4 steps on how to implement Industry 4.0
Digitalization is all around us. Real-time data analysis, digitalized monitoring, and machine learning are only a few of the technologies being introduced under the concept of Industry 4.0.
The possibilities of industry 4.0 are endless. The challenge is how to implement the technologies in an order that gives the best result on the bottom line.
By breaking Industry 4.0 into 4 steps, your production will gradually mature into a digital factory. The 4 steps presented in this article are data collection, digital processes, predictive maintenance and self-adjusting machines.
STEP 1: DATA COLLECTION
Without data collection, no data analysis. The first step towards a digital transformation is to collect data from your machines. You can collect data from e.g. PLCs and sensors. The data is transmitted to a piece of specially designed IoT software via a secure cloud solution. This will provide you with a snapshot of the current status of your production.
Why do two identical machines perform differently? And why is the outcome of identical manufacturing processes different depending on the production site? Data collection and analysis will shed light on the blind spots in your production, and you will gain knowledge of previously unknown factors. By comparing data from 2 machines or production sites, you will get fact-based answers to questions that you were unable to answer before.
STEP 2: DIGITAL PROCESSES
Step 2 is about digitalizing existing production tools. LEAN and OEE are frequently used for production management and monitoring. Used as analog tools, they can be hard to work with and the risk of errors is high.
By digitalizing LEAN and OEE, you can simplify your production processes. This will make it easier to take concrete actions. When using the data collected in Step 1 for recording the amount of and reasons for downtime, you will be able to measure and compare the efficiency of your production across machines, production sites, and time.
STEP 3: PREDICTIVE MAINTENANCE
The ability to predict downtime and to prevent it before it happens is the essence of Step 3. Many companies already possess the required knowledge, but they lack the tools for turning their knowledge into tangible actions. If you start out on the right foot in Step 1, predictive maintenance is not that far away.
When you are able to predict downtime caused by mechanical issues, supply chain gaps, or logistical challenges, you will also be able to make decisions that will prevent expensive downtime. This will significantly reduce the costs for service and maintenance.
STEP 4: SELF-ADJUSTING MACHINES
Step 4 is about machine-to-machine communication. Try to imagine machines communicating across locations. Two identical machines producing the same part in India and Germany and communicating via the IIoT system of your company. In India, the machine may have learned that a speed reduction of 1/10 will reduce the amount of unplanned downtime. The machine will share this information with the machine in Germany. The machine in Germany will in turn have learned that a certain component is to be replaced more often than before. The machine will send this information to the machine in India.
BENEFIT IMMENSELY FROM BREAKING DIGITALIZATION INTO STEPS
The technological development is moving so fast that a stepwise approach is required. The road from idea to action is shortened. And by breaking the many technological opportunities into tangible steps, you will be able to benefit immensely from a digital transformation of your production. A good way to start is by investing in a future-proof platform that can be expanded as the technological development progresses.
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