Industrial IoT Archives - iotindustries

OEE – Do You Think Your Production Is Running at 100%? You Might Be Losing Up to 50% of Its Potential!

11. April 2025

In many manufacturing companies, everything seems to be running smoothly at first glance. Machines are running, workers are working, and the production plan appears to be on track. Management believes that the business is operating at 100% simply because they’ve gotten used to calling this their maximum. But the reality can be quite different. Not because something visibly isn’t working, but because no one realizes that it could work much better. The company may have a hidden potential that remains untapped.

Today, the winner in manufacturing is not the one with more machines or a larger workforce. The winner is the one who can maximize the use of the resources already available. And that’s exactly the essence of the OEE – Overall Equipment Effectiveness indicator. It’s one of the most important tools for managing production performance, capable of uncovering where a company’s hidden potential lies. More importantly, it enables this potential to be converted into tangible results.

What Is OEE and What Does It Measure?

OEE is a quantitative indicator of a machine’s overall effectiveness. It measures how efficiently a machine actually operates compared to its full potential, by considering three critically important components: availability, performance, and quality.

Availability shows how much time the machine was actually producing compared to how much time it was scheduled to produce.
Performance indicates whether the machine produced the expected number of units in the actual production time, based on the ideal cycle time.
Quality measures the ratio of defect-free products to total output.

Each of these dimensions is expressed as a percentage, and the final OEE value is the product of these three percentages. In practice, this means that even if each individual component is relatively high, the combined effect may still reveal significant losses.

Example:
If a machine had 100% availability (ran for the full 8 hours) and 100% performance (produced the expected number of pieces), but only 50% of the products met quality standards, the resulting OEE would be just 50%.
Because 100% x 100% x 50% = 50%

OEE is also commonly used as a core metric in methodologies such as Downtime Management, Lean Manufacturing, Six Sigma, or Kaizen.

What Does the Final OEE Value Really Tell Us?

OEE acts like a diagnostic tool, similar to a thermometer. It won’t fix the problem by itself but helps identify it. The final OEE value is above all an indicator of where the company has room for improvement.

If availability is low, it’s time to analyze downtime.
If performance is poor, focus on optimizing production cycles.
If quality is lacking, investigate causes of defects.

Many companies assume they’re running at 90–100%, simply because production appears to be moving. But this subjective perception often hides a harsher reality. Real-world data often reveals that OEE is around 50–60%. In some cases, it’s as low as 45%, meaning more than half of the machine’s potential goes unused.
On the other hand, the “World Class” level of OEE is around 85%, which is already exceptional in many sectors. And the gap between these two levels represents a huge improvement opportunity.

It’s easy to “create” perfect numbers – by setting low production targets or ignoring true cycle times. When data is collected manually, it’s not unusual to see inflated values like 97–98%, which reflect a convenient plan, not actual performance.

Sometimes, with a poorly defined goal and only 50% availability, a company can “achieve” an OEE of over 130%. This is obviously methodologically incorrect.
Only if the cycle times reflect the real mechanical capabilities of the equipment and data collection is accurate, can OEE be a reliable indicator.

What Comes After Measuring OEE?

With a well-configured data collection system, the application itself can identify most of the specific reasons for reduced efficiency:

Why is the machine not running?
How many minutes per day are lost to short stoppages?
How often does material run out?
Which breakdowns occur most frequently?

All of this can be monitored in real-time and easily evaluated using clear reports. These reports reveal where the biggest losses occur – whether in terms of time or costs – and give management a solid basis for corrective actions.

Just like with IoT solutions, the goal isn’t to collect data. The goal is to act on it. That’s why we use the Six Big Losses model.

The Six Big Losses Model

This model categorizes losses into three groups, each linked to one of the three OEE components:

Availability Losses
- Unplanned Downtime: machine failures, missing materials, unexpected maintenance
- Planned Downtime: changeovers, scheduled maintenance, cleaning
Performance Losses
- Short Stops: brief downtimes typically under one minute
- Reduced Speed: when a machine runs slower than its optimal rate
Quality Losses
- Startup Defects: errors during machine warm-up
- Production Defects: non-conforming products during normal operation

What makes this model powerful is not just naming the six major loss types, but also assigning a specific goal for their elimination.

Some losses (e.g., unplanned downtime, short stops, speed losses, process defects) can and should be eliminated entirely.
Others (like changeovers or startup errors) can at least be minimized.

This structure helps businesses not only define problems but also set realistic and measurable goals – resulting in a much more systematic improvement process.

OEE as a Practical Tool, Not Just a Metric

One of the biggest strengths of OEE is its ability to challenge gut feelings with facts. It replaces assumptions with data, emotions with numbers, and “we think we’re efficient” with measurable reality. It exposes hidden machine capacity, which often remains unused simply because no one is tracking it.

With OEE, performance becomes something that can be measured, managed, and improved. It’s not just a metric – it’s a transformational tool.

✅ OEE Increases by 10–15% Right After Implementation

Simply starting to measure – without any other changes – often leads to a dramatic shift in behavior. It boosts discipline, reduces unnecessary downtime, and makes time usage more efficient. This “halo effect” typically results in an immediate OEE boost of 10 to 15%.
Not because the technology changed – but because awareness did.

