Tag: overview

  • [Guide] What Is Machine Monitoring, and Why Does It Matter

    [Guide] What Is Machine Monitoring, and Why Does It Matter

    Introduction

    If you’re running a small or medium-sized manufacturing operation, you’ve likely heard about machine monitoring. But what exactly is it, and why should you care? 

    Simply put, machine monitoring is your direct window into how your equipment is performing, minute by minute. It’s the difference between guessing what’s happening on your shop floor and knowing for certain.

    Machine monitoring gives small manufacturers the same visibility into operations that was once only available to large enterprises with massive budgets. It’s not just about tracking when machines are running or stopped anymore—it’s about understanding why, predicting what might happen next, and making smart decisions based on real data, not hunches.

    In this guide, we’ll break down what machine monitoring is in practical terms, show you how it works without the technical jargon, and explain why it matters especially for smaller operations where every minute of downtime hurts your profit.

    What Is Machine Monitoring?

    Machine monitoring is the process of collecting, analyzing, and acting on data from your manufacturing equipment in real time. It’s like having a health monitor for each of your machines that constantly checks vital signs and alerts you to any issues before they become major problems.

    At its core, machine monitoring uses sensors and connections to your existing equipment to gather information on:

    • When machines are running versus sitting idle
    • The actual length of production cycles compared to expectations
    • Why downtime occurs and how often
    • Which machines might soon have maintenance needs
    • How your overall production efficiency stacks up

    The beauty of modern machine monitoring is its simplicity. While the technology behind it is sophisticated, using it doesn’t have to be complicated. Today’s systems are designed to be user-friendly, offering clear dashboards that show you exactly what you need to know without requiring an engineering degree to interpret.

    For small manufacturers, machine monitoring isn’t about collecting data for data’s sake. It’s about getting practical insights that help you make better decisions about scheduling, maintenance, staffing, and quoting new jobs with confidence.

    Why Does Machine Monitoring Matter for Small and Medium Manufacturers?

    Small and medium manufacturers face unique challenges that make machine monitoring particularly valuable:

    Doing More With Limited Resources

    Unlike large corporations, you don’t have excess capacity sitting idle. When a machine goes down unexpectedly, it immediately impacts your delivery schedule. Machine monitoring gives you early warning of potential issues so you can address them before they cause delays.

    For example, vibration analysis might detect a bearing that’s starting to wear before it fails completely. This lets you schedule maintenance during planned downtime rather than suffering through an emergency repair that stops production entirely.

    Making Data-Driven Decisions

    How long does a typical job really take on your shop floor? Without monitoring, you’re often relying on estimates or operator-reported times that may not capture the full picture.

    With machine monitoring, you know exactly how long similar jobs have taken in the past, allowing you to quote new work more accurately. This means better margins on jobs and more realistic delivery promises to your customers.

    Identifying Your True Capacity

    Many small manufacturers are actually running at a fraction of their potential capacity without realizing it. Short stops, slow cycles, and inefficient changeovers eat away at productive time.

    Machine monitoring reveals these hidden capacity killers. One small machining company discovered through monitoring that they were losing over 20 hours of production weekly to short, unrecorded stops. Addressing these issues was like adding another machine without the capital expense.

    Improving Without Expanding

    Before investing in new equipment, it makes sense to maximize what you already have. Machine monitoring shows you exactly where to focus improvement efforts for the biggest return.

    A producer of aerospace parts in Missouri had set a goal of raising their machine utilization, so they’d be running at least 65% of their staffed time. Using machine monitoring in combination with Lean methodology, they reported “an easy 15% or more improvement in utilization.”

    Success factors

    You may have noticed it already in the case study above. Machine monitoring is a tool in your belt. But how you use it is up to you. Just like the manufacturer from St. Louis that we just described, you need to:

    • Set specific, meaningful goals: You can pursue many kinds of “improvement.” But not all of them will yield equal business benefits in your specific situation. The manufacturer in our example focused on utilization, which mattered most to them. They also set their goal at an attainable level. For comparison, at a rule of thumb level, a 20-30% improvement would be very good for most operations optimization initiatives. So our example manufacturer’s 15% improvement from limited effort is impressive.
      Setting “SMART” goals is often seen as a gold standard for setting such goals. But be sure you don’t get so enamored with precision that you lose the view of the big picture. For example, the aerospace company’s goal of “65% utilization” is quite simple. But it still set an aggressive standard that was meaningful for them.
      What will most move the needle for you? What degree of improvement is realistic in your context?
    • Build capabilities, not just tools: It’s perfectly human to buy new tools and assume that they will yield results on their own. But you need complete capabilities and put in hard work to achieve the desired results. The aerospace manufacturer from our example used machine monitoring to generate insights as well as Lean methodology to make use of the lessons. And all of that is only possible if you have people who can do this sleuthing and have sufficient time and authority to do the work properly.

