The term “digitalization” (or the phrase “digital transformation”) has different meaning as applied to different industries. For production facilities, even before the onset of the “digitalization” revolution, the automation segment drove the adoption of advanced technologies. Today, the automation segment naturally finds itself at the center of the whole discussion.

The last decade has seen several industries make significant progress in utilizing digital technologies to grow more efficient and cost-effective. Depending on the industry, however—and to a certain extent, the personnel and the entities involved in project development—digitalization is looked at in far different ways.

Of course, the methods and technologies employed for implementing digitalization will significantly depend on an organization’s end goal. For an engineering professional or a program manager who is setting out digitalization strategies for a new project, it can be challenging to define focus areas from the wide spectrum of topics covered by digitalization. The key is to understand where the organization currently stands in terms of three core areas of digitalization, and then define where the organization wants to be in the near future.  

Core Areas

For any industry, we could broadly say that digitalization, or digital transformation, focuses on three core areas: the systems and processes, automation and communications, and data analytics. These areas can also be considered the primary enablers of digitalization.

Systems and Processes

These are related to the operations management of an organization. A system is the set of procedures and processes that define how the work is done, and a process is a set of steps designed to achieve a particular goal. A multitude of established processes make any given system work more efficiently.

From these definitions, one can see the vast potential for digitalization in these areas. Every organization has their own systems and processes that help it run efficiently. Digitalizing these systems and processes offer immense opportunities for automating tasks while ensuring compliance. Digitalizing operational requirements also creates opportunities for collection, storage, and instant transfer of data over networks to support archiving data and analyzing it for continuous improvement.

Production Automation and Communications

Automation and communication technologies play a key role in enabling the overall digital transformation strategy. These two disciplines were the forerunners that helped spearhead the digitalization revolution for the industrial world, and they still remain core areas for continuous evolvement of technologies and practices for better and efficient management of production facilities.

The disciplines’ influence is demonstrated by the fact that a majority of production facility projects have digitalization strategies built around them, irrespective of the industry or the organizational culture. For an enhanced digitalization project, the automation segment helps extend the way process data is measured, controlled, recorded, and analyzed. The data collection and computing capabilities of sensor technologies, controller hardware, safe and enhanced data communication methods, and the efficient storage and computation of data help build advanced monitoring and control algorithms suited to each particular industry.

Data Analytics

Data becomes a treasure chest for an organization when its analysis can help improve systems, processes, production methods, and forecasts. In the industrial world, however, the word “digitalization” is often associated with this part of the whole spectrum—which, unfortunately, is misleading. The other enablers of digitalization, developed and implemented as part of the transformation project, lay the foundation for data collection and analytics. These enabling stages are as critical as the analytics part.

All branches of data analytics—descriptive, predictive, and prescriptive technologies—are used in developing models and solutions that suit the industry and the unique aspirations of the organization. Artificial intelligence and machine learning technologies help further the utilization of data and deployment of solutions throughout the organization.

Challenges

While setting out on a digital transformation project, it is important to understand where the organization stands on the three core areas discussed above, and to set a realistic goal considering the time and resources available for the project. It is also critical to evaluate the future evolution of technologies and their significance to the organization’s ambitions beyond the project execution period. The balancing act between selecting an innovative technology that is field-proven while being futureproof could be challenging to project management. Due to the expanding reach of technology, ever-increasing cybersecurity requirements will also demand significant evaluation and resource allocation.

Conclusion

The success of a digitalization strategy for a production facility greatly depends on the organization’s evaluation of its current position and its identification of areas of focus for the transformation campaign. Early planning and implementation of the enablers, and a clear vision for efficient utilization of data for corporate competitiveness, will go a long way toward the success of the strategy.

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