As we see in the current situation, efficient, flexible processes and systems in production and logistics are essential for companies. Only in this way can companies react quickly to changing circumstances. When the first version of our digitization report was written, we could not foresee the situation we are in today. Nevertheless, we are convinced that the strategic use of IoT technologies in production plants can enable companies to anticipate and react to such events.
But what types of applications are possible, what improvements can be achieved and how does Zielpuls Industry 4.0 drive initiatives? All these questions are addressed in our Digitalization Report - Industry 4.0:
Industry 4.0 (abbreviation: I4.0) and the Industrial Internet of Things (IIoT) are two terms that are encountered more and more frequently. But what do these concepts – often used as buzzwords – actually describe? While I4.0 is primarily used to refer to the digitalization of processes in industry, IIoT describes the technical structure of the resulting systems: solutions in which all objects are networked and capable of communicating with one other. The results of I4.0 initiatives and a broad application of IIoT are fully networked companies in which entire factories with their machines, transport and warehousing systems produce products largely autonomously. But which benefits are enabled by such technologies? How should managers proceed when driving related initiatives and what challenges should they expect?
This Zielpuls report summarizes our experience in factory-based digitalization initiatives and provides an initial orientation. To provide a concrete guideline for the realization of I4.0 projects, we describe the Zielpuls Best Practices for preparing, executing and leveraging digitalization initiatives, as well as the particular challenges involved.
Fields of Application
I4.0 initiatives are strategic decisions, not just solutions to individual problems. Large organizations often still operate in a way that aims to maintain the procedural status quo and only address those problems that visibly run against it. From this perspective, "problem areas" would likely be the more understandable heading for this section. In fact, we deliberately chose the term "fields of application" to show that the use of digital technologies is possible and can make sense in many fields of application, even if these are currently not perceived as problems in a classical sense with an immediate need for action. In our experience, this distinction is essential, because the essence of digitalization lies in questioning the current situation and looking for technical solutions to improve it.
Digitalization is much more than just predictive maintenance. The most frequently mentioned fields of application of I4.0 fall into the areas of production and logistics. In this context, the topic of predictive maintenance is often mentioned, i.e. anticipating the right moment for maintaining machines and systems by applying probabilistic methods on live machine data. This example however only represents the most immediate form of value-adding digitalization in manufacturing. Other promising processes for digitalization in production include (partially) automated control of production processes and quality assurance, intelligent planning of production programs, and autonomous logistics systems (see figure below). In all these applications, real-time data from operations can be integrated into planning and execution processes. Complemented by classical automation of processes (e.g. robots in material handling), a largely autonomous process sequence can be achieved. If factories also provide structural flexibility, this combination of data-driven control and automation enables order-oriented production of individual products.
Apart from production and logistics, digital applications can be used also for efficiency gains in other business processes of manufacturing organizations, from sales to purchasing. For example, administrative tasks that are repetitive and run based on clear rules have great potential for data-driven automation of work processes.
Accordingly, decision-makers should be careful not to understand the term I4.0 too narrowly. Rather, production processes should be seen as the starting point for systematically identifying further fields of application. After an in-depth exploration of the possibilities in a clearly defined area, the focus should be expanded to also examine the neighboring and supporting processes and areas within the company for potentials and synergies. This approach can be quite useful and ensures that the derived measures leverage the global potential and do not merely represent the next local optimum.
Effects of Digitalization Initiatives
Benefits are possible in many relevant KPI dimensions to improve productivity and agility. Consequently, I4.0 enables a wide range of use cases, each of which can lead to significant improvements. But what is the potential impact in terms of specific KPIs? In fact, already today the systematic collection and utilization of information enables organizations to exploit significant potentials in traditional production environments with regard to productivity and agility. Our experience from previous I4.0 and IIoT projects shows that significant benefits can be realized even with basic solutions, which enables the improvement potentials as illustrated below.