✅ A Key Milestone on the Road to Digital Transformation

OEE is also an essential step toward digitalizing production.
It replaces paper forms, messy spreadsheets, and imprecise guesses with automated data collection, instantly available real-time reports, and a whole new level of management insight.

Companies that adopt OEE gain continuous visibility into performance – at the level of specific machines, lines, and operations.

✅ Immediate Response to Any Issue

With OEE, data is no longer a historical snapshot – it becomes a daily decision-making tool.
If management sees that a machine loses an hour each shift due to lack of materials, they can act. Maybe the issue is delayed warehouse communication. By adding a simple feature – such as an automatic alert when material drops below 10% – the downtime can be reduced from 60 minutes to just 5.

Not next week. Not after a meeting. But the next day. That’s the power of real-time data.

✅ A Continuous Optimization Process

OEE isn’t just analysis – it’s action.
Everyone from operators to managers has live access to what’s really happening. They know what changed, what worked, and what needs further adjustment. This transforms improvement from a one-off project to a continuous optimization process, built not on guesses, but on data.

✅ Savings of Tens or Hundreds of Thousands of Euros, ROI Within Months

Perhaps most importantly, OEE increases output without needing new machines.
A 25% OEE improvement across 20 machines can achieve the same output gain as buying five new machines, saving tens to hundreds of thousands of euros.

Thanks to the flexible licensing of Ignition software, the return on investment in OEE is often just a few months to a year. And from that point on, the system pays for itself.

Tailor-made end-to-end solution by IoT Industries

OEE is not just a number. It’s a tool for smarter production management – one that connects data, people, and decisions into a single, efficient system. And that’s exactly what modern manufacturing is about – not just producing, but producing effectively.

At IoT Industries, we’re ready to help you with a complete OEE implementation – from data collection to visualization.
Get in touch with us today.

Why Choose IoT/IIoT Implementation with IoT Industries?

Traditional companies typically specialize in OT (operational technologies, such as production lines and devices) or classic enterprise IT systems. However, we are able to connect both of these worlds. Our unique expertise in integrating OT and IT allows us to deliver innovative solutions in digital transformation, enhancing efficiency, reliability, and competitiveness for manufacturing companies.

Manufacturing Process Optimization That Delivers Real Results

8. April 2025

by Karin Kramara Industrial IoT Reporting and Business Intelligence SCADA/MES

Manufacturing is changing faster than ever. A globalized market, fluctuating demand, rising costs, and increasing pressure on lead times and flexibility — all of this means that simply producing is no longer enough. You need to produce efficiently. Every unnecessary step, every underutilized resource, every inaccuracy in planning or maintenance leads to a loss of time, money, resources, reputation — and ultimately competitiveness.

What is the key to sustainable efficiency? It’s not about pushing people harder or investing in new technologies without a clear strategy. The key is optimizing your manufacturing processes. But this isn’t a one-time project — it’s a systematic approach that constantly identifies bottlenecks, uncovers hidden reserves, and transforms data into tangible improvements in real time. That’s what drives lower costs, higher productivity, and overall better performance across your operations.

Why does manufacturing process optimization often fail?

Many companies have tried to “streamline” production in the past. They’ve modernized machines, adjusted shifts, introduced KPIs… Yet problems persist. Delays continue, costs rise, competitiveness drops. Why?

Because without reliable data, it’s impossible to objectively identify where the problems arise, what causes them, or how to fix them. Optimization efforts often stop at the symptoms — not the root cause.

And that brings us to the most common reason why optimization fails: many manufacturers still work with inaccurate or incomplete data. Data is collected manually, reports arrive late, and the numbers often don’t add up. As a result, decisions are based on guesswork, gut feeling, or outdated templates — not current reality. And without real data, there can be no real optimization.

What does truly effective optimization look like?

Manufacturing process optimization isn’t just about doing things faster or cheaper. It’s a far more strategic and systematic effort. It means understanding the entire value stream — from the moment raw material enters your facility to the final shipping of finished goods. The goal is to identify and eliminate anything that doesn’t add value for the customer. In practice, this includes several key steps:

✅ Gain complete and transparent visibility of your operations in real time. Because only with accurate, up-to-date data can you identify bottlenecks and make decisions based on facts, not assumptions.

✅ Minimize all forms of waste. Whether it’s time, material, machinery, human capital, or energy — any waste represents untapped potential and unnecessary cost.

✅ Optimize planning and production management. Instead of relying on ideal models or historical templates, you need to plan based on current priorities and real capacity — including staff, machines, and materials.

✅ Shift from reactive to predictive and condition-based maintenance. That means using real-time data about the current technical state and performance of machines — not waiting until failures occur.

What role does digital transformation play in this?

Thanks to digital transformation, data is no longer collected manually — it’s gathered automatically, straight from machines, production lines, sensors, and measurement devices. These insights are immediately connected with other systems like ERP, warehouse management, maintenance, or quality control.

