1 Introduction

Industry 4.0 offers great potential for relieving operators in their daily business by providing data-driven (decision) support. Therefore, operators can focus on their core competencies  [1, 2]. Furthermore, industry 4.0 can fasten manufacturing processes due to data-based and autonomous decision-support for operators and reduce errors, e.g., by enabling a paperless production that reduces or eliminates media disruption [3]. Therefore, implementing industry 4.0 strictly requires data as an enabler for more automated processes and decision support. Nowadays, modern machines generally are capable of data generation and processing, e.g., via OPC UA. However, organizations rarely realize the potential of using this data due to significant barriers, e.g., the lack of interdisciplinary technical knowledge of employees. Depending on the company’s size, the lack of knowledge differs since small enterprises often have fewer resources for industry 4.0 projects  [4]. Another challenge is the collaboration of production and software engineers. While production engineers are very familiar with the production process, the corresponding data points, and their meta-information (e.g., accuracy, unit), they lack skills regarding information technology and vice versa  [5]. Hence, in an industry 4.0 environment, it is crucial that these domains collaborate to enable a syntactically and semantically correct data flow. Thus, tools are necessary that address this demand. A suitable tool for this purpose is value stream mapping (VSM) 4.0. Originating from lean management, VSM 4.0 enhances the classical VSM with properties for data transferring and processing. Performing the VSM 4.0 within real world use cases points out some shortcomings, especially from an information technical viewpoint. Enabling a comprehensive data flow and processing is difficult since relevant information is missing. Addressing this issue, this contribution enhances VSM 4.0 by adding relevant properties to VSM 4.0 plus. The VSM 4.0 plus provides further technical properties. This allows both production and software engineers to comprehensively point out the current production process and the corresponding data flow more efficiently. This leads to the following overarching research question (RQ): How can the VSM 4.0 method in its current status be extended to illustrate the data and information flow in a technically holistic way?

The remainder of this contribution is organized as follows: First, a brief introduction of value stream mapping is given in Sect.  2, starting with its origin within a lean management context. Then, after pointing out related work in Sect.  3 and providing the methodology that has been applied in this contribution in Sect.  4, value stream mapping 4.0 is introduced in Sect.  5. Subsequently, the new VSM 4.0 plus is introduced by listing the existing shortcomings that will be directly solved. In Sect.  6, the application within industrial environments is shown. A discussion of the results, followed by a conclusion and outlook, completes the paper.

2 Origin of value stream mapping

The value stream mapping originated in 1915 and was introduced by Charles E. Knoeppel  [6]. Figure 1 shows a graphical example of the classical VSM.

Fig. 1
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Exemplary value stream mapping as lean management tool, according to [7]

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The VSM is a tool from lean management and aims to improve the production process of a specific product or part. Initially, the current material and information flow must be evaluated comprehensively in a graphical manner. Therefore, standardized symbols and key performance indicators that quantify the single process steps exist, e.g., process cycle time, delivery time, or storage duration. On this basis, process steps containing non-value-added elements and waste can be identified and further eliminated [6, 7].

3 Related work

Industry 4.0 aims for data-driven smart manufacturing processes [8], but the implementation is challenging for small and medium enterprises (SMEs) [9, 10]. One way to simplify this is to develop tools for initializing and subsequently optimizing the data flow.

Campos et al.  [11] conducted a case study on a bi-directional data flow between 3D-CAD design and finished parts. Their approach is limited to STEP-enabled manufacturing environments and covers one aspect of manufacturing, namely the construction of mechanical parts.

Joppen et al.  [12] developed a method for the specification of data flows within production. Their data map is a tool to visualize data potentials by giving an overview of data sources, processing units, and sinks. The medium of data transfer is captured as well. They present a business process overview, focusing on the manufacturing and machinery perspective.

A state-of-the-art implementation of a data-integrated manufacturing process begins at the design of the production facility, as shown by Tao et al.  [13]. This approach models the data flow very early in the product design phase. Similar to the material flow design, its effectiveness and leanness are crucial factors.