    How Machine Monitoring Actually Works

    Let’s demystify how machine monitoring systems actually capture and process information from your equipment:

    1. Data Collection: The Foundation

    Machine monitoring starts with connecting to your equipment. There are typically two approaches:

    • Direct integration: For newer CNC machines and equipment with built-in computer controls, machine monitoring systems can often connect directly to read operational data. This might use standard protocols like MTConnect or OPC-UA that many modern machines support.
    • Sensor-based monitoring: For older equipment without built-in data outputs, simple sensors can be attached to monitor power usage, vibration, temperature, or simply whether a machine is running. These retrofit solutions make it possible to include all your equipment in your monitoring system, regardless of age.

    The good news? You don’t need to replace your existing machines to start monitoring them. Most small manufacturers use a mix of both approaches depending on their equipment.

    2. Data Transmission: Getting Information Where It Needs to Go

    Once collected, data needs to reach your monitoring system. This typically happens through:

    • Wired connections: Traditional ethernet networks within your facility
    • Wireless transmission: WiFi or cellular connections for flexibility
    • Edge devices: Small computing devices that sit near your machines to pre-process data

    Most systems today use secure cloud storage, meaning you can access your machine data from anywhere, whether you’re on the shop floor or checking in from home after hours.

    3. Data Analysis: Turning Numbers Into Insights

    This is where machine monitoring really shines. Modern systems don’t just collect data. They analyze it to:

    • Calculate Overall Equipment Effectiveness (OEE) to show your true productivity
    • Identify patterns in downtime or quality issues
    • Detect when machine performance is starting to drift from normal
    • Create performance comparisons across different shifts, operators, or job types

    The analysis happens automatically, meaning you get useful information without having to spend hours crunching numbers yourself.

    4. Visualization and Alerts: Making Data Usable

    Finally, the system presents information in ways that make sense:

    • Real-time dashboards showing current machine status across your shop
    • Historical reports to spot trends and improvement opportunities
    • Automatic alerts when issues arise, delivered by text, email, or app notifications
    • Performance comparisons against goals you’ve set

    These visualizations and alerts turn complex data into clear action items for your team, whether it’s addressing a machine that’s down, shifting work to underutilized equipment, or recognizing which jobs consistently run efficiently.

    Key Features to Look For in Machine Monitoring Systems

    Not all machine monitoring solutions are created equal. Small manufacturers should look for these essential features:

    Easy Implementation

    The best systems for small manufacturers offer:

    • Quick setup without extensive IT requirements
    • Ability to start small and expand over time
    • Minimal disruption to ongoing operations
    • Clear implementation support and training

    User-Friendly Interfaces

    Look for:

    • Dashboards that anyone in your shop can understand at a glance
    • Mobile access so you can check status from anywhere
    • Customizable views that highlight what matters most to your operation
    • Visual trouble indicators that make problems immediately obvious

    Flexible Connection Options

    Ensure the system can:

    • Connect to a wide range of equipment types and ages
    • Work with both modern and legacy machines
    • Offer retrofit options for older equipment
    • Expand with you, as you add or upgrade machines

    Actionable Intelligence, Not Just Data

    The system should provide:

    • Clear reasons for downtime, not just duration
    • Trends that help predict and prevent future issues
    • Comparisons against your defined targets
    • Practical recommendations for improvement

    Cost-Effective Scaling

    Look for pricing that:

    • Starts affordable for small operations
    • Scales reasonably as you grow
    • Delivers clear ROI within months, not years
    • Doesn’t require expensive IT infrastructure

    Real Benefits Small Manufacturers Are Seeing

    Machine monitoring isn’t just theory. It’s delivering measurable results for small manufacturers across industries:

    Reduced Downtime

    A contract manufacturer in Michigan reported a 37% reduction in unplanned downtime within three months of implementing machine monitoring. By addressing the top three downtime reasons identified by their system, they recovered over 400 production hours annually.