The result is a Single Source of Truth (SSOT) — a consistent and reliable data layer that every level of management can trust, from operators to the CEO.

But to make such complex data flows work as one cohesive ecosystem, you need the right tools. This is where modern digital solutions like SCADA, MES, or EMS come into play. These systems together create an interconnected, centralized environment where data can be collected, analyzed, and visualized across the entire production process — in real time, from one place.

With this approach, data is no longer buried in complex tables — it’s transformed into clear, interactive dashboards that instantly show material availability, equipment status, energy consumption, production progress, or deviations from the plan. No more waiting for weekly reports or gathering data from multiple departments — everything is available instantly, in one place.

When efficiency drops, equipment fails, or anomalies occur, management can respond immediately. Manufacturing optimization thus becomes a proactive management tool, not just reactive analysis. Companies can prevent issues before they escalate. And even more importantly, optimization becomes a continuous, data-driven improvement process — not a one-off initiative.

A tailored solution from IoT Industries

At IoT Industries, we believe that real manufacturing process optimization starts with accurate data and well-connected systems. We help manufacturing companies set up their entire data pipeline — from collection to visualization — so they can make smarter, faster, and more confident decisions.

If you want to identify exactly where your losses are and how to turn them into savings and performance gains, we’re here to help. Let’s talk.

Why Choose IoT/IIoT Implementation with IoT Industries?

10 Reasons Why Implementing SCADA and MES Systems is the Key to Your Business Success (Part 2)

4. March 2025

by Karin Kramara Industrial IoT SCADA/MES

In the first part of this article, we discussed the major challenges that manufacturing companies face. The solution to these challenges lies in implementing SCADA and MES systems. These systems enable transparent management and optimization of production processes. While SCADA focuses on monitoring and controlling production equipment, MES is dedicated to production management, planning, tracking efficiency, and ensuring smooth production operations.

➡️ SCADA

SCADA (Supervisory Control and Data Acquisition) serves as the eyes and hands of operators. It provides real-time oversight of manufacturing technology. It primarily communicates with PLC (Programmable Logic Controller) systems, which control individual machines. However, in the IoT environment, SCADA can also communicate directly with sensors via protocols such as MQTT and OPC UA.

✅ Immediate Response to Failures

One of the key advantages of SCADA is its ability to immediately respond to failures, minimizing downtime and reducing production losses. If a machine shuts down unexpectedly, experiences performance drops, or technological deviations (e.g., unacceptable temperatures or pressures), operators can quickly intervene and restore production.

✅ Remote Control of Technology

Another key feature of SCADA is remote control of technology. It allows operators to turn equipment on and off remotely, as well as adjust parameters such as speed, pressure, and temperature directly from their interface without having to be physically present at the machine.

✅ Historical Data Storage for Analysis and Optimization

SCADA also stores historical data, enabling not only retrospective analysis of problems but also long-term improvements in production processes.

❓ When is SCADA (Not) Suitable for a Business?

If a SCADA system were not implemented, operators in smaller plants might be able to manage oversight manually. However, in large-scale enterprises, this would significantly extend response times and cause losses. Additionally, without data collection, it would be impossible to generate accurate reports, further complicating strategic decision-making at the management level.

➡️ MES

While SCADA monitors technological equipment, MES (Manufacturing Execution System) manages the production process itself. It integrates machines, materials, and workers to provide a comprehensive view of the entire production process — from planning and execution to storage. While SCADA collects data at intervals of seconds, MES links them to orders, allowing managers to monitor production status in real-time and respond to deviations immediately.

✅ Digitalization and a Unified Data Source

The MES system replaces paper-based processes with electronic data collection, ensuring that all information is available in real-time and eliminating errors caused by manual data handling.

It allows both automated and manual data entry throughout the entire production process, creating a single source of truth (SSOT). All data is centrally recorded and accessible at every level of management, eliminating delays, inaccuracies, and adjustments caused by manual reporting. Decision-making is based on hard real-time data.

✅ Automated Production Planning

One of the main benefits of MES is automated production planning. The system uses data from ERP (e.g., SAP) to manage manufacturing operations based on orders and available resources, providing a complete real-time overview of production status (WIP – Work in Progress). MES also synchronizes production data with ERP systems, ensuring seamless data exchange between the company and the shop floor without the need for manual intervention.

✅ Efficient Workforce Management

The system ensures that only qualified employees are assigned to production operations. By logging into the MES system, employees verify their credentials, and the system checks whether they meet the requirements for operating a specific machine or performing a particular task. This process eliminates errors caused by unqualified workers and reduces the likelihood of workplace accidents.

✅ Optimization of Resource Utilization

MES provides detailed insights into the use of production resources, whether it be machines, materials, or personnel. It monitors equipment conditions, reports failures, and alerts to potential shortages of materials. If necessary, the system automatically notifies the warehouse to replenish materials before production is disrupted. This approach minimizes downtime and maximizes resource utilization.

✅ Production and Product Traceability

Every manufactured unit or batch is linked to all production data — from raw materials and individual operations to the final product. This system allows for full traceability in the event of a complaint, which is crucial in industries with strict regulations, such as pharmaceuticals and food production.