Furthermore, Uckelmann [14] offers a limited extension of value stream mapping by considering value-adding information flows and information logistical waste through the establishment of CPS in production environments. Tripathi et al.  [15] face improvements in sustainability by developing an agile VSM for industry 4.0 purposes. Since the authors do not consider the technical domain for data gathering, it remains unclear how industry 4.0 benefits from their VSM approach. Lasa et al.  [16] summarize that gathering the relevant data from corresponding information systems increases the efficiency of processing the VSM without presenting further details. Balaji et al.  [17] connects the VSM with the Industrial Internet of Things (IIoT). They gather sensor data directly from the shopfloor but do not provide a method for doing so.

Another appending to the VSM 4.0 is done by Molenda et al.  [18]. They present a methodology for visualizing and analyzing information processes in manufacturing companies, namely the VAAIP mapping methodology (visualizing, analyzing, and assessing information processes). Apart from the mapping, they present a way to analyze the current state of the information process. They define a global information index that quantifies the given state and give recommendations on how to classify it.

Busert et al.  [19] present a six-stage procedure to improve information quality by harmonizing the information flow. Their work focuses on the optimization of information flows to control operational processes.

Finally, Meudt et al.  [20] developed the VSM 4.0 that enlarges the classic VSM with options for gathering process steps’ data points. Lewin et al.  [21] enhance the VSM 4.0 by adding symbols. Since both versions of VSM 4.0 are generally suitable for the first choice of needed data points and their processing, some shortcomings, especially for implementation purposes, were identified, addressed, and solved in this contribution. Hartmann et al.  [22] derived the value stream design 4.0 method from the results of Meudt et al.

4 Methodology

This section presents the methodology for building the VSM 4.0 plus. A suitable research method for further improvement of the VSM 4.0 is provided by Peffers et al.  [23] through the adaption of design science research (DSR) to information technology and systems. Through the method, there should be a continuous iteration to develop an artifact. An artifact within the domain of information technology, is understood to be a development object that can be expressed both in a concrete software instantiation and in a symbolic representation as a result of conceptual design based on observed problems [24]. Artifacts can be methods, as in this work, that solve a problem which is defined and identified in previous steps [25]. The iteration includes a demonstration and evaluation of the artifact as well. After the execution of the iteration loops, the communication of the result is given.

In the following, the implemented method, which is based on Peffers et al., is described. This work used a problem-centered research entry point. Occurring problems of previous VSM 4.0 and resulting objectives are introduced as shortcomings. Referring to the shortcomings, the artifact has been developed, which in this DSR approach corresponds to a method or an extension of an already existing method (VSM 4.0). As in the DSR by Peffers et al. intended, the artifact built by the shortcomings is demonstrated, evaluated, and adapted in further iteration steps. For this purpose, a learning factory is used. The learning factory of the chair of production systems at the University of Bochum serves as the very first test bed, as it depicts a small manufacturing environment. Some preliminary work has already shown that learning factories are capable of representing the scope of SMEs [26, 27] so that the environment learning factory provides a suitable and valid test bed for the first iterations of trial. After the artifact was capable of representing the learning factory in its overall complexity, further trials were performed in SMEs. The results of the iteration steps demonstration and evaluation according to Peffers et al. are presented in Sect. 6. As the DSR provides, an iterative return for further development is not performed. The results of the investigations in the test environment SME are the basis for a final discussion of the VSM 4.0 plus method, which leaves complementary extensions for further research.

5 Enhancing VSM to value stream mapping 4.0 plus

5.1 Evolution of value stream mapping

The classic VSM includes the rough information flow of a specific production process but does not consider the information management itself. Nowadays, false or non-existent data and information management can also lead to waste, e.g., product recalls due to erroneous quality data or manual data input, although data is available digitally. Due to its age, VSM does not consider digitalization and industry 4.0 aspects. For this reason, Meudt et al.  [20] enhance the VSM to the “value stream mapping 4.0” and introduce new symbols and their values. Figure 2 illustrates the enhancement of one process step from the classic VSM.

