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Why it’s Best to Start with Digitalization for Industrie 4.0?

Digitalization, Factory owner

Why it’s Best to Start with Digitalization for Industrie 4.0?

27 May, 2021

This article will discuss:

  • The digitalization of the factory floor, the technologies required, and the digitalization process
  • The importance of digitalization of the factory and how it supports accountability
  • The role of digitalization in achieving Industrie 4.0

The smart, interconnected factory is the building block for implementing Industrie 4.0 business models. Within the interconnected factory, data is shared virtually or digitally which highlights the importance of digitalization of the factory floor. The fully digitalized factory floor has digitized technologies in place to capture both structured and unstructured data to support diverse Industrie 4.0 strategies.

 

What is the digitalization of the factory?

Digitalization or digitization are both forms of conversion of physical content into a digital form that can be processed by a computer. For example, converting customer-demand records from a binder to an Excel sheet is a basic form of digitization. To digitize content, specific digitization technologies are used and, in the example below, a smartphone with a camera and text-capturing app can handle the digitization process.

Taking the context of digitization to the big stage, more tools or digital technologies are required to achieve digitalization of the factory floor. The average factory runs on interrelated processes to either manufacture a product or deliver a service such as warehousing. These interrelated processes include material handling, supply-chain management, resource management, and machine operations.

The interrelated processes of the average factory floor produce their own set of structured and unstructured data that tell specific stories about the operations being undertaken. Capturing or digitizing these data sets requires the use of digitization hardware and software.

Hardware technologies usually focus on data capture and visualizing aggregated data while digitization software is used for transcribing data, transferring data, and data analysis. Examples of digitization hardware solutions include a 3D scanner that captures point cloud data from physical objects and a sensor that captures data from a machine. Both hardware transfers captured data to a computing platform. An example of digitization software, on the other hand, is simulation modeling software which can create digital models using digitized historical data or captured data sets from the factory floor.

 

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The role of digitalization of the factory floor in achieving Industrie 4.0

The introduction of Industrie 4.0 in 2011 heralded a new way of doing things within the traditional factory floor. This paradigm shift focused on enabling large-scale machine-to-machine communication and data analysis to automate the production cycle. Successful Industrie 4.0 implementations means that smart machines will be capable of operating, diagnosing themselves, and analyzing issues without human intervention. Factory machines will be autonomously interacting with customers and suppliers – making the manufacturing process faster and more efficient.

The founding fathers of Industrie 4.0 hinged its success on digitizing the traditional manufacturing process. Digitalization supports machine-to-machine communication and human-to-machine communication, which are both crucial to achieving a fully automated manufacturing process.

The digitized factory floor ensures that captured data is transcribed to a machine language that the shop-floor equipment understands. The transcribed data can then be transferred to either the cloud, to a network of equipment, or to individual machines on the shop floor, thus supporting diverse Industrie 4.0 use cases.

For example, to implement a data-driven plant performance optimization process, digitalization technologies play a significant role in capturing shop-floor data and analytics. Historical data from past production cycles serve as benchmark data to guide the production process, which ensures that machines recreate past scenarios to yield optimal throughput.

Implementing a data-driven process is just one example of how digitalization supports Industrie 4.0 use cases. Other important Industrie 4.0 business models such as the examples outlined below rely heavily on the digitalization of the factory floor:

  • Predictive maintenance – Digitalization tech digitizes historical maintenance data and analyzes the data with modern, digitized software applications to develop accurate predictive maintenance strategies. Data from equipment can also be captured using digitization technologies such as IIoT devices and edge devices to develop predictive maintenance strategies.
  • Validation and training – Properly evaluating new operational strategies before implementation is what validation is about. Digital transformation technologies such as simulation modeling software or the digital twin utilize digitalized data to recreate shop-floor models. Evaluation is done within the model using operational data such as available resources, facility layout, and shop-floor assets.

Augmented reality devices such as VR headsets are digitized technologies that utilize shop-floor data to create virtual training programs. These programs capture the tribal knowledge of experienced operators and transfer it to the younger, less-experienced generation.

  • Condition monitoring – The condition-monitoring process involves monitoring machine data in real-time to discover or predict faults before they occur. Digitalization of the factory floor provides the technological solutions required to track machine data, analyze it, and gain the insight needed to implement condition monitoring.

 

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Implementing servitization strategies through digitization

If Industrie 4.0 business models are the operational strategies to optimize production and improve efficiency, servitization is the process from which the end-user gains from the efficiency of Industrie 4.0. Digitalization technologies support the implementation of basic, intermediate, and advanced servitization.

Digital technologies make it possible to provide value-added services such as predictive-maintenance tool kits and can benchmark operational data at a cost to the end-user. The digitalization of the factory floor provides the foundation for delivering both intermediate and advanced servitization services, as well as reaping its benefits.

For example, digitalization technologies capture the data needed to provide predictive maintenance services for intermediate servitization while also allowing the service provider to capture data from its advanced machine-as-a-service initiatives.

 

Conclusion

At the core of digitalization of the factory is the need to eliminate paper and digitize data and data-collection processes. Implementing simple digitalization strategies is generally affordable, although the expenses increase according to the scale of its implementation. Once implemented, a digitized factory becomes equipped with the tools to implement diverse Industrie 4.0 business models that guarantee sustainable growth.