✅ Quality and Performance Management

MES actively monitors the quality of production processes. It detects deviations from standards and immediately signals them, minimizing the risk of production errors. Quality data can be integrated with external software for Statistical Process Control (SPC) or Laboratory Management Systems (LMS), ensuring even more precise quality management.

The system also calculates OEE (Overall Equipment Effectiveness), identifying production bottlenecks and providing tools for their optimization.

✅ Digitalization of Documentation

MES automates document management, ensuring that workers have access to all necessary information, such as work instructions, technical drawings, and safety guidelines, at the right time. Documentation is available electronically, often via QR codes placed directly on machines, reducing the need for physical documents and increasing operational efficiency.

✅ Efficient Maintenance Management

MES plays a significant role in maintenance management. The system enables preventive maintenance planning, reducing unexpected failures and minimizing costs associated with reactive maintenance. Maintenance staff can log interventions, plan tasks, and monitor equipment status directly in the system.

MES also analyzes historical equipment performance data, allowing businesses to predict potential failures before they occur. In combination with SCADA, businesses can gradually transition to predictive maintenance, leveraging advanced analytical algorithms to detect anomalies and prevent failures before they happen.

❓ When is MES (Not) Suitable for a Business?

Not every business requires all MES system functionalities. While some companies implement only selected modules to address specific issues, industries such as pharmaceuticals or food production (F&B) often require a comprehensive MES system. These sectors must ensure batch traceability, quality control, and strict regulatory compliance, as even the smallest mistake can have serious consequences for consumer health.

Companies that aim to improve efficiency, reduce costs, and increase competitiveness can no longer rely on outdated manual processes and paper-based records. SCADA and MES are not just technologies—they are strategic tools that enable businesses to transition to smart manufacturing, driven by real-time data and automated processes. Are you ready to take the next step?

10 Reasons to Implement SCADA and MES

📌 1. Increased transparency in production processes

📌 2. Faster and more accurate reporting

📌 3. Precise inventory management

📌 4. Immediate response to issues

📌 5. Reduced downtime and prevention of unplanned failures

📌 6. Improved workforce management and error reduction

📌 7. Higher product quality and elimination of production defects

📌 8. Complete traceability and tracking of production processes

📌 9. Increased efficiency, productivity, and optimization of production resources and costs

📌 10. Readiness for Industry 4.0 and future innovations

Why Choose IoT/IIoT Implementation with IoT Industries?

10 Reasons Why Implementing SCADA and MES Systems is the Key to Your Business Success (Part 1)

4. March 2025

by Karin Kramara Industrial IoT SCADA/MES

SCADA and MES systems are key pillars of modern manufacturing companies striving to optimize production processes, increase efficiency, and minimize costs. Despite their advantages, many businesses still rely on outdated manual processes, paper-based records, and inaccurate estimates. To enhance competitiveness and adapt to changing market demands, implementing SCADA and MES is no longer just an option. It is a necessity.

Challenges Faced by Companies Without SCADA and MES

❌ Lack of Transparency in Production Processes

The biggest challenge in such companies is the lack of transparency in production. Without a comprehensive system for monitoring and managing manufacturing, efficiency is often estimated based on manual records, Excel spreadsheets, or inaccurate reports.

However, these data do not reflect the real situation. When companies try to optimize costs or increase production, they lack clear data to pinpoint bottlenecks and identify where the biggest time or financial losses occur.

❌ Inefficient Reporting and Production Tracking

One of the main consequences of a lack of transparency is inefficient reporting. Many companies struggle with slow and inaccurate reporting. Obtaining the necessary data can take days or even weeks. By the time management receives reports, they are often outdated and do not reflect the current state of production. In many cases, reports are distorted or embellished because data is collected manually, making accuracy dependent on subjective reporting from employees.

This issue is particularly evident in tracking work-in-progress. At the end of the month, an ERP system like SAP might record a lower number of produced units than planned. However, the company may struggle to quickly determine whether the products have been manufactured or are still in production. This leads to delays, inefficient planning, and difficulties in meeting deadlines.

A similar issue arises in production planning. If a production plan changes, many companies still rely on printed documents. These must be physically distributed to workers on the shop floor, and changes must be explained in person. This results in unnecessary delays and the risk that some employees may miss critical updates.

❌ Material Tracking and Inventory Management Issues

Another significant challenge is material tracking and inventory management. In many cases, production teams realize they are out of materials only when workers on the production line run out. When an operator reports a material shortage, it often takes hours to resolve the issue. The material must be manually picked from storage, checked, transported to the right location, and prepared for further processing. During this time, production slows down or completely stops, causing downtime and disrupting delivery schedules.

The absence of a digital system also affects the accuracy of material usage. There is no mechanism to ensure that workers use the correct material in the required quantity. Without automated verification, operators may use incorrect components or incorrect dosing, leading to defective products or even damage to machinery.

❌ Delayed Fault Detection and Reactive Maintenance

In large and complex manufacturing facilities, it is impossible to have everything physically monitored at all times. Production often relies on workers noticing a malfunction and contacting maintenance, leading to time losses and unplanned downtime.