Fig. 2
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Value stream mapping 4.0 according to Meudt et al. [20]

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Meudt et al. disaggregate the rough information needed for a single process step into multiple data points. Within VSM 4.0, every data point can be characterized with the following properties: frequency and type of recording and actual value. Furthermore, the VSM 4.0 depicts the storage medium (e.g., paper, employees, software systems as enterprise resource planning), the direction of the information flow (from the storage medium to the process or vice versa), and the usage of a data point (e.g., for shopfloor management (SFM) or process control). In its current state, VSM 4.0 only focuses on a more business perspective, so the methodology lacks technical implementation, e.g., the communication protocol. Based on this, Lewin et al.  [21] enlarge the VSM 4.0 with properties that faces technical implementation, data processing, interfaces, and data security (see red enhancements in Fig. 3).

Fig. 3
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Value stream mapping 4.0 according to Lewin et al. [21]

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According to DIN EN 62264 [28], Lewin et al. integrate on which layer on the Reference Architecture Model Industry 4.0 (RAMI 4.0) the data point is located. Moreover, data transfer (manual/paper-based, by wire, wireless, verbal, and visual), data processing (none, central, decentral), human interactions within the system, and data exchange between systems is integrated. Besides, Lewin et al. exchange the dimension storage medium, as it is used in the approach of Meudt et al., with the more differentiated dimensions "local non digital data", "local digital data", and "connected digital data". However, the added depth of information still gives insufficient details on data processing. In addition, new introduced symbols indicate potential security issues and inadequate data within the information flow. Although Lewin et al. integrate properties for technical implementation issues, some essential properties are missing to enable an adequate flow of single data points, e.g., the interface between data transmission and the data sink (ERP, MES). Therefore, the following section introduces the VSM 4.0 plus that focuses on a more technical perspective.

5.2 Value stream mapping 4.0 plus

The VSM 4.0 plus integrates all properties listed before and enlarges the VSM 4.0 of Lewin et al. with technical properties, so both production and software engineers can use this tool. Figure 4 introduces the VSM 4.0 plus, where the orange parts stand for the newly added building blocks (all usable symbols and abbreviations used are shown in the appendix).

Fig. 4
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Value stream mapping 4.0 plus

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The VSM 4.0 has some shortcomings (SC) which are presented below. Subsequently, it is shown how the VSM 4.0 plus meets these shortcomings.

SC 1: Lack of technical data point definition.

Besides the frequency of recording, the VSM 4.0 plus adds the necessary accuracy for recording a data point to avoid possible processing errors through rounding. In addition, the corresponding unit must be defined to avoid further miscommunication (e.g., temperature units degree celsius and kelvin). Furthermore, the VSM 4.0 plus integrates the communication protocol as property.

SC 2: Unclear Type of recording.

In both versions of the VSM 4.0, the definition of the property Type of recording is unclear. Meudt et al. differ between automated, semi-automated, and manually (independent of the data flow direction), while Lewin et al. propose the values manually and automatically for data input as well as analog and digital for data output. For example, an operator wants to set up a machine by entering the machine’s setting data that is stored on an RFID card. The operator manually places the card on the machine’s interface, and the machine automatically starts setting up the desired parameters. While the operator needs to perform a manual task by placing the RFID card on the machine’s interface, the required data points are provided automatically. In the VSM 4.0, a new value mt (= manual trigger) was added to close this issue. In addition, the symbols Levin et al. introduced to describe the human–machine interface were removed from VSM 4.0 plus since they give no exact interface specification. Instead, the VSM 4.0 plus provides a new dimension Interfaces that is subdivided into the technical and human interface (see Fig. 5). Thus, interfaces now can be mentioned precisely.

Fig. 5
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Dimension interface

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SC 3: Insufficient differentiation between transmitting and storage medium.