    Improved Utilization

    A precision parts maker discovered through monitoring that their most expensive CNC machines were actually running for just 35% of available time, far below industry benchmarks. After implementing changes based on monitoring data, they increased utilization to over 60%, effectively adding capacity without buying new equipment.

    Better Quality Control

    By correlating machine performance data with quality metrics, a small aerospace parts supplier identified specific machine conditions that predicted quality issues. Addressing these conditions before they affected parts reduced their scrap rate by 23%. 

    Enhanced Maintenance

    Rather than performing maintenance on a fixed schedule, many small manufacturers now use monitoring data to perform maintenance exactly when needed. One company extended the life of expensive tooling by 40% while simultaneously reducing emergency repairs by 65%.

    Competitive Quoting

    With accurate data on true production times, small manufacturers can quote jobs more precisely. A custom fabricator attributes winning 15% more competitive bids to their ability to quote jobs based on actual production data rather than estimates.

    Getting Started: First Steps Toward Implementation

    If machine monitoring sounds valuable for your operation, here’s how to begin:

    1. Define Your Goals

    Start by identifying your biggest pain points:

    • Are unexpected breakdowns (i.e., reactive maintenance) disrupting your schedule?
    • Do you suspect machines sit idle more than they should?
    • Are you struggling to meet production quotas and delivery dates?
    • Do you question whether you’re getting maximum value from your equipment?

    Your specific challenges will guide which aspects of machine monitoring to prioritize.

    Consider setting “SMART” goals for your team, as long as the resulting precision clarifies without causing analysis paralysis.

    2. Start Small But Think Big

    You don’t need to monitor every machine on day one:

    • Begin with 2-3 critical machines that impact your throughput most
    • Choose equipment that represents different machine types on your floor
    • Select machines with known issues that you want to address
    • Pick a work center that’s a bottleneck in your process

    This focused approach lets you learn the system and demonstrate value before expanding.

    3. Involve Your Team Early

    Machine monitoring works best when your team embraces it:

    • Explain how it will make their jobs easier, not monitor their performance
    • Include operators in the implementation process
    • Use their knowledge to help interpret initial data
    • Share wins and improvements the system helps identify

    When operators see monitoring as a tool that helps them succeed rather than a way to watch over them, adoption becomes much smoother.

    4. Establish Baseline Metrics

    Before making changes, use your new monitoring system to establish current performance:

    • Document current OEE (Overall Equipment Effectiveness)
    • Track typical downtime causes and durations
    • Measure average setup times
    • Record standard cycle times for common jobs

    These baselines give you a starting point to measure improvements against.

    5. Act on What You Learn

    The most important step is using your new insights to drive action:

    • Address the top three downtime causes revealed by your data
    • Adjust maintenance schedules based on actual machine conditions
    • Re-allocate work to maximize utilization across all equipment
    • Update quoting standards based on real production times

    Machine monitoring delivers value only when you use the information to make changes.

    Conclusion: Machine Monitoring Is No Longer Optional

    Yes, even for smaller manufacturers who compete in today’s market, machine monitoring has shifted from a nice-to-have technology to an essential operational tool.

    When larger competitors optimize every aspect of their production using sophisticated data, running blind puts smaller operations at a significant disadvantage.

    The good news is that machine monitoring systems have become more affordable, easier to implement, and specifically designed for small to medium manufacturers. The investment typically pays for itself within months through improved utilization, reduced downtime, and better decision-making.

    Most importantly, machine monitoring gives you certainty in an uncertain world. Instead of wondering what’s happening on your shop floor or why you’re missing delivery dates, you’ll know exactly where you stand, why issues occur, and what to do about them.

    In manufacturing today, the difference between thriving and merely surviving often comes down to how well you understand your own operation. Machine monitoring provides that understanding in real time, giving even the smallest manufacturers the insights they need to compete and win.