Without proactive monitoring, companies cannot detect warning signs before a failure occurs. For example, an increase in oil temperature in a machine may indicate an impending issue. However, if there is no monitoring system in place, maintenance only reacts when an actual failure happens. This approach, known as reactive maintenance, means problems are only addressed after they have already caused disruptions.

Additionally, when a failure occurs, the root cause is often unclear. There are no historical records indicating which parameters were out of range, what actions preceded the failure, and what interventions operators attempted. As a result, companies simply “extinguish the fire” and hope the issue does not recur, rather than preventing it proactively.

❌ Limited Remote Control of Production

Without a SCADA system, controlling production equipment is only possible locally. Operators must be physically present at the machines to make adjustments. If an error occurs or a process is configured incorrectly, there is no way to address the issue remotely, leading to extended response times and costly consequences.

For instance, if a worker misconfigures the routing of a manufactured product, employees must manually transfer materials to the correct location. This causes delays and disrupts production planning. Moreover, many local control panels do not require operator authentication, meaning that if an error occurs, there is no way to trace who was responsible. This lack of accountability prevents targeted prevention measures such as training.

❌ Limitations in Workforce Management

Many companies aim to optimize labor costs, but without accurate data, this becomes extremely challenging. Without an MES system, it is impossible to track individual worker efficiency, evaluate performance, and analyze how much time is spent on specific operations. In most companies, productivity is measured only at the team or department level, making it difficult to identify areas for optimization.

HR records may indicate which employees are trained to operate specific machines, but production equipment itself does not use this information. This means that an unqualified worker may access and operate machinery, increasing the risk of production errors, lowering product quality, and, in the worst cases, leading to workplace accidents.

❌ Lack of Traceability in Production Information

Another critical issue is the lack of traceability in production records. If a product defect is discovered, companies often struggle to determine which other products may have the same issue. There are no detailed records of when the product was manufactured, which machine was used, what settings were applied, or what materials were used.

For example, if a production deviation occurs on a specific machine, the company cannot simply recall the affected batch of 1,500 units. Instead, they must recall all 10,000 products made during the same period as a precaution. This results in significant financial losses and unnecessary waste.

❌ Limitations in Energy Management

Companies may have ambitious plans to implement an Energy Management System (EMS) to monitor energy consumption and reduce operating costs. However, even if energy meters are installed on all machines, their effectiveness is limited without centralized data collection and visualization.

If a company cannot track and analyze this data in real time, the only option is manual regulation—employees would have to physically check and turn off machines that are not in use, which is inefficient and impractical. Energy savings are not just about data collection but also about real-time response and automated interventions, which are impossible without SCADA and MES.

❌ Inability to Implement Advanced Technologies

Without comprehensive data collection and production monitoring, adopting advanced technologies such as artificial intelligence and predictive maintenance is unrealistic.

SCADA and MES systems provide the foundation necessary for expanding production monitoring. For example, predictive maintenance relies on machine learning algorithms to analyze machine vibrations and detect anomalies early. However, this approach is ineffective if the company lacks a basic system to monitor key parameters such as temperature, pressure, and speed.

SCADA and MES as a Solution to Manufacturing Challenges

In this part of the article, we explored the biggest challenges that slow down manufacturing companies and lead to unnecessary costs. In the second part, we will look at specific solutions and show how SCADA and MES systems help optimize production management and reduce losses.

Why Choose IoT/IIoT Implementation with IoT Industries?

Turn Data into Profit – Microsoft Power BI Transforms Decision-Making in Manufacturing Businesses

26. February 2025

by Karin Kramara Industrial IoT Reporting and Business Intelligence

In today’s world, managing a company based solely on intuition and experience is no longer enough. Truly successful businesses rely on accurate data that enables them to make quick and informed decisions. However, many manufacturing companies still struggle with manual data collection, delayed and inaccurate reports, and inefficient processes. This costs them money, customers, and a competitive edge. But what if you could have all the essential information visually clear, up-to-date, and accessible with just a few clicks? That’s exactly what Business Intelligence (BI) offers, along with one of the most powerful tools on the market – Microsoft Power BI.

What Are the Most Common Problems Faced by Companies Without Modern Business Intelligence Tools Like Microsoft Power BI?

In most manufacturing companies, data is still collected manually. Workers record information on paper forms, which are then transcribed into spreadsheets at the end of the shift. Reports are generated daily or weekly from these spreadsheets, meaning management receives them with significant delays. Not only can such data be inaccurate or distorted, but if production issues arise, management learns about them too late to take timely action.

Without a unified data source, different departments often have conflicting views on the actual state of production. Sales teams might sell more than production can deliver, or the production team might overproduce, leading to excess inventory that ties up capital and remains unsold. There is no Single Source of Truth (SSOT) to consolidate all data into one system and eliminate inconsistencies between departments.

How Can MS Power BI Solve These Problems?

Power BI is Microsoft’s Business Intelligence tool that transforms raw data into clear, real-time insights and visualizations.