In the VSM 4.0 of Lewin et al., transmitting and storage media are not differentiated. The RFID chip in SC 2 for setting up a machine is not a data storage in terms of a database or system but a transmitting medium. Another example is the medium "paper" with a printed QR or barcode. After finishing a production order, all information regarding this production order is condensed into a QR code and printed out on paper. The operator then carries the paper to an ERP terminal and scans the QR code, transmitting all information to the software system. Then, the operator discards the paper. For this reason, the VSM 4.0 plus provides the new properties Transmitting medium and Type of recording to cover those applications.

SC 4: Unconsidered data input to storage or software system.

The VSM 4.0 covers the data input and output only on the machine/process side and does not include the storage/software system. Consider the example in SC 3, where an operator transfers information about a production order to the ERP system. In this example, the operator scans a QR code, but other methods (e.g., manually, directly from the machine) are possible. For this reason, the property Type of recording (system) was established. To continue, the frequency of importing data points is to factor, especially when it differs from the frequency of recording from the source, e.g., in the case of pre-processing. Therefore, the VSM 4.0 plus integrates this property.

SC 5: Misleading meaning of the terms analog and digital.

From a technical perspective, the definition of the terms analog and digital may differ from the business perspective. An example is the representation of an analog value on a digital display. From a technical perspective, the original format is essential. The properties Type of output (electronic display, analog tachometer, or print) and Digitally available (yes/no) were added to avoid misapprehensions.

SC 6: Unconsidered management of data processing itself.

The VSM 4.0 focuses on waste reduction within a specific production process, considering data and information in the context of industry 4.0. Improving data processing and management, i.e., efficient data gathering, processing, and information generation, is not an element of the VSM 4.0. The VSM 4.0 plus provides the first indicator by integrating the Processing time data point property as a key performance indicator (KPI). As an outlook from the technical perspective, the VSM 4.0 plus can be enhanced vertically to depict the data transfer for reaching lean data management.

SC 7: Insufficient representation of data processing.

The VSM 4.0 provides only dimensions for the data storage and the usage of data points, while data processing is not considered. Although Lewin et al. introduce a magnifier as the symbol for data processing, no possibilities for an exact specification of this data processing were provided. Furthermore, the VSM 4.0 does not differentiate between pre- and post-processing. The VSM 4.0 plus adds pre- and post-processing to the storage dimension and includes three sub-dimensions, namely server and device infrastructure, cloud infrastructure, and human interaction, that specify the location of the data’s pre- and post-processing as also the data storage (see Fig. 6). In the application of the method, any number of platforms can be added to the dimensions pre- and post-processing without limitations. The introduction of the three platform types and the human interaction are also applied to the storage dimension. They are meant to be more of a technical framework than limited to a specific number. Moreover, the method is capable of mapping the combination of application and platform on which the application runs. The method illustrates which applications use which resources. This can reveal potential waste caused by error-prone cross-platform interfaces.

Fig. 6
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Dimensions pre-/post-processing and storage

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SC 8: Low detail of data usage.

The VSM 4.0 provides the data point’s usage roughly, e.g., shopfloor service. Here, the VSM 4.0 plus offers more details by differentiating between the Type of Use and the Application (see Fig. 7). While the type of use represents the usage from the VSM 4.0, application specifies the usage. An example is the presentation of the KPI “overall equipment effectiveness” (OEE) (Application) within the shopfloor management (Type of Use).

Fig. 7
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Dimension usage

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Summarized, VSM 4.0 plus offers a comprehensive description of the data flow and processing by enhancing VSM 4.0 with more technical properties. In particular, with VSM 4.0 plus, a more detailed description of single data points is possible by considering the unit or accuracy. In addition, technical information regarding the used protocol or the type of input and recording is given. Finally, VSM 4.0 plus provides more details for data processing through enhanced dimensions and adds input information to software and storage systems.

5.3 Adaptions in the execution procedure

Meudt et al. and Lewin et al. adapt the execution procedure of the traditional value stream analysis to the industry 4.0 extension. Both approaches involve performing the classic value stream analysis at the beginning and similar steps to perform the extended contents. Table 1 illustrates a comparison of the two approaches.

