with evidence.
Machine monitoring adds a tremendous amount of value because it transitions decisions and actions from subjective to objective, from assumption-driven to data-driven. In other words, machine monitoring, when implemented properly, results in comprehensive, highly accurate, and objective data that can be easily shaped into insightful actions.
A reliable data foundation creates alignment across the organization. It provides a consistent reference point for operators, supervisors, and managers - and supports steady, focused progress.
It Creates a Rich, Reliable Data Foundation
Machine monitoring creates a rich and connected data foundation comprising a broad range of metrics. Here are some examples of metrics that can be generated from just two or three sensors.
| Metric Category | Representative Examples |
|---|---|
| Six Big Losses | Down Loss, Cycle Loss, Startup Reject Loss |
| Counts | Good Count, Reject Count, Startup Rejects |
| Rates | In Rate, Target Rate, Rate Efficiency |
| Labor | Labor per Good Piece, Earned Labor, Lost Labor |
| OEE | OEE Loss, Availability Loss, Performance Loss, Quality Loss |
| Cycles | Run Cycles, Equipment Cycles, Small Stop Lost Time |
| Production Times | Run Time, Down Time, Planned Stop Time |
| Target | Target Count, Efficiency, Count Variance |
| TEEP | Utilization, Schedule Loss, Hidden Factory Time |
The result of implementing a machine monitoring system is achieving a consistent data foundation across your manufacturing equipment from which all employees can draw upon and make data-driven decisions. We like to refer to this as creating a “data democracy.”
We also think it’s important to emphasize the difference between “data” and “information.” Machine monitoring begins with data collection, but the goal is to leverage that data into actionable information.
It Generates Accurate and Unbiased Data in Real Time
Manual tracking introduces error. Estimates introduce bias. Delayed reports limit response time.
Automated machine monitoring removes those variables.
Because data is captured directly from the equipment and delivered in real time, issues can be addressed while they are still affecting performance.
Since machine monitoring makes data collection a largely automated process, it removes the elements of human error and unconscious bias. And since data is delivered in real time, your team can transition from being reactive (acting after the fact) to being proactive (responding immediately).
In our experience, companies usually have a reasonably accurate understanding of their quality losses. On the other hand, companies are often shocked when they discover the true extent of their downtime and how much manufacturing time is lost to slow cycles and small stops. While it can be a bit unsettling at first, it is necessary to have an accurate understanding of your manufacturing production losses in order to effectively address them.
Clear data can be uncomfortable - but it is critical for improvement.
It Empowers Your Team to Take Action with Confidence
Once you have a foundation of timely and accurate information, you are well-positioned to leverage that information into results.
We refer to this progression as IDA:
Information → Decision → Action.
We highly recommend the IDA framework as an easy and effective way to transform information generated by machine monitoring into results that boost your bottom line.
Machine monitoring provides your team with the ability to look forward towards progress rather than looking backward at missed opportunities. Monitoring production without taking action provides no benefit to your processes or bottom-line profitability. But, taking action is also where many companies falter. It is much easier to consistently collect data than to consistently take action on that data. That is why organizing data into actionable information is so important. For example, when data is organized into Top Losses, it is immediately clear where improvements will have the biggest impact.
A simple starting point is to select the largest production loss where:
- The team understands the cause
- Actions can be taken immediately
- Minimal external resources are required
Small, consistent improvements compound over time.
It Strengthens ERP and MES Integrations
Machine monitoring systems add even more value when integrated with your ERP or MES system. There are two key integration points.
1. Input from ERP/MES
The first integration point is having your ERP or MES provide key values, such as Ideal Cycle Time or Takt Time, to your machine monitoring system so metrics are calculated based on existing company standards.
One note of caution: be sure that values used for Ideal Cycle Time do not include any budgeted losses. The single most common cause of inaccurate OEE scores is Ideal Cycle Times that are too high. Machine monitoring software can notify you of this with real-time alerts or through historical analytics by detecting when Run Cycle Times are faster than Ideal Cycle Times or by detecting when OEE Performance is over 100%.