Unlike outdated manual methods, Microsoft Power BI collects, analyzes, and visualizes data automatically. By integrating with other systems such as ERP, SCADA, and MES, company leaders can monitor production performance, order status, and financial indicators at any time without waiting for manual reports. In case of production issues, managers gain instant insight into what happened.

MS Power BI also unifies data from various departments into a single central information source (SSOT). This ensures that everyone works with the same accurate data.

Why Power BI Alone Is Not Enough

Microsoft Power BI is a powerful tool, but the quality of its outputs depends on the quality of the input data. If data is incomplete, inaccurate, or delayed, even the best BI tool cannot enable effective decision-making. That’s why having a well-structured data collection and management system is crucial. This is where systems like SCADA and MES come into play, ensuring the automatic collection of precise data directly from production lines.

Comprehensive Custom Solution from IoT Industries

For Business Intelligence to deliver the desired results, it is essential to connect the right tools with high-quality data sources. IoT Industries offers a comprehensive solution. From setting up data flows and integrating Microsoft Power BI with MES and SCADA systems to creating custom interactive dashboards. The result is a system that provides accurate and up-to-date information necessary for efficient production management.

If you want to take your business decision-making to the next level, contact us. Discover how Power BI, combined with intelligent data collection, can transform your operations!

Why Choose IoT/IIoT Implementation with IoT Industries?

BAS (Building Automation System) can solve the most common building management challenges

25. February 2025

by Karin Kramara Building and Data Center Monitoring Industrial IoT

Efficient building management is crucial for companies not only in terms of costs but also in productivity, safety, and sustainability. Despite this, many businesses still operate without a centralized system to optimize their building operations. The result is high energy costs, frequent technical issues, and inefficient management of various systems. However, BAS (Building Automation System) can provide a solution.

BAS is a system that centrally manages all key processes in a building, from lighting and heating to security and fire protection systems. It not only optimizes energy consumption but also helps prevent failures, enhances workplace comfort, and simplifies managerial decision-making.

Common Challenges in Building Management That Companies Face

❌ Uncontrolled Energy Consumption and High Operating Costs

Companies often receive only a summary energy bill without a detailed breakdown of where exactly consumption occurs and where waste happens. Lights stay on when not needed, production halls are fully heated even on weekends, and air conditioning may be set to inefficient temperatures. Without automation, these losses cannot be effectively identified and eliminated.

❌ Manual Management and Resulting Time Losses

Without intelligent automation, employees must manually adjust lighting, temperature, or ventilation in different areas of the building. This leads to inefficiencies, time losses, and frequent errors. In case of malfunctions or unexpected situations, the response time is too long, and the costs of problem resolution unnecessarily increase.

❌ Lack of Integration Between Systems

In most companies, lighting, HVAC, security, and heating systems operate separately without communication between them. When managers need a comprehensive overview of the building’s status, they must monitor multiple systems and applications, which slows decision-making and reduces operational efficiency.

❌ Inability to Meet Environmental and Regulatory Standards

With increasing ESG (Environmental, Social, Governance) requirements and new legislation on carbon footprint reduction, businesses face mounting pressure. Without accurate data on energy consumption and CO₂ emissions, it is difficult to meet required standards, potentially leading to financial penalties and a loss of competitiveness.

How BAS (Building Automation System) Solves These Problems

✅ Optimized Energy Consumption and Lower Operating Costs

The Building Automation System (BAS) monitors energy consumption in real time and automatically adjusts settings to eliminate waste. It can reduce heating in unoccupied areas, turn off lights in empty rooms, or adjust air conditioning based on outdoor temperature. The result is significant energy savings.

✅ Automation and Intelligent Management

Instead of manual adjustments, BAS ensures automated control of all systems based on sensors and predefined rules. Heating, ventilation, and lighting automatically adapt to the current building conditions without requiring employee intervention.

✅ Integration of All Systems into a Single Platform

BAS integrates all key building systems—lighting, heating, air conditioning, ventilation, security, and fire protection—into one platform. Managers gain a complete overview of the building’s status in a single interface, eliminating the need to switch between multiple applications. This enables faster and more accurate decision-making based on real-time data.

✅ Compliance with Environmental and Regulatory Requirements

BAS helps businesses monitor and optimize their energy consumption and emissions, making it easier to comply with ESG standards and legal regulations. Automated reporting simplifies the auditing process and ensures compliance with environmental requirements.

IoT Industries – Your Partner for BAS Implementation

Implementing a Building Automation System (BAS) requires expertise, the right technology selection, and customization to fit a company’s specific needs. At IoT Industries, we provide tailor-made solutions that include analysis, design, implementation, and long-term optimization of BAS systems. If you want to reduce costs, increase efficiency, and gain maximum control over your building management, contact us today to learn how BAS can help you achieve your goals.

Why Choose IoT/IIoT Implementation with IoT Industries?

How to Reduce Overhead Costs in Manufacturing with Digital Transformation?

24. February 2025

by Karin Kramara Industrial IoT SCADA/MES

Overhead costs make up a significant portion of manufacturing expenses, yet many companies fail to give them sufficient attention. While direct production costs, such as material expenses and wages, are easily measurable, overhead costs often remain hidden in excessive energy consumption, unnecessary downtime, and inefficient processes. The result is higher expenses, lower productivity, and reduced competitiveness.