Table 1 Comparison of the procedures
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The execution of the VSM 4.0 plus method is not fundamentally changed and remains based on the previous procedure. The approach results from the combination and a content expansion of the steps of both. The overarching approach is based more on Meudt et al., as the tool is primarily conceived as a tool for analysis and not for design purpose. The adapted approach to implementation is illustrated in the following Fig. 8. The next chapter demonstrates the VSM 4.0 plus within a real-world application.

Fig. 8
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Execution procedure of VSM 4.0 plus

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6 VSM 4.0 plus within a real world application

This approach is not only to introduce a new lean and industry 4.0 focused tool but also to critically question its functionality and applicability at real-world manufacturing sites. Therefore, the VSM 4.0 plus method has been tested among various environmental conditions. This included four small and medium enterprises as well as a learning factory. The selected companies represent both plastics and metal processing companies and a non-processing, pure assembly company. Regardless of their industry, the SMEs tested differed in particular in terms of their operating- and information-technological infrastructure as well as in their overall company size. For the initial application of the method, contents, procedure and the overall objective of the method are first presented to selected companies’ process and IT-infrastructure specialists in a first meeting separate from the actual implementation. In a further appointment, the method is performed on a sample value stream selected by the company. The authors recommend bottleneck or high-runner value streams as selection criteria. During the actual application, the participating specialists were actively supported and guided by the authors. Afterwards, the results are prepared and discussed by the participants.

In the following, observations made during the performance of the trials in different industrial environments are summarized. This subsection focuses on the observed capabilities during the application. Furthermore, this section provides a hands-on application of the VSM 4.0 plus method for the use case “OEE dashboarding” in the learning factory.

6.1 Capabilities of VSM 4.0 plus

During the application in various environments, it was shown that the method is able to represent great complexities in informational and operational technology (IT/OT), machinery, and plant infrastructure holistically. Even in the case of highly heterogeneous approaches for data processing and aggregation within just one production system, the method now includes tools to manage and map every kind of data and information flow. Immediate data processing via OPC UA is just as possible as information transfer on sight or through paper, as it is still often used in practical industrial environments. The VSM 4.0 plus method displayed each data point and its processing in detail. Both raw machine data points and other production-relevant information that are provided by the processes are displayed appropriately. Each step of the further processing was traceable and can be fully understood through the added dimensions - every data movement is displayed. The interaction between processing software and processing platform, as well as with used interfaces, became clear. Because of the supplementation, interfaces between analog (e.g., paper) and digital (e.g., MES) media are taken into account. The method masters the interfaces’ complex synergies sufficiently and comprehensively due to the introduced interface description from shortcoming three. Furthermore, the dimension of usage shows the potential lack of use of aggregated data. Data graveyards, further processing inconsistencies, and media breakage are revealed and made transparent. The lean tool of kaizen can be applied appropriately [20]. After the implementation of the method in workshops, discussions were held with the participating SMEs about achieved results. It emerges that the results and identified potentials from the VSM 4.0 plus method and kaizen are similar to considerations regarding further development potentials that have arisen internally by the SMEs in the meantime. This technical consensus shows that the tool can uncover potentials without deep understanding of local processes. The results of the method lead to approaches for use cases to be implemented and also transparently show technological prerequisites and framework conditions. Comparing the results of the VSM 4.0 plus with the possibilities of the previous VSM 4.0 versions, the following circumstances in the tested production environments could not have been mapped in detail. Accordingly, the VSM 4.0 plus made it possible to identify and also to illustrate extensive and collaborating OT-backend infrastructures with protocol translators, data platforms and various applications with corresponding interfaces, combinations of used applications and their running platforms as well as the depiction of interfaces between applications and non-digital verbal or written information and data. The VSM 4.0 plus now offers a common tool for software and production engineers by comprehensively considering both domains in their holistic complexity. On the basis of the findings obtained in the industries tested, the method proves to be industry-neutral. Complexity and effort decrease when process stations are similar and repetitive, such as in assembly lines tested here. It can be seen that although the domain-specific content of the information differs, the technical data acquisition is independent of whether the machine is a plastics or metal processing machine. Even for the use case of automated assembly processes, the data acquisition is almost identical to that on the previously mentioned machines. In most cases encountered, machine data are provided by PLCs. At this point, the tracking of data processing begins across various dimensions mapped in the VSM 4.0 plus regardless of the industry- or manufacturing process-specific content. Furthermore, different manufacturing technologies are used even within one domain. Thus, the method shows to be capable to consider technologies for machining, forming, but also for heat treatment during the tests within the metalworking industry. A similar variety of technologies to cover was also found in plastics processing.