Some of these effects stem from one of our customers, a manufacturer of medical products. In the project we were able to achieve significantly increased transparency in production by means of systematic collection and provision of data. The result was that various product and production optimization analyses could be carried out on a broad basis of discrete data, leading to the identification of the causes for deviations and 7-digit savings for the individual manufacturing plants. The global collection and aggregation of performance data also enabled the client to identify trends and, if necessary, anticipate worst consequences. A special characteristic of the technical solution that enabled these benefits is that it was not only designed with the current needs in mind. Rather, it offers various interfaces and opportunities for future functionality extensions and integration of new technologies into the overall system. As a result, further efficiency gains can be realized in the future and process innovations can be adopted more easily.
Solutions and Features
To realize significant improvements, however, a certain infrastructure is needed. In this section, we explain how this infrastructure looks like and what impact it has on the company-wide IT architecture.
The technical solutions needed to exploit the identified improvement potentials are as company-specific as the use cases to be implemented. Nevertheless, the solutions are based on similar patterns that can be described as follows.
A good analogy for explaining the necessary steps is that of a supply chain. Sensors and machines represent the source of the raw material, which is data (see step 1 in the figure below). From these sources, the data is forwarded via bus and network connections (step 2) to be merged and stored in central databases, bringing data from different sources into a uniform format (step 3). These processes can be understood as transport and warehousing processes. At the same time, data is often also transformed (step 4), for example by enriching and linking it with further information. This step can be imagined as a setup process that takes place before the actual added value is created. The main added value occurs primarily through in-depth analyses in which insights are gained from the information and improvement measures are derived (step 5). The data can also be used to automatically trigger and control processes. Since both the ability to analyze and automate allow for significant value-add, they can be viewed as the actual production process. Passing the entire process chain in a largely automated fashion enables very short cycle times. Moreover, even complex analyses can be carried out automatically by integrating artificial intelligence solutions. As a result, insights can be generated in the blink of an eye, which were previously tedious and difficult to develop manually.
For implementing such an information supply chain in practice, adjustments in the IT landscape are often necessary. In many organizations, the machines and IT systems in production were traditionally integrated to a low extent or not connected at all to ERP and other business applications. For I4.0 and IIoT applications, however, a continuous information transfer must be guaranteed, as shown in the figure below. This can be achieved via IoT platforms that are explicitly dedicated to collecting, storing, exchanging and transforming data. Such platforms offer special functions to integrate new information sources and clients such as ERP and PLM systems as well as analytics applications with little effort. A positive side effect of such a central IoT platform is that it automatically creates a high degree of transparency about information flows. Currently, an ever growing range of IoT platforms is available, offered by manufacturers from the traditional plant engineering sector, by companies with roots in the IT sector, as well as Industrial and IT system integrators (see figure on the right). However, a careful and diligent look behind the marketing smoke screen is necessary, as many platforms are still in the development stage. Some vendors have only implemented partial solution use cases and lack maturity and a proven production track record.
How to drive Initiatives
What is the best way to develop and implement I4. 0 initiatives and digitalizing the processes in your company? We are using a Best-Practice approach based on our previous digitalization projects and industry knowledge, represented by the following four steps:
- Value Exploration: In this initial phase, the status quo is determined and the possibilities for use cases are explored. The result of this phase is a roadmap with possible use cases to be implemented and specific to the situation experienced by the customers. In addition, the use cases to be implemented directly are identified to ensure that the costs incurred by the IoT solution can be quickly amortized.
- Solution Design: Based on the requirements arising from the use cases, we develop alternative feasible solution architectures. The resulting solutions consist of IT architectures, minimum viable products or software prototypes, for instance.
- Implement & Transform: Once a solution has been selected, it is time to implement it. In this step, proof-of-concepts, pilots or initial rollouts with broader scope are carried out. As a result, the first benefits can be realized immediately.
- Grow & Accelerate: In the last step, the solution is scaled. Based on the technical prerequisites accomplished in the previous step, scaling aims to multiply the positive effects by implementing further use cases and rollouts in additional plants, regions or customer groups.