With modern digital solutions like SCADA (Supervisory Control and Data Acquisition), MES (Manufacturing Execution System), EMS (Energy Management System), and BMS (Building Management System), companies can not only accurately identify sources of unnecessary overhead costs but also significantly reduce them.

What Are Overhead Costs in Manufacturing?

Overhead costs include all expenses that are not directly linked to producing a specific product but still impact the entire manufacturing process. These typically include:

Energy costs – electricity, gas, water, cooling, heating
Maintenance and repairs – unplanned downtime, machine failures, service interventions
Inefficient production planning – downtime, material waste, underutilized workforce

Many companies accept these expenses as an unavoidable part of manufacturing. However, the truth is that modern technologies can significantly optimize them.

What Are the Most Common Issues That Increase Overhead Costs?

❌ High Energy Consumption and Inefficient Operational Costs

Manufacturers often lack a detailed overview of which machines consume the most energy and where waste occurs. It is common for machines to remain powered even when idle, heating and lighting to run in unused spaces, and production cycles to be poorly optimized for energy efficiency. As a result, energy expenses continue to rise.

❌ Inefficient Maintenance and Frequent Downtime

Many companies still rely on reactive maintenance — fixing machines only after they break down. This leads to unplanned downtime, delays, and increased costs for urgent repairs. A more effective approach is implementing digital planned maintenance and condition-based maintenance, which monitors key parameters such as oil temperature or bearing vibrations, allowing companies to address issues before they result in breakdowns. Once these levels are established, businesses can advance to predictive maintenance using advanced data analysis.

❌ Poor Planning and Underutilized Production Capacity

Lack of accurate data results in inefficient production planning. Machines operate with low efficiency, employees wait for materials, and inventory levels spiral out of control. Poor planning also means that production is not flexible enough to quickly respond to shifts in demand.

How Can Digital Transformation Reduce Overhead Costs?

✅ Optimizing Energy Consumption with EMS and BMS

An Energy Management System (EMS) provides companies with real-time insights into energy consumption across different production areas. A Building Management System (BMS) uses this data to automate energy regulation, shut down unnecessary machines, and optimize production cycles to significantly reduce energy costs.

✅ Immediate Failure Response and Smart Maintenance with SCADA and MES

Supervisory Control and Data Acquisition (SCADA) continuously monitors production equipment and allows for immediate responses to malfunctions through remote control. It also provides essential data for optimizing maintenance strategies—whether planned, condition-based, or predictive. Manufacturing Execution System (MES) further integrates this data into the broader production context.

✅ More Efficient Production Planning with MES

MES connects ERP systems with real-time production data, improving the efficiency of manufacturing operations. This reduces downtime, enhances workforce utilization, and optimizes material inventory, leading to significant cost savings.

Overhead Costs – Example of Savings Calculation

A company that pays €30,000 per month for electricity can reduce consumption by 15–20% using EMS and BMS, resulting in annual savings of up to €72,000. Similar savings can be achieved in maintenance, logistics, and overall production process optimization.

The Key to Successful IoT/IIoT Implementation

Many companies struggle with where to start when optimizing their overhead costs. The solution lies in a detailed analysis of manufacturing processes and the implementation of intelligent control systems. At IoT Industries, we offer tailored solutions – from cost analysis and the implementation of MES, SCADA, EMS, and BMS systems to long-term support and production optimization. Contact us to find out how you can reduce your overhead costs.

Why Choose IoT/IIoT Implementation with IoT Industries?

The Most Common Pitfalls of IoT/IIoT Implementation and How to Avoid Them

24. January 2025

by Matej Medvecký Industrial IoT

In today’s world, where digital transformation is a necessary prerequisite for maintaining competitiveness, IoT (Internet of Things) and IIoT (Industrial Internet of Things) play a key role. These technologies enable businesses to collect, analyze, and utilize data to optimize processes, reduce costs, and improve efficiency.

However, the implementation of IoT/IIoT also brings certain challenges. If approached without a systematic plan, complications may arise that impact not only the progress of the project but also the long-term return on investment. In this article, we will outline the most common pitfalls that companies face before, during, and after implementing IoT/IIoT, and we will also provide specific steps on how to effectively avoid them.

Why Does IoT/IIoT Implementation Often Become Complicated?

Complications Before Implementation

One of the biggest challenges is the lack of clearly defined goals and expectations at the start of the project. Many businesses know they want to leverage IoT to optimize processes, but they lack answers to key questions:

Why do we actually need IoT?
What problem are we trying to solve?
What specific outcome do we expect?

Businesses often perceive IoT as a goal in itself rather than a tool to achieve specific, measurable results. This misguided approach can ultimately lead to the project failing to deliver the expected benefits.

Complications During Implementation

Issues with Network Infrastructure

IoT projects heavily depend on reliable network infrastructure, which, however, is not a given in every location. While some areas have access to a robust corporate Wi-Fi network, others – such as remote locations or production halls with a large amount of metal structures – may face significant issues with connection stability.

