In many factories, production is still written on paper forms and typed into a spreadsheet at the end of the shift. How many minutes a machine stood idle, how much energy it drew at a given hour, where the scrap rate spiked — most of it surfaces the next day, and only after being copied by hand. The problem is plain: manually collected data arrives late, stays incomplete, and delays the decision.
Pulling data directly and automatically from machines changes that picture. This guide explains what machine-to-machine communication (M2M) and the Internet of Things (IoT) are, which protocols they run on, how to start with a single line, and which incentives can fund the investment.
Why is machine data hard to collect?
Equipment on a production floor is never uniform. Two machines standing side by side may come from different years, different brands, different control units. One may push data out through a modern PLC; another only shows it on a screen; a third offers no digital output at all.
This mix makes “let’s connect the machine to the internet” harder than it sounds. Three obstacles dominate in practice:
- Different languages: Each brand uses its own data format and protocol; without a shared vocabulary, the data never lines up.
- Legacy equipment: Machines without a digital output need an external sensor or meter to be read at all.
- Shop-floor conditions: Dust, vibration, heat and an unstable network are far more demanding than an office setting.
These can be overcome — with the right architecture. That is where M2M and IoT come in.
What do M2M and IoT mean, and how do they differ?
M2M (machine-to-machine communication) is two devices exchanging data without human intervention. A meter talking directly to a data collector is a classic M2M example. It is usually a point-to-point connection built for a specific purpose.
IoT (the Internet of Things) is the broader version of that idea: many devices, sensors and machines connect to a network, data flows to a central platform, and there it is processed, visualised and analysed. M2M is typically the lower layer of IoT; IoT turns the data it gathers into a decision system.
Put simply: M2M makes machines talk, IoT turns that conversation into a meaningful whole. In manufacturing, the two are used together.
Which protocol: OPC UA or MQTT?
When you start collecting machine data, the two standards you will meet most often are OPC UA and MQTT. They are not rivals — more often they complement each other.
| OPC UA | MQTT | |
|---|---|---|
| Developed by | OPC Foundation | Designed in 1999, open standard |
| Architecture | Client/server | Publish/subscribe |
| Strength | Structured, meaningful data (variables, alarms, relationships) | Lightweight, low bandwidth, many subscribers |
| Typical use | Secure data acquisition from field devices and PLCs | Moving data to the cloud and analytics layer |
OPC UA is the industrial automation standard that lets machines from different vendors speak a common language; it does not just carry data, it also describes what each value means (Source: OPC Foundation). MQTT is a lightweight messaging protocol built for constrained devices and unreliable networks; it delivers data to many subscribers with minimal resources.
A common setup has OPC UA collecting structured data from the field PLC, while MQTT carries that data northbound to a cloud platform or a predictive-maintenance model. Which protocol belongs where depends on your line and your goal — which makes it a design decision from the very start.
How to start with a single line
Trying to connect the whole factory at once is the most common mistake. A spark pilot is far healthier:
- Pick one line, a few machines. Start with the most critical or most frequently stopped equipment; that is where the payback shows fastest.
- Decide what you are measuring. Downtime? Energy use? Output count? Scrap? Without a target, the data you gather is waste.
- Identify the data output. Does the machine’s PLC expose data, or do you need to add a sensor or meter? This is where the connection protocol is chosen.
- Collect data in one place. Field data should pass through an IoT gateway to a central platform, and from there into an ERP or production-tracking system.
- Read first, automate later. Just monitor for the first few weeks; once the data is reliable, add alarms, reports and process automation.
If the pilot works, you replicate the same pattern on other lines. The risk stays small, the learning stays fast.
What is the collected data good for?
Machine data on its own is not a pile of tables; set up correctly, it turns into a few concrete gains:
- Real-time production tracking: You see stoppages, bottlenecks and throughput without waiting for the shift to end. This is the basis for measuring overall equipment effectiveness (OEE).
- Predictive maintenance: Deviations in vibration, temperature or current data can warn you before a failure occurs, cutting unplanned downtime.
- Energy and carbon measurement: Machine-level energy data lays the groundwork both for lowering cost and for calculating your carbon footprint. The data your customers ask for under CBAM and CSRD begins exactly here.
That last point matters: digital and green transition feed off the same data. The energy data you collect from a machine serves both production efficiency and the emissions report. Building the measurement layer once serves both agendas at the same time.
Do incentives cover this investment?
Short answer: largely yes. Under Türkiye’s KOSGEB SME Digital Transformation Support Programme, hardware such as sensors, network devices and servers, along with software such as ERP, production-tracking systems (MES) and data-analytics tools, are among the items that can be supported (Source: kosgeb.gov.tr).
One condition of the programme is a digital-maturity assessment from a certified consultant; this report shows where the business stands and which investment should be prioritised. Because eligibility criteria, upper limits and application calendars are updated periodically, confirm the current terms before applying — via kosgeb.gov.tr or an authorised consultant.
A machine-data collection project is exactly the kind of investment these programmes want to fund: measurable, reportable, and tied directly to production efficiency.
How İkiz Eksen approaches it
İkiz Eksen starts by measuring the data on the floor: it collects production and energy data through machine communication, sensors and IoT. It then turns that data into value on the digital transition side with ERP, production tracking and process automation, and builds CBAM/CSRD-ready reporting on the green transition side. Running on Microsoft Azure, with the ERP depth of the Qera ecosystem, it delivers projects turn-key across Türkiye.
We can work out together which line and which data to start with. Take a look at our solution focuses or get in touch — let’s talk through your shop floor.
Frequently Asked Questions
What is the difference between M2M and IoT?
M2M is a direct data exchange between two devices without human intervention, usually a point-to-point connection built for a specific purpose. IoT is the broader structure that connects many devices to a central platform over a network and processes and analyses the data. M2M is often the lower layer of IoT.
Can I collect data from old machines too?
Yes. Equipment without a digital output can be read by adding an external sensor, meter or signal reader. This takes more field work than a modern PLC, but it is a common approach.
Should I use OPC UA or MQTT?
In most installations the two are used together: OPC UA collects structured data from the field device, MQTT carries it to the cloud or analytics layer. The right choice depends on your line, your machines and your goal, and should be treated as an architecture decision from the start.
How does machine-data collection connect to carbon reporting?
Machine-level energy data is the most reliable input for a carbon footprint calculation (Scope 1-2). Building the measurement layer once feeds both production efficiency and the emissions report required under CBAM and CSRD.
Can I fund this investment with incentives?
Under the KOSGEB SME Digital Transformation Support Programme, items such as sensors, network devices and data-analytics/MES tools can be supported. Confirm the current terms and limits at kosgeb.gov.tr before applying.