These steps have demonstrated their effectiveness for a number of reasons. On the one hand, the explicit distinction between value exploration and solution design makes it possible to develop more than just a solution for a single immediate problem. Instead, the broad spectrum of possible actions is first analyzed and captured. Based on this analysis, the identified options can then be examined for commonalities and prioritized for implementation. This means that the requirements of all options can be kept in mind from the outset, and planning can be carried out with foresight. Also, possibilities can be provided to efficiently expand the subsequent solution in later phases. The motivation for a step-wise approach in the implementation and growth phase lies in the fact that learnings can be derived after the first implementation and, if necessary, the solutions can also be modified. This ensures that both the solution to be implemented and the implementation process itself can be executed in the best possible and most efficient way without encountering unforeseen difficulties across the board.
During the phases of first implementation and subsequent scaling, we typically pursue three goals (see figure above). The primary goal of our approach is to develop a solution that provides the means to combine short-term feasibility with long-term options for extension. This is achieved by applying a systematic approach and innovative thinking (step 1 in figure above). Nevertheless, the required IT solution itself commonly does not yet generate any benefits. Therefore, the focus is subsequently placed on identifying and leveraging the efficiency and optimization potential in order to achieve a positive ROI (step 2). The final step is to concentrate on increasing flexibility and agility. In doing so, we are aiming to ensure the sustainability of the efficiency gains and make the results of our customers’ organizations more robust against disruptive influences such as fluctuations of business.
What are the particular challenges of implementing I4.0 and IIoT projects? Despite a clear plan and defined use cases, the implementation of such projects is anything but trivial. The reason for this is the dependence on the individual circumstances and the current state of technology in the client’s company. A particular challenge is that it is often the technical details that really matter. IoT solutions are technically quite complex, yet they should provide a seamless fit with the corporate IT landscape. Without an in-depth analysis, decision-makers run risk of buying into something only to discover later on that the desired effects cannot be realized with the chosen solution. Hence, a deep understanding of the existing technical preconditions as well as the characteristics of future platforms is required. Both the initial implementation project and later extensions imply that IT solutions have to be developed and adapted, whose target form is unclear at the outset. This fact promotes a flexible approach for developing solutions based on the actual needs of the organization. Setting up a solution design process with iterative steps creates opportunities for prototyping, testing and learning. Another factor for successful execution of IIoT projects is the culture in the company, which can influence implementations both positively and negatively. Since implementation of IIoT solutions often go hand in hand with process-related adjustments in factory and IT operations, early involvement of the relevant stakeholders is an important measure to achieve the necessary acceptance. If this prerequisite is not achieved, there is a risk of developing a solution that will not be accepted by the workforce, with negative impact on the performance that can be expected.
To meet these challenges, we use different methods in each of the respective project phases. In the exploration phase of a typical project, for example, we apply creativity techniques such as design thinking or hold thematic break-out sessions with our experts to inspire our clients. Furthermore, we typically involve the relevant parts of the customer organization’s workforce actively into the solution design process at an early stage, to generate commitment and achieve lasting results. In the subsequent solution design phase, we apply systematic requirements engineering and agile software development methods. In order to make well-founded decisions about the selection and implementation of individual use cases, we also carry out business cases and SWOT analyses. After all, our capabilities in stakeholder and project management help to support our customers also in non-technical matters.
Conclusions and Outlook
We experience that more and more companies are using IoT solutions in their daily practice as part of their I4.0 strategies. This development is propelled by the benefits offered by the methodical and IT-supported utilization of data and information. The adoption rates and pace of progress is differing between the industries, as the degree of regulation and the intensity of competition create different dynamics. Nevertheless, more and more concrete application scenarios for IIoT can be identified and developed that help to achieve major efficiency gains in all segments. Simultaneously, a broad range of IoT platforms shows that the solutions and technologies have now arrived at industry standards. Although we expect that this market will still consolidate in the coming time, the large number of well-known providers is clearly reflecting the high priority and economic opportunities in this field of technology.
We at Zielpuls are happy to accompany you on your way into the future by supporting you in the planning and implementation of your I4.0 and IoT technology strategy. We would be glad to use our experience and our broad expertise in digital technologies to help you develop a concept that is optimally suited to your needs and put it into operation.