The future of the company
The decision to strategically maneuver your organization to Industry 4.0, which includes automation, IoT, and Machine Learning projects, is a pivotal moment that comes with a unique set of challenges.
Digital products play a major role in market competitiveness and in identifying customer needs and how to meet them. Challenges such as the combination of rapid technological changes and long-term investments (machines, buildings, etc.) present many companies with fundamental decisions. These include decisions on their own IT architecture, on the further development, or even new development, of required competencies and the adaptation of existing operating processes.
Even established large companies are now facing fierce competition by start-ups from outside the industry, if they do not have a strategy in place to face these challenges.
It takes not only the ability to implement technology, but also the right attitude and culture to tackle these new and shorter processes. ”
Business Case vs. Use Case
The usual calculation for return on investment, is simple and is based on how long it takes to pay back the investment costs with the positive monetary effect. In Industry 4.0 this is no different. However, a distinction should be made between use cases and business cases.
A simple use case may be a digital display in a meeting room that shows whether the air is too stuffy based on the CO2 content. This may be a nice gimmick, but the costs are not justifiable because there is no return on investment.
A business case could relate directly to a production process such as in a factory. An automated quality check on products which finds a small fault in the production process, that costs the company a lot of money, leads to corrections in the process and on the product. This not only increases quality, but also reduces scrap, warranty quantities, machine control personnel, and the throughput time for production. As a result, production costs are optimized. In this case, there is a direct correlation between this business case and the return on investment.
However, in order to put in place a profitable business case, it’s important to gather the right knowledge. Typically, such systems and their processes are very complex and require a lot of know-how. External consultants know the best approaches and technical possibilities, while production specialists know the peculiarities of the company, the production, and the product to be produced. Therefore, it is important to analyze the whole process by getting all stakeholders involved to check each single process for its correctness, importance, and optimization.
“This is a discussion among many and not only at management level”
If, for example, the fastest throughput time is achieved with a certain optimum surface temperature, this specific knowledge must be included in the planning as early as possible. This requires the measurement and validation of the surface temperature in real time at the right place in the process and the possibility to act on this temperature automatically.
The right data architecture
Often information does not have to be obtained with sensors, because it is already available in existing systems – however, people are often not aware of this and the data is therefore not used.
“Get your data chaos in order”
In our projects, we have found that few companies know about the flood of data coming externally, as well as the internally, from their customers or products. By exposing this data and putting it to work, we have helped countless organizations gain insight into their products and optimize them accordingly. Products enriched with information and fast services can contribute massively to competitiveness.
However, none of this can be done without the right data architecture. A strong data architecture entails having a data integration platform that helps to integrate future systems.
Combining standards and individual solutions - a challenge
Once you have insight on process optimizations, you can already submit the corresponding requirements for the production machines to your automation supplier. If the insights are relevant, they may be incorporated into the process. If this is not the case, or if the machines are already in use or come from different manufacturers, the complexity is increased.
Production machines today usually communicate via common protocols such as OPC-UA, Modbus or MQTT and usually meet the requirements for security, latency, or data volume. If not, gateways are used which modulate the data accordingly. Sensors, on the other hand, often communicate via analog I/O or via radio (e.g. BLE etc.).
This means that sensors and machines communicate in different ways and a uniform software interface is required for control and monitoring. The proprietary solutions of most IoT providers on the market become a major challenge when they are expanded or merged into one platform.
There is a lot to consider when it comes to sensors. Standard sensors often contain many more features than are needed. It is worthwhile to manufacture the sensors so they are customer-specific and refrain from standard products. Furthermore, the specifications and certifications in the different countries must be considered in order to be able to import and legally operate the sensors.
One challenge organizations face is that IoT projects fail because no one feels responsible for setting the standards, even if the individual solutions seem very good and innovative at first glance. Making the right choice here is crucial to success.
The right communication technology
Communication is another stumbling block and central to the successful implementation of national and international IoT projects. But often it is too expensive, not feasible or simply not standardized.
The question of how to communicate is central, both on the hardware and software side. Which communication technology is the best for my needs and works as trouble-free as possible in my environment? Which software platform should be used? Are my customers located nationally or internationally? Which technical requirements must be met globally? Political interests and restrictions should also be known and considered.
“Do not rely on marketing and flyers for communication”
Whether the sensors are supposed to collect data autonomously over several years, or intelligent systems with algorithms at the machine directly influence them – the communication possibilities are available, but far from uniform standards and global availability. The networks in the individual countries with technologies such as 4G/5G LTE, LoRa, Sixfox are unequally developed, use different frequencies, or are prohibited. New approaches such as satellite supported LoRa communication (Lacuna Space) will help in the future to be able to operate sensors at the customer’s premises without access to his network.
The right mix of data protection and data security
The machines are now tapped and ready to be read, the products are at their customers’ sites are diligently delivering data that you can use for improved support and an enhanced product experience.
However, security is a central concern, so it makes sense to think about the legal basis of data protection and data security early on. Where is the data stored? Which data belong to me and which to the customer? How should the data be made available to customers? How can we protect the systems against unauthorized access?
Different levels of security can be applied here, from verifiable operating systems, devices and sensor-internal encryption components, early warning systems to data validation, there are numerous combinations that can meet the need. When it comes to security, it is not advisable to evaluate and procure a standard, but to understand the components used as a network, which can be continuously adapted to the current conditions.
“Nobody can escape data protection and data security”
Often the required methods and security concepts can be adapted and extended to an existing environment – if you don’t have one yet, it would certainly be time to take a closer look at system security – otherwise it would be an expensive learning curve.
Of course, various topics have remained untouched in this blog – nevertheless, it is relatively easy to see that the complexity of each individual area cannot be dealt with by a single company in a way that meets all needs. A good ecosystem consisting of specialists in the individual areas is recommended. To avoid laborious discussions, a responsible general contractor is also a good option. In our previous projects, either we ourselves or one of the ecosystem partners took over the management of the project as SPOC at the customer’s site.
We are happy to be available for an exciting exchange and wish you success in your engagement with Industry 4.0.
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