3 Data Integration Projects from the Process Industry

3 Data Integration Projects from the Process Industry

Data Integration is the cornerstone of digitalization. With the exploding volume of data every company possesses nowadays and its existence in different databases, serving specific needs in the organization is a constant challenge. Without unified data, creating a single report requires logging into multiple accounts, accessing data from native apps, reformatting and cleansing data — and that's before the analysis can start.  

Well-thought-out data integration can enhance process visibility, support the calculation of accurate KPIs and provide the backbone for advanced data analytics. Data integration encourages collaboration between internal and external users and makes the data more comprehensive. It uses technical and business processes to merge data from different sources. The goal is to gain access to valuable information efficiently. 

Here are three examples of successful data integration project implementations by IPCOS. 

End-to-end Process Visibility Using Data Virtualization 

In this project, the customer had multiple discrete MES applications and databases dedicated to different sections of the production system. It included multiple batch production units and continuous operations.   

The quality data was not properly integrated with the production data, and real-time synchronization was impossible, so quality issues could not be related to particular machine settings. Another gap in the data infrastructure was the absence of a single database storing long-term production data at high resolution.  

IPCOS recommended the implementation of a new data historian for direct storage of long-term history. This historian was kept independent of the existing MES applications and databases not to affect underlying production systems. A new database was designed to store static MES data, and a uniform data model was employed for all new databases.  

The real innovation in the project was the new data service layer using data virtualization technology. This service layer allowed for complete data integration without replication and helped other business processes be easily incorporated.  

All these implementations resulted in better traceability of production problems leading to faster response times to customer complaints. The production process was visualized in greater depth, and finally, better control of the production process was achieved, leading to reduced recycling and waste. 

New Data Warehouse Ensuring Faster and More Accurate KPIs  

This client was experiencing slow and inefficient reporting processes. The reports were taking too long to create and lacked valuable information. The corporate headquarters (HQ) had limited visibility on the operations and over the different plants. This project's purpose was to generate automated reporting and receiving on-demand KPIs.  

IPCOS implemented a layered approach which consisted of a data warehouse as the single point of access for all data. IPCOS installed several certified commercial applications to speed up and automate the data entry and help with visualization and reporting and the latest tools for data and event annotation. 

The implementation resulted in faster, more accurate KPIs, but not only that. The productivity of the clients' employees increased due to the elimination of manual tasks and the enhanced collaboration between production lines and the Corporate HQ. This, in turn, empowered operations to address the underlying causes of deviations in the KPIs. 

While a new data warehouse was the key delivery for this project, there were other technical innovations. 

Cost-effective Data Integration for Specialty Chemicals Using Cloud 

This project is typical of batch chemical' producers who face issues in implementing digitalization in their highly distributed plants. Relevant data was not collected in an automated fashion, and, in this case, data centralization did not exist.  

Generally speaking, there is no good off-the-shelf digitalization solution for batch production. Processes are so specific that "standard" digital techniques, such as automatic OEE, tracking of losses, follow-up of KPIs on process performance, comprehensive real-time monitoring, real-time optimization, are not directly applicable. Every plant is different and significant customizations are often necessary to standard software.  

Typical digital solutions for continuous bulk production do not have the required flexibility to account for the wide range of different operating modes and are often too expensive for the scale of the operations. As a result, the reporting processes are slow, time-consuming and lack adequate digitalization.  

After a digital assessment of the requirements, IPCOS advocated moving data to the Cloud and using open-source software to engineer fit-for-purpose applications. The specific strategies used IIOT to increase the amount of relevant data available to plant operators and engineers.  

Moving all data to the Cloud allowed for plant data to be integrated with other non-numeric data in a single data warehouse. Using data warehousing on the Cloud allowed for utilizing an event hub, data factory, and Azure data explorer. Open-source and SaaS software helped build custom fit-for-purpose applications on the Cloud. 

Some of the tangible benefits observed by the customer included a significant increase in analytical capabilities with minimal additional hardware/software investment. The increased analytical capabilities led to other substantial benefits such as manufacturing flexibility, new insights generated through data science, and optimization of the recipes. The reduction in batch variability decreased production losses, and a considerable OEE increase was detected by minimizing quality and performance losses. 

In addition, the cost of ownership and lifetime maintenance was reduced. Projects were delivered in weeks compared to months when assessed against standard MES implementation. 

Conclusion 

Data integration is an important value driver for digitalization, which is invaluable for achieving tangible business outcomes. The three examples above employed three different techniques in data management, but all of them delivered the much sought-after business results. Better visibility over the production units, fast and accurate KPIs and cost-effective data integration for small batch production sites are easily quantifiable outcomes. With digital innovation, data integration is possible on almost all levels with the right approach.  

Contact IPCOS today for a detailed analysis of your business digitalization.   


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