6.2 Application of VSM 4.0 plus

For illustration and application purposes, the existing value stream of the already introduced learning factory of the chair of production systems at the Ruhr-University Bochum is used. The value stream established in the production of the learning factory includes several process steps for manufacturing a demonstration product. These include several machining production processes, such as milling, sawing and turning, as well as assembly processes. The learning factory mirrors the heterogeneous production infrastructure similar to historically grown SMEs. The learning factory maps a heterogeneous production system combining many different data processing and aggregation approaches. Immediate data processing via various machine communication protocols is just as possible as information transfer on sight or through paper, as it is still often used in industrial practice. Since the key performance indicator OEE is widely spread in the manufacturing industry, OEE is represented in the learning factory, either [29]. The calculation of the chosen production-focused indicator OEE is done according to Nakajima  [30]. For the exemplary application, one process step of the value stream is illustrated in Fig. 9.

Fig. 9
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Application of VSM 4.0 plus method for the use case OEE in a learning factory

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As the advanced method for this exemplary case shows, the turning process has three interfaces, both technical and human. Data, provided through the communication protocol Profinet, is pre-processed by an OPC UA server before it is stored in a SQL database. In addition to machine data collection through Profinet, data is collected manually via the MES terminal or via the medium paper. While data recorded via the MES terminal is stored directly in the MES database, data recorded via paper require an interface. In this case, the interface box in Fig. 9 describes the same kind of interface. The illustration shows the combination of the application and its running platform. Both the MES and the SQL database are running on the identical virtual machine. In contrast, the dimension post-processing shows a different platform application combination. Furthermore, it shows that all data provided by the process is also accessed by the shopfloor management usage dimension. Referring to a possible comparison between achievable results by VSM 4.0 plus and the previous VSM 4.0 versions (see Sect. 6.1), the chosen color coding should be noted here. Thus, the grayed areas represent the information that would be represented using VSM 4.0 according to Meudt et al. which again leads to the shortcomings discussed in Sect. 5.

The analysis of the graphical expression of the VSM 4.0 plus method of the exemplary process by the kaizen method, as already introduced as a tool in the domain of lean production, shows potentials for improvements - by making the data flows transparent, this application shows redundant data storage in the MES and SQL database as well as still necessary human interactions, such as the paper-based data recording of some data points, which are entered manually into the MES in a laborious process. If this analysis is seen as an impulse for the implementation of improvement potentials, databases should be consolidated and redundancies reduced, also in order to avoid media breaks and transmission losses due to interfaces. In order to implement the often pursued overriding goal of paperless production, concrete need for action can be derived from the analysis.

7 Discussion

The VSM 4.0 plus method proves to be a detailed and comprehensive tool that is able to depict the interaction of machinery, manual processes and IT/OT infrastructure in the background holistically. It is able to detect information technology waste [20, 31] and redundancies even at the level of pre- and post-processing. The higher grade of detail and information density lead to higher complexity to be managed. The implementation of the new method requires a highly qualified interdisciplinary team that represents both production and information technology knowledge. During application in real production environment, the method proved to be non-intuitive. Without a high level of methodological competence (expressions, symbols etc.) of the user group, the method proves to be time-consuming and partly sluggish. In particular, the interface description from analog to digital environments turns out to be rather bulky. In practical use, however, it has been shown that similar interfaces can also be represented by only one correspondingly labelled interface box (see *1 in Fig. 9). By extending the method to