Matt Barber
Factories have always needed a way to know what's being made, and whether it's right. The tools have changed enormously, from clipboards to cloud platforms. The underlying need hasn't.
This article traces how manufacturing systems evolved into MES and MOM, and what that history suggests about what comes next.
Before computers: skill and paper
In the early days of industrial manufacturing, production depended on the skill of individual workers. Coordination happened through supervisors and paper records.
Data was collected by hand and analysed after the event, if at all. Problems were dealt with as they arose rather than prevented. Quality relied mainly on visual inspection and the judgement of experienced people.
It worked, but it limited how much a factory could produce and how consistently it could produce it.
Control systems arrive
The programmable logic controller (PLC) changed that. It was invented in 1968 and first used by General Motors in 1969, replacing banks of hard-wired relays with a computer that could be reprogrammed.
Automation spread quickly. Supervisory control and data acquisition (SCADA) systems followed, letting engineers monitor and adjust equipment from a central screen. Process plants adopted distributed control systems (DCS). These control systems are still the foundation of every modern factory. More in PLC vs SCADA vs DCS vs MES.
Planning moves onto computers
On the business side, material requirements planning (MRP) emerged in the 1960s to work out what to make and buy, and when. It grew into MRP II, then into ERP, which brought finance and planning onto one set of data. More in ERP vs MRP vs MES.
That left a gap between the plan in ERP and the machines on the floor.
Departmental systems fill the gap
Each department filled its part of that gap with its own system. Quality teams bought quality management or laboratory systems, and maintenance teams bought maintenance management systems.
Each system solved one department's problem. Few of them shared data with each other.
MES brings it together
The term MES emerged in the early 1990s to describe systems that managed execution on the shopfloor, between ERP and the control layer. MESA International, founded in 1992, published its eleven-function model of MES in 1997. More in MESA's MES models, and what ISA taking over means.
In 2000, the first part of ISA-95 standardised how business systems and manufacturing operations fit together, and defined four areas of manufacturing operations: production, quality, inventory and maintenance. More in The ISA-95 model explained.
As platforms grew to cover all four areas, the term MOM, manufacturing operations management, came into use. MES/MOM captures data at a much more detailed level than ERP, as a by-product of managing the work. More in MES vs MOM.
Connected, data-driven manufacturing
Since the 2010s, Industry 4.0 has pushed manufacturers towards connected equipment and analytics. Modern MES/MOM platforms connect to IIoT devices and data platforms, and increasingly build AI into the tools operators and engineers use every day. More in Industry 4.0 vs Industry 5.0.
Demand for MES/MOM has grown with that shift, yet many manufacturers, especially smaller ones, still run on paper and spreadsheets. More in The MES/MOM market.
The timeline at a glance
| Period | What changed | What it meant on the shopfloor |
|---|---|---|
| Before the 1960s | Manual work, paper records | Quality and coordination depended on people |
| 1960s to 1970s | PLCs, early MRP | Machines automated; planning moved onto computers |
| 1980s | SCADA and MRP II | Equipment supervised centrally; planning broadened |
| 1990s | ERP and the first MES | Business data unified; shopfloor data still split by department |
| 2000s | ISA-95 and the rise of MOM | A standard model for operations; broader platforms |
| 2010s onwards | Industry 4.0, IIoT, cloud, AI | Connected equipment and data-driven operations |
What history suggests about what's next
Each step built on the one before. Control systems made automation possible, and MES/MOM later brought shopfloor data together with its context.
AI is the next step, with one difference: it doesn't have to wait its turn. Models that predict and optimise operations learn from reliable, contextualised data, and they're one of the strongest reasons to build it. Most factories today sit somewhere between paper-based and partly digital, so from here the data foundation and the AI grow together. The stages are described in Time to truth, and where AI fits in AI will transform your factory, if you give it the right data
My view
The history of MES is a story of scope growing, from recording production to running the whole operation as MOM. It also shows that each step builds on the data the last one created. AI builds on that data too, and gives every factory a new reason to capture it well. I expect the two to grow together.
Where does your factory sit on that timeline today?
