Manufacturing Execution System (MES) has been around since the late 90’s. However, it is only recently that companies have started adopting it to improve manufacturing efficiency. Now, the backbone of Industry 4.0, the global MES market size is projected to grow from $16.57 billion in 2025 to $41.78 billion by 2032.
So, what’s the reason behind the uptick in MES adoption?
The answer is simple – it’s data!
The modern MES helps manufacturers monitor, track, document, and control the entire manufacturing process from collecting raw materials to building finished goods.
Let’s just say it is a treasure trove of data. It comprises a large volume of data that enables manufacturers to improve the end-to-end manufacturing process.
With MES, manufacturers can:
- Track and monitor the production process: MES keeps a record of every step in the manufacturing process – from the raw materials used to the machines and the time required to manufacture the product. It links the final product with these manufacturing records. So, if there are any problems with a specific part of the product, the manager can trace back to the manufacturing process, see what’s happening on the factory floor, and take corrective actions. It brings transparency to the process and enhances manufacturing quality.
- Optimize material and resource management: Since MES maintains a record of all materials and resources used in production, manufacturers gain real-time visibility into available materials and resources, enabling them to make adjustments. This will help manufacturers reduce excess inventory, save costs, and optimize material and resource management.
- Improve operational efficiency: MES collects a large volume of data, enabling decision-makers to schedule equipment maintenance. Timely maintenance reduces unexpected downtime and helps manufacturers keep operations running smoothly.
As it’s clear by now, the success of MES hinges on data quality. Without high-quality data, no good MES can save the manufacturer’s business.
That’s why data discipline is crucial for MES’ efficiency. It’s the lesson our XYZ clients and we have learned in so many years.
So, what affects MES’ efficiency, and how can manufacturers instill data discipline? Let’s explore further to know more.
Factors Impacting MES’ Efficiency
The real power of an MES lies in its ability to collect and process data in real time as soon as it is generated. This data serves as the source of truth for manufacturers to monitor machine performance, production rates, inventory levels, and other quality indicators. This data helps manufacturers respond to issues before they escalate, optimize operations, and improve operational efficiency.
However, MES becomes redundant if it suffers from challenges such as:
- Data overload: While real-time data is essential, manufacturers can easily become overwhelmed by too much raw data. The continuous influx of data leaves little time for decision-makers to filter, analyze, or interpret the data. They would be left with inaccurate and inconsistent data, leading to decision paralysis or flawed decision-making. This impacts overall operations, including cash flows, sales, and demand forecasts. Without proper context or actionable insights, manufacturers would be left with an avalanche of underutilized data and missed business opportunities.
- Inconsistent data: For MES to aid decision-making, consistent data quality is essential. Without it, decision-makers cannot implement standardized improvements. They will be left to make guesswork decisions instead of data-driven ones. This could create a ripple effect. The production schedule would go haywire. There would be no proper planning for procuring raw materials, which would directly affect labor allocation. Unfortunately, most of the time, different facilities and operators generate inconsistent data. This makes data analysis and interpretation difficult. It creates friction at every stage of production, resulting in operational and compliance risks.
- Missing information: The primary role of MES is to provide decision-makers with real-time insights on the shop floor. Without complete data, the decision-makers would not have the full picture of the operations. The operators would not be able to identify bottlenecks or machine performance in real time. The managers would make decisions based on gut feeling. Missing data on quality inspection, temperature, or pressure readings could lead to product defects and costly product recalls. Missing information can also make traceability and root cause analysis difficult and time-consuming.
- Fragmented data sources: MES integrates with systems such as ERP to gather data, plan production schedules, manage inventory, and maintain production quality control. However, some legacy systems are not designed for modern integrations. This leads to data silos. The manufacturers are left with disconnected, unstandardized data that provides no real insights into operations or machines. Without access to real-time, unified data, employees have to spend time reconciling data across different systems. Decision-makers, too, are compelled to make decisions based on redundant or inaccurate data. This results in problems such as inefficient allocation of materials, labor, and equipment, and delayed decision-making.
To mitigate these issues and enhance MES’ efficiency, data discipline is necessary.
How Data Discipline Will Improve MES’ Efficiency
Data discipline is a set of practices and policies that can help manufacturers collect and manage accurate, complete, and reliable data. With data discipline, manufacturers can shift from operating on intuition to following a data-driven, evidence-based approach to decision-making.
Since an MES operates on the garbage-in, garbage-out principle, manufacturers need to ensure the system is fed with reliable, accurate data. That’s where data discipline comes into the picture.
With data discipline, manufacturers can feed on high-quality, real-time data. This will help them make more accurate decisions, improve quality control, predict potential equipment failures, and enhance traceability and compliance.
However, to maintain data discipline, manufacturers need to eliminate data silos and establish data governance.
With these steps, manufacturers can improve the quality and accuracy of data recorded by MES systems and maintain consistency. They will be able to optimize production schedules, allocate resources efficiently, and streamline operations.
Conclusion
Building insight-driven factories is not just about using modern systems and practices such as MES and data analytics. It is about controlling data quality from the moment it is collected and fed into the system. That’s why maintaining data discipline is crucial. Our experience shows that factories that embrace data discipline can make better data-driven decisions and improve their business outcomes.
Need help with improving data quality and governance? Contact us for more information.
FAQs
How does MES benefit the manufacturing industry?
MES records every step in the manufacturing process and provides real-time access to decision-makers. It helps manufacturers monitor the production process, manage materials and resources, and increase operational efficiency.
What happens when MES becomes inefficient?
When MES doesn’t receive real-time, high-quality data, manufacturers are left with inconsistent, missing, and fragmented data that impacts their decision-making and creates operational and compliance risks.
Why data discipline matters in building insight-driven factories?
By eliminating data silos and establishing governance, manufacturing can bring data discipline within its factories. With data discipline, decision-makers and operators will have access to high-quality, real-time data that will accelerate decision-making and improve manufacturing productivity and quality.
