The theory for IIoT: Smart machines work faster and more precisely, cheaper and more efficiently than humans – and they cooperate. However, standardization of the data is required for implementation.
The IIoT or Industrial Internet of Things offers many possibilities to optimize processes and procedures. This includes increasing flexibility, improving operational efficiency, reducing costs in production and logistics, more transparent and faster processes, as well as optimized value chains and new business models.
For many companies, growth, competitiveness and future viability depend on it. The focus of the IIoT is on data collected by sensors from the shop floor level, as well as data from various other systems from purchasing to warehousing and logistics to marketing and sales.
The implementation of an IIoT strategy is a complex undertaking in which three areas are essential: data collection, data integration, data evaluation. While data collection and data evaluation and the conclusions to be drawn from them are very specific for each company, the hub of the whole, the integration of data standardizes well today. For your IIoT strategy to work, the data integration should work as smoothly and inconspicuously as possible. The following checklist shows you what to look out for.
7 Points To Look Out For When Integrating Data
Good software for data integration impresses with its simple handling, for example with an intuitive user interface and drag and drop. Test: How many steps do you need for the entire integration process from one system to another? Also, pay attention to simple updates and version changes.
2. Overview and structure
Has the software a logical structure for you? Does the software offer clear documentation of the mappings – e.g. for exact tracking?
3. Speed / time savings
Compare: How fast are you in implementing interfaces? Can you set a direct mapping of source and destination, or does your system only offer the route via complex – and error-prone – intermediate points? Test the performance: How many data records does your system process in an emergency? And how much is this stressing your systems?
Submit Tool for all integration topics (EAI / IOT / EDI / ETL …), or do you have to use several systems? Is there central monitoring for all interfaces?
5. Comfort / Knowledge
Are – for your flexibility and future security – all industry standards included in the system (then you should be able to access almost 10,000 different templates)? Is it standard software or special solutions with high maintenance costs? Do you need special programming skills or is your process knowledge crucial for data integration?
Compare the price/performance ratio between standard software and stand-alone solutions, but also between different providers. Are there lengthy, phased development steps during implementation or can you save a lot of time by only requiring one test and one productive system? Do you receive free software updates/upgrades with a view to your planning security?
Are you independent of service providers (cost-time factor) and operating systems? How extensive are the hardware requirements?
Also Read : What Is The Internet Of Things (IoT)?