For an industry location such as Germany, Industry 4.0 is key to its future. The Internet of Things (IoT) in turn is essential for Industry 4.0; it refers to the technologies, devices and sensors that are connected and controlled over the Internet. What are some of the recent developments, what are the types of obstacles faced by companies, and what types of approaches are emerging in this context?
What are the current developments in the IoT environment?
The following developments and trends can be observed in the quickly changing IoT environment at present:
- Connectivity creates value!
It is becoming increasingly obvious that value is created by connecting multiple technologies and hitherto separate information. More and more companies utilize machine learning and artificial intelligence tools for using machine data. Augmented reality solutions such as the Microsoft Hololens are used for expanded visualization and control purposes, primarily on the production side.
- Technologies from the private and professional sphere are merging.
Solutions from the private sphere are adopted into the corporate setting. Voice control, as offered by Alexa and Siri, is a preliminary step to what we can expect in the communication with our production facilities in the future.
- The fight for “horizontal platforms” (Cloud Service Providers).
Many providers are entering the market, or are attempting to expand their market share with a view to the IoT. Microsoft Azure has become a big player in this context. The IoT Cloud services and development components (e.g. Azure IoT Suite) that are integrated into this system significantly reduce the requirements for new IoT solutions.
- “Vertical platforms” are pushing into the market.
More and more providers that focus on certain application areas or industries are entering the market. The platforms of large industry outfitters such as General Electric or Bosch are gaining in importance. Especially Siemens, with its Industry(4.0) platform Mindsphere, has greatly expanded its market position.
- Scalability of IoT solutions.
Many companies are looking at the question of how small pilot projects or proofs of concept can be turned into company-wide or company-relevant solutions. Experts estimate that this process will be unsuccessful in four out of five cases. This means that only 20% of IoT solutions have the potential to scale up significantly.
What are the typical obstacles from the company's point of view?
With all the agreement on the relevance of IoT, many companies are still hesitating. We have identified the following factors in particular:
- The initial obstacles are considerable, and a lack of practical experience creates a feeling of uncertainty, so that the testing of IoT projects is delayed.
- The (in-house) development or (external) acquisition of technical know-how is still in the infancy stage.
- The IoT or Industry 4.0 strategy is not yet anchored in the higher-level digital or corporate strategy.
- Without the right use cases, the company is unable to fully identify the added value.
- On the other hand, it is also clear that the IoT segment is also associated with considerable costs and investments.
These hurdles are real but not insurmountable....although: every strategy must address exactly these items. The company's own IoT strategy must demonstrate how these hurdles are overcome within the company.
What use cases ensure the viability of IoT solutions?
The technology is ready. The question is where and how it can be best applied. It`s all about Use Cases:
- Internal use cases are a good starting point, as they initially make do without a direct customer interface. In this way, experience, skills and qualifications can be developed from the ground up. Potential failures are not as serious, and usually without lasting damages.
- At the same time, internal IoT use cases also offer great potential. The optimization of production processes is a promising area in this regard. Here too the focus is on the integration of technologies. Most recently, we connected machine data with chatbots. Now employees can submit status queries using spoken language (“When will work piece 4 be finished?”). In the next step, the machine data and throughput times are optimized using machine learning. In this way, the more intelligent combination of production steps leads to an increase in made-to-order production per day. At the end, the quality control process (which is usually manual) is also supplemented with machine learning. In this area, items are often incorrectly diagnosed in practice (> 25% pseudo errors). Retesting takes time and ties up resources. Machine-learning models can avoid these pseudo errors. Usually, such a model can be amortized by our customers over a period of a few months.
- IoT is the means, not the end in itself. When we take into account the items noted above, IoT makes a sustained contribution to companies, the environment and society.
- IoT can play a central role in the energy transformation. Especially projects in the energy segment lend themselves to the implementation of rapid (and efficient) solutions. The fact that these solutions also offer a high degree of environmental relevance makes them even more attractive and sustainable.
- IoT can play a central role in compensating for the shortage of skilled labor. In some industry segments, it is already becoming evident that the expansion of production capacities is restricted by the lack of skilled labor; this leads to losses in terms of revenues, growth and market share. IoT solutions can be used to partly compensate for these shortages. Based on our customer experience, the combination of visualizing machine data via dashboards and augmented reality (smart glasses such as Hololens) achieves the targeted and improved qualification of service employees in maintaining production equipment. Chatbots round off these use cases, as they enable employees to use natural language to ask questions about the status of the machine or the required maintenance procedures while they are examining the machines. Thus more can be achieved with fewer skilled employees.Two current examples:
- CS has developed a Smart Factory system that companies can use to manage and automatically optimize lighting in production independent of location. Lighting dynamically adjusts to current demand, and thus significantly reduces electricity costs and CO2 emissions.
- We have worked with a variety of customers to implement sensor-based solutions for the prompt provision of actual energy data for warehouse and production facilities. Instead of collecting and analyzing data on an annual basis, heating and energy costs are now optimized (or reduced) on a daily basis. At the same time, new forecasts assist with predictive or preventative maintenance at the various locations (e.g. spare part replacements).
What process will enable me to reach my goal?
Finally there is the question: How can I get the right IoT solutions, and what process will I need for this purpose? Maybe some of the following will be helpful:
- Analysis and validation formats such as Design Thinking and similar form the starting point for the safe development of business-relevant IoT application cases. You can also use the DARE process. It comes from practice, and is made for practice (see below).
- IoT is a technology issue. But not only that! Make sure that your process combines technology, methodological knowledge and change management. It is only when all three dimensions are combined in a specific project that the success of the resulting solution can be experienced by the entire company.
- Turn IoT into something tangible. Create access to and visibility for the first pilot solutions. More important than the scope of the solution is as many visitors as possible. Actively invite management to try out the prototypes themselves. Or put the prototype right at the entry to the canteen, and let employees communicate with the chatbots.
- IoT is not a project; rather, it normally consists of a multitude of entirely different projects, initiatives and ideas. Therefore they should be put in some plausible context to each other, and ideally also visualized. In this case, the set-up of a dashboard or IoT portfolio makes a lot of sense. A simple overview in SharePoint is already helpful in the beginning. It promotes acceptance and knowledge in management, and helps individual employees find the right contact persons for related projects.
- External partners help with the know-how transfer and the development of own skills, and also help with convincing skeptics or overcoming obstacles. Where needed, an external project manager can also help out in the starting phase.
And finally: How can I find out more?
Here are a few ideas for reading or viewing:
- A comprehensive analysis of IoT developments: Industry 4.0: Why now?
- An interesting source for IoT use cases: www.iot-analytics.com/latest-insights/
- A concrete template for a process model: DARE: The Campana & Schott process model for digital transformation projects