2. Output to ERP/MES
The second integration point is transferring KPIs for completed jobs or part runs to your ERP or MES so job and part number costing is accurate, and so you have more accurate data for scheduling.
What Are Some Different Types of Machine Monitoring?
Machine Monitoring Across Manufacturing Processes
Machine monitoring applies to a very broad range of discrete manufacturing processes, with just a few examples being stamping, bottling, labeling, packaging, molding, assembly, forming, and printing.
The especially interesting aspect of this is that almost any type of discrete manufacturing process can be monitored in a similar way with similar metrics. Cycle times, downtime, quality, and other losses can be measured using the same fundamental principles. This makes it easy to analyze and roll up data consistently across your entire plant or even across multiple plants.
Regardless of process type, the objective remains the same:
- Measure losses at the constraint
- Quantify performance using OEE and the Six Big Losses
- Identify where improvement will have the greatest impact
The application may vary. The principles do not.
Machine Monitoring for OEE
OEE machine monitoring is truly transformational. Why? It serves as an abstraction layer that enables you to view all of your manufacturing processes from a single lens of efficiency and effectiveness. OEE, or Overall Equipment Effectiveness, and related metrics, such as Six Big Losses and TEEP, were created to serve as machine monitoring metrics, hence the equipment part of Overall Equipment Effectiveness.
OEE machine monitoring also has a very low barrier to entry. You can get started with just two sensors (monitoring Cycles and Good Count) and an Ideal Cycle Time for each part. This enables OEE software to generate a complete portfolio of OEE, Six Big Loss, and TEEP metrics.
- Availability Losses (Unplanned Stops and Planned Stops with detailed downtime reasons)
- Performance Losses (Slow Cycles and Small Stops)
- Quality Losses (Production Rejects and Startup Rejects)
Frequently Asked Questions About Machine Monitoring
Where to Go From Here
If you are tracking production manually, the next step is to automate data collection at the constraint and establish an objective performance baseline.
If you are already measuring OEE but questioning the accuracy of the data, a purpose-built system eliminates manual entry and standardizes how performance is captured.
If your goal is to increase capacity without adding labor or equipment, the practical starting point is to measure where time is being lost and quantify how much of it can be recovered.
For most manufacturers, the simplest way to evaluate impact is to pilot a system on one line, at the constraint, and review the results.
Measure first. Improve next.
How Machine Monitoring Comes Together With Vorne XL
Machine monitoring is most effective when real-time data is easy to collect, understand, and act on. Vorne XL brings these capabilities together in a single, purpose-built platform.
Automated Data Collection
Sensors connected to your machines feed real-time production data into the Vorne XL Productivity Appliance™ - no manual tracking required.
Built-In Reports and Analytics
Access OEE, downtime, Top Losses, and 140+ metrics instantly through XL's browser-based reporting tools - no software to install.
Operator and Supervisor Interaction
Operators and supervisors interact with XL devices during the shift - entering reasons, managing shifts, and viewing live status on a tablet or smartphone.
Alerts, Displays, and Integrations
Visual scoreboards, automated alerts, and ERP, MES, and PLC integrations deliver the right information to the right people at the right time.
See Machine Monitoring in Action on Your Line
With the Vorne XL Productivity Appliance™ you can:
- Win the shift by motivating your operators with real-time targets and a plant-floor scoreboard
- Instantly access 100+ real-time metrics including OEE, Six Big Losses, and TEEP
- Provide supervisors and managers immediate insights with 50+ out-of-the-box reports
- Present information exactly as you want it with an unlimited number of custom reports
- Receive email alerts when your attention is needed on the plant floor
- Receive email shift reports at the end of each shift
The Vorne XL Productivity Appliance™ is an industrial IoT (IIoT) device that delivers all of this and much more. Our most popular model is $4,690 and includes unlimited users, free software updates, free technical support, and an industry-leading 3-year warranty. There are 42,000+ XL installations across 45+ countries, and we encourage all new applications to start with a free 90-day trial. Book a one-on-one webinar and one of our product experts will explore your application.