In such cases, it is essential to use alternative solutions, such as:

Ethernet (wired connection) – ideal for locations where a stable network infrastructure with high speed and data transmission stability can be ensured,
GSM/Mobile networks – used for data transmission in areas without fixed connections,
LPWAN (Low-Power, Wide-Area Network) – low-energy technologies for long-distance data transmission, used in areas with limited coverage, including LoRaWAN, SigFox, or NB-IoT.

Although these solutions can address connectivity issues, they add to the overall complexity of the project – requiring specific hardware, and their implementation may increase costs.

IT Security and Approval Processes

Another common complication is the concerns of IT departments regarding the security of company networks. These concerns are understandable—protecting the corporate network is a top priority for any IT department. The most common requirements include:

Data encryption – ensuring that the data transmitted between devices and systems is protected,
Certification from trusted manufacturers – guaranteeing the quality and security of devices,
Data localization – some companies do not want their data to leave their internal servers.

Although these requirements are justified, the approval process can take weeks or even months, especially in large companies with complex internal processes.

A reliable IoT solutions provider should, however, consider these aspects from the early stages of the project. Our task is to ensure the selection of devices that meet security standards and to work closely with the IT department to expedite the process. A pilot project (Proof of Concept – PoC) is an ideal tool in this regard to verify the technical and security design before full implementation.

Complications After Implementation

After the successful implementation of IoT/IIoT solutions, the phase that determines the long-term success of the entire project begins – its daily use. Although modern IoT systems are designed with an emphasis on simplicity and intuitive user interfaces, effective utilization requires proper employee training. It is also crucial to ensure their long-term functionality through regular monitoring, verifying the accuracy of measured data, maintaining certain devices, and updating firmware.

How to Prevent These Issues?

1. Clarifying Goals and Expectations

IoT/IIoT implementation should begin by answering three fundamental questions:

What exactly do we want to achieve?
- Do we need to refine energy measurement to optimize consumption?
- Do we want to measure OEE (Overall Equipment Effectiveness) of machines that are currently not networked?
- Are we interested in predictive maintenance using artificial intelligence to prevent failures and reduce downtime?
What technologies and processes will we use to achieve the goals?
- This is primarily the responsibility of the supplier, who must design suitable devices, software solutions, and infrastructure to ensure the system works smoothly and reliably.
Why are we doing this? What results do we expect?
- Do we want to reduce energy costs?
- Increase the efficiency of machines and employees?

In this step, the supplier should help the customer clearly formulate their expectations. If the customer does not have specific expectations defined, it is necessary to work together to develop and fully understand them. For both the supplier and the customer, this is a crucial step – not only in terms of evaluating benefits but also for the design and development of the application itself.

2. Initial Audit and Solution Design

Every project should begin with a thorough analysis that includes:

Identification of devices to be connected to IoT/IIoT,
Network availability check, or the design of alternative solutions,
Selection of suitable hardware, which may include IoT modules (e.g., Advantech Wise), gateways (Ewon Flexy), and industrial PLCs (Siemens, Omron, Allen-Bradley, and others),
Definition of the types of data to be collected, their usage, and presentation in the IoT system.
We use the proven and modern Ignition platform, which not only enables data collection and visualization but also allows for easy expansion with additional functionalities, such as SCADA, MES, EMS, BMS, and many other systems for managing and monitoring operations.

3. Pilot Project (Proof of Concept – PoC)

A pilot project allows for verifying the functionality of the solution on a smaller sample of devices or processes. It should include:

Connecting several production machines
Testing the network
Verifying data quality
Evaluating the initial results

This step minimizes the risk of issues and allows for identifying weak points before scaling the project to the entire operation.

4. Training and Long-Term Maintenance

The implementation of IoT/IIoT does not end with the deployment of the system. Following these next steps ensures that the systems will operate reliably and securely in the long term:

Employee Training: Thorough training on how to use the system, along with ongoing training when new features are introduced, ensures that the entire system will be used effectively.
Regular Monitoring: Monitoring whether all IoT devices are online and fully functional will be ensured by the Ignition platform. It includes a clear network monitoring overview via a web dashboard and email notifications that alert to any outages or unusual activity.
Occasional Data Accuracy Check: After a power outage or signal issues, measurement interruptions may occur. Once the system is restored, it may be necessary to compare the measured data from the devices with the data stored in the system to avoid discrepancies.
Device Maintenance: Devices with their own power supply, such as sensors using LPWAN technologies, may require battery replacement every few years, depending on the data transmission frequency.
Firmware Updates: Device manufacturers regularly release firmware updates that improve cybersecurity, increase reliability, and often introduce new features. Implementing these updates ensures that the system operates at peak efficiency and security in the long term.

Key to Successful IoT/IIoT Implementation

Implementing IoT/IIoT is not just about technology – it’s about proper planning, collaboration, and a long-term vision. Companies that implement these solutions with clearly defined goals and an experienced partner can achieve significant improvements in efficiency, cost reduction, and increased competitiveness. IoT Industries is ready to be your partner on this journey – from initial analysis to long-term support and solution expansion. If you want to take your business to the next level, don’t hesitate to contact us.