Smart Factory, Industrial Internet of Things or networked productionMany concepts that are being developed in the context of Industrie 4.0 often sound highly theoretical. Theory and practice cannot always be perfectly reconciled in this context. One fundamental difference that will be discussed in the following is that between so-called "greenfield projects" and "brownfield facilities".
Greenfield projects are about creating a fully digitalised factory on a free, green meadow to build. Most of the considerations on the topic of Industry 4.0 are based on this. In reality, however, the number of brownfield plants predominates. Therefore, many companies would like to see approaches that are more closely aligned with reality. Such realistic concepts are especially important because networked manufacturing represents a great opportunity for Germany. It can prevent manufacturing from migrating to low-wage countries and thus contributes to the success of Germany as a business location.
The Greenfield Approach in Industry 4.0: The Ideal
If Smart Factorys described, it is the "pure idea" of digitally transformed and networked production. All machines and plants are equipped with sensors that monitor the ongoing operation, work items are smart objects that are equipped with chips and can provide information about their current processing status, the data storage in the background allows profound Big data analysesprocesses are improved and adapted on the basis of this information.
The smart factory described in this form must accordingly be seen as a Ideal state be understood. This ideal form of a networked factory would come about if a perfect manufacturing factory were to be built on a greenfield site according to all the rules of the art. The problem with the so-called greenfield approach is that not every company that wants to take advantage of all the benefits of networked manufacturing can simply plan and build a new factory from scratch.
This is how the German Electrical and Electronic Manufacturers' Association (ZVEI) visualised digitalised industrial production.
As a rule, factories and production lines are built with a runtime of at least 20 to 25 years so that the costs are amortised and profits are generated. Greenfield projects are therefore the exception rather than the rule, and the majority of companies can realise digitalisation more easily within the framework of a brownfield plant. Nevertheless, there is currently a great need for action because more and more companies are switching to Industry 4.0 and competition is increasing accordingly.
The Brownfield Approach: The Reality
The reality is different in most cases. Many factories and plants were planned and built at a time when it was not yet apparent how fast the development of digital networking was progressing. The production conditions in many factories therefore do not meet today's requirements.
As "Brownfield" plant is used to describe a factory or manufacturing plant that has already been built and has been in operation for some time - a "brown field" is therefore a Field already built on. Accordingly, the brownfield approach in the context of Industry 4.0 is the digital transformation of an existing manufacturing facility.
The first central step in a brownfield project is the Digitisation of all analogue components and processes. To prepare a conventional factory for networked production, for example, it is necessary to consistently digitise all processes where communication is still paper-based or carried out "shirt-sleeved".
Just as the "paperless office" was based on the elimination of paper, this analogue medium is no longer important in the smart factory. The second, decisive step on the way to networked production is the Digital networking of machines, people and materials for example with the help of sensors or RFID chips. There is no patent remedy here, precisely because every company has a different levels of digitisation has achieved. So solutions have to be worked out specifically for each company in each sector.
The main challenges in digitalisation
At the Digitisation from already existing processes, so with the brownfield approach, the most important thing is to make sure that they are transferred completely and with a lot of care. Errors in the transfer from the analogue to the digital world can lead to far-reaching consequences. Lack of data quality is one of the most common sources of error in data science projects.
The problem is: any gaps or errors in process knowledge are inherited when linked to IT processes. Experts estimate that up to 40 per cent of the data in the IoT environment could be inaccurate, poor or erroneous and therefore useless. (Source: Computerwoche) A typical source of errors are data records that have been recorded twice or differently formatted data that are based on old industrial reporting systems, for example. Also, when mounting measurement sensors, great care must be taken to ensure that the measured values are correct and not falsified by external influences. If you want to learn more about how to get a optimal data quality We have put together the 5 most important tips for achieving this.
Many companies are very hesitant to tackle the topic of Industry 4.0 because it seems like a Herculean task to digitally network the entire production from one moment to the next. At the same time, it is enough to start with a single Use Case and implement it successfully. In our experience, the results are so convincing that the staff are also quicker and more active in the next project. Thus the digital transformation takes place step by step. Complete system architectures are difficult to set up in parallel to ongoing production anyway.
Older plants in particular can benefit
Older machines and industrial brownfield plants in particular can benefit from digitalisation and a switch to a data-based approach. For it is precisely they that are very much More susceptible to maintenance than new systems. The more often machines have to be serviced, the longer the downtimes. Even if only individual machines come to a standstill because, for example, they have to wait for special spare parts, in the worst case the entire production can come to a standstill. The consequences are sometimes enormous economic losses. In view of this situation, predictive maintenance offers itself as a solution.
In so-called "predictive maintenance", a machine or production plant is equipped with numerous sensors to monitor its operation. Down to the component level, it is thus possible to predict with a high degree of probability how long a machine will function without problems. The time when a component must be replaced can also be derived from the measurement data. Replacement can take place even before before there is a failure comes. With the Preventive maintenance other digital technologies such as VR or AR glasses can also be used.
Every company, every factory and every plant can and must be digitised
The distinction between greenfield and brownfield annexes clearly shows one thing: Every company, every factory and every process can be digitised. Since many companies in Germany still need to catch up in terms of development in the area of Industry 4.0, this approach is particularly promising. One prerequisite is crucial here: first, all processes in a company must be digitised. Only then can the actual digital transformation take place by linking manufacturing, supply, maintenance, production, delivery and customer service in real time via the internet.
This digital networking of the manufacturing process is the core idea of Industry 4.0 and a promising concept that companies in Germany are Competitive and sustainable can do.