  • [White Paper] Route Costing and Energy Tracking Solutions for small and Mid-Sized Manufacturers

    1. Introduction: Energy Challenges for SMB Manufacturers

    Manufacturing is inherently energy-intensive. For small and medium-sized manufacturers (SMMs), energy management has historically been an underdeveloped capability — often because they needed to prioritize keeping production running with limited staff and resources.

    Many SMBs treat energy as a fixed overhead: one big monthly bill from the utility company, with little visibility into which machines or processes are driving costs. This lack of granularity means wasted energy often goes undetected.

    In both the United States and Europe, external pressures are increasing:

    • Energy price volatility — In 2024, European industrial electricity averaged €0.199/kWh, about 2.5× higher than U.S. industrial rates ($0.075/kWh) .
    • Sustainability demands — Larger OEMs are requiring suppliers to provide carbon footprint and efficiency data.
    • Regulatory compliance — EU’s Energy Efficiency Directive and similar policies encourage (or require) better energy tracking.

    Route-level energy tracking addresses these challenges by breaking down energy consumption to individual machines, lines, or product routes — turning energy into a controllable variable rather than a hidden overhead.

    2. Understanding Route-Specific Energy Tracking

    In manufacturing, a route is the sequence of processes a product undergoes from start to finish — for example, cutting → milling → heat treatment → finishing.

    Route-specific energy tracking captures the energy used at each stage, enabling calculation of:

    • Total kWh per product
    • Energy cost per batch or order
    • Carbon emissions tied to each production route

    How It Works

    1. Sensors — Non-intrusive clamp-on current transformers (CTs) are installed on machine power lines to measure electricity draw in real time.
    2. Gateways — These collect sensor data and transmit it to the cloud via Wi-Fi, Ethernet, or LoRaWAN.
    3. Cloud Platforms — Software aggregates, stores, and visualizes the data, often with analytics to identify anomalies or trends.
    4. Integration — Energy data can be linked to production counts from MES/ERP systems to calculate energy per unit produced.

    3. Technology Landscape

    All-in-One IoT Energy Platforms

    Vendors in this category supply the sensors, gateways, and cloud platform as a turnkey service. Examples include solutions that:

    • Use self-powered clamp sensors (no batteries or wiring)
    • Offer per-sensor subscription pricing
    • Provide dashboards, reporting, and alert features

    Pros: Simple deployment, minimal in-house IT required.
    Cons: Ongoing subscription costs, limited customization.

    Standalone Hardware + Custom Integration

    Some SMBs buy wireless energy sensors (e.g., Pressac, Monnit) and integrate them with open-source or in-house analytics platforms (like ThingsBoard, Node-RED).

    Pros: Lower long-term cost, high flexibility.
    Cons: Requires technical skill, more maintenance responsibility.

    Energy Management Software (EMS)

    Platforms such as Wattics or EnergyCAP aggregate energy data from various sources. Typically software-led, they can work with existing meters or IoT devices.

    Pros: Strong analytics, can cover multi-site operations.
    Cons: Often requires existing metering hardware.

    Machine-Embedded Monitoring

    Some OEMs build energy monitoring into machines. This can be used where applicable but is rarely consistent across mixed fleets.

    4. Pros and Cons

    Advantages

    • Granular Visibility — Machine-level data shows exactly where energy is used .
    • Cost Savings — Case studies report 5–15% energy reduction after implementing continuous monitoring .
    • Predictive Maintenance — Abnormal power draw patterns can signal mechanical issues .
    • Accurate Product Costing — Assigning real energy costs to each product enables better pricing decisions.
    • Sustainability Reporting — Facilitates ISO 50001 compliance and ESG reporting.
    • Behavioral Change — Real-time dashboards encourage operators to eliminate waste.

    Challenges

    • Upfront Cost — Even affordable systems require investment.
    • Technical Complexity — SMBs may lack internal IT/OT expertise.
    • Data Overload — Without goals, large data sets can overwhelm.
    • Integration Hurdles — Linking with MES/ERP may require custom work.
    • Accuracy — Lower-cost sensors can drift; periodic calibration may be needed.
    • Workforce Adoption — Must avoid perceptions of “monitoring people” rather than processes.

    5. Real-World Case Studies

    Of course, your plant is unique. Your challenges and possible benefits will differ from those of anyone else. But it’s still helpful to see that energy tracking truly translates into savings and better OEE across many industry sectors and geographies. If energy matters to your business, then monitoring it benefits your business too.

