DATABERG
Types of industrial data services you need to know about in 2020
“The global industry 4.0 market was valued at around USD 66.10 billion in 2017 and is expected to reach approximately USD 155.30 billion by 2024, growing at a CAGR of slightly above 14.9% between 2018 and 2024.”
This is the forecast of Zion Market Research, which emphasizes on the enhanced importance of the creation of smart factories and the use of industrial data services to support the success of those.
But why do we need such services?
Well, they play a key role in supporting the management of information and making the best possible use of the data, which is generated within the industrial plant: they transform data from complex and senseless resources into a valuable corporate development tool.
What is more, industrial data services help us to:
- Understand the supply chain of our operations better
- Gain an overview of the details of every task
- Have control over every process and framework within the supply chain
- Be able to constantly monitor assets, human and machine capital
- Quickly interfere if any issue arises
- Understand customers, partners, stakeholders, and internal processes and relationships
- Forecast demand and plan supply
- Generate added value
- Achieve a competitive advantage
There are many types of industrial data that third party companies provide services on. However, just a few of those are becoming essential trends, which drive business success and become an irreplaceable part of every smart factory.
Let’s take a closer look at them.
Asset monitoring and predictive maintenance
Those services use two types of industrial data to drive organizational value: Sensor data and Asset Metadata.
Sensor data
This type of data gives information about utility meter, location, speed, temperature, PIR, ultrasonic, and other sensors used in the manufacturing plant.
It provides better control over the machine capital of the business entity. What is more, the integration and analytics of these data give the organization the opportunity to maintain a constant monitoring process and interfere immediately if any problem occurs.
This way, the sensor data facilitates the prevention of any asset issues, and as a result, avoids operational delays, errors, and lags.
These data are derived mainly from industrial protocols, IoT protocols, and various databases used in the management of the smart factory.
Asset metadata
These data give detailed information about the essence of the industrial machine capital, such as hardware models, serial numbers, vendors, configuration, etc.
By keeping track of these data, the industrial organizations are enabled to do quick updating, referencing, fast configuration, parts replacement, and repair of machinery. Besides, the information that the companies gain facilitates them to set up complex machine configurations and keep track of the functionalities in order to benefit from maximum productivity.
The business welfares that industrial plants can take advantage of, in terms of the asset metadata, are related to a number of key operational performance factors:
- Reduced costs (for set up, repair, and replacement)
- Optimized working capacity (balancing the pace of amortization)
- Increased productivity (to drive the total output up. Together with the reduced costs, the industrial plants have the potential to achieve economies of scale)
- Slower depreciation of assets ( which has a positive effect on the financial statements by reducing incurred amortization expenses)
The asset metadata sources are usually derived form ERP and EAM systems, various databases, and device management platforms.
Industrial Control Systems (ICS) monitoring and Operational Technology (OT) security
These services provide smart factories with alerts on issues, events, changes, and updates regarding the systems used in day-to-day operations, such as operating, firewall intrusion systems, databases and communication logs, system performance data, and others.
Keeping control over those systems allows the companies to maintain their “health” by sustaining their proper functionalities, avoid any lags and delays, prevent security issues, and other performance-related problems. This contributes to enhanced productivity, better task efficiency, and improved data management processes.
What is more, maintaining high-quality communication between frameworks, keeping track of the system logs, and access attempts in the servers and systems support the creation of robust security of data assets.
In fact, according to research done by Splunk, “one company was able to increase operational and security visibility and reduce security investigations from 12 hours to one” by only using ICS monitoring and OT security data services.
Connected product monitoring and analytics
Those industrial data services alert the business entities on communication problems between appliances, devices, and other tangible assets, used in operations.
As a result, the manufacturing plants are enabled to conduct remote health measurements of machine capital and other appliances and evaluate the efficiency of communication and data flow between the different devices.
This provides industrial companies with plenty of competitive advantages, such as decreasing the time for problem-solving, better real-time decision-making process, and immediate risk evaluation.
The connected product monitoring and analytics services use networks and sensors data, as well as data derived from devices, communication logs, and other primary machine sources.
Conclusion
Smart factories are based on data. Therefore, using relevant and efficient industrial data services is key for their long-term performance and success.
The three services mentioned in this article are selected as the ones that are a MUST for every organization operating in the Industry 4.0, in order to benefit truly from the data it generates and make the most of it.