    When it comes to specific savings, it’s smart to be skeptical of self-reported figures. Luckily, neutral outside researchers confirm the hard benefits of energy monitoring too. For example:

    Monitoring lets you fight the hidden cost of idle energy

    Idle equipment can consume 60%+ of a facility’s total energy load (e.g., one study found idle energy to consume 38 – 63% of total energy use). That’s power burned without producing anything—an enormous opportunity for factories to reclaim wasted capacity. But it takes monitoring to find it. For example, the study referenced above monitored for energy savings potential at four levels: Systems, process, equipment, and facility levels.

    Real-time usage monitoring Unlocks Additional Improvements

    Other research from the Automotive sector highlights the benefits of collecting and analyzing data in real time. That plant achieved a roughly 8% boost in annual energy efficiency, using analyzers and SCADA-integrated monitoring. With visibility into real-time usage, management could spot waste and implement smarter energy policies that stuck.

    Both raw cost savings and return on investment are attractive

    Of course, energy savings are only useful if the investment needed to achieve the savings is reasonable. Luckily, you can achieve good ROI with energy monitoring.

    For example, one factory that researchers studied not only cut 10% from their total annual energy costs via energy monitoring and action but also achieved a 14-month investment payback period, all on a meaningful scale, with roughly 192,000 kWh saved over six months.

    Industry expertise matters more than data science sophistication

    These savings would be out of reach for smaller manufacturers if one always needed dedicated data scientists to produce results. Hiring data scientists can be near-impossible, especially for smaller and mid-sized companies, since demand for them far outstrips supply. This has driven up wages and made even the available data scientists unrealistically expensive to hire.

    But luckily, results don’t depend on advanced statistics and data handling techniques. Researchers found that practical, real-world experience in and understanding of plants turns out to be the “key performance improver over state-of-the-art deep learning techniques.” In their study a chiller plant’s team used their domain knowledge to achieve 7% daily power savings. With energy monitoring data in hand, this team created simple models that captured the actual mechanism at work in the equipment. They accurately captured the plant’s running status and optimized it in real time, achieving savings without relying on advanced theory.

    6. Regional Comparison: U.S. vs. Europe

    FactorUnited StatesEurope
    Electricity CostAvg. $0.075/kWhAvg. €0.199/kWh
    Regulatory PressurePatchwork; mostly voluntaryStrong EU directives, national programs
    Adoption DriversCost savings, IoT trendCost savings, compliance, sustainability
    IncentivesDOE Industrial Assessment Centers, utility rebatesEU & national grants, tax breaks for ISO 50001
    Vendor LandscapeMachineQ, Monnit, EMS platformsSensorfact, Dexma/Wattics, Pressac, ABB

    European SMBs often adopt faster due to higher energy costs and regulatory mandates, while U.S. SMBs are catching up as IoT affordability improves.

    7. Implementation Guidelines

    1. Baseline Review: Gather utility data, identify major loads.
    2. Set Goals: Examples: reduce idle energy by 20%, track energy cost per product.
    3. Pilot Project: Start with 2–3 major energy consumers.
    4. Select Technology: Match budget, scalability, and integration needs.
    5. Install & Verify: Ensure sensors are accurate; cross-check with main meter.
    6. Analyze Patterns: Look for peaks, idle loads, and outliers.
    7. Act: Adjust schedules, fix leaks, upgrade inefficient equipment.
    8. Scale Up: Extend monitoring plant-wide; integrate with ERP/MES.
    9. Train Staff: Build energy awareness into daily operations.
    10. Improve Continuously: Review monthly, update targets, and maintain sensors.

    8. Conclusion

    Route costing and energy tracking is no longer reserved for large enterprises. Affordable IoT technology, combined with rising energy costs and sustainability expectations, makes it an essential tool for SMB manufacturers.

    By breaking energy down to the machine or product level, manufacturers can:

    • Reduce costs
    • Improve operational reliability
    • Accurately cost and price products
    • Meet compliance and sustainability demands

    Real-world case studies show that 5–15% savings is common, often with payback in under two years. The key is to start small, stay goal-focused, and build a culture where energy is managed as carefully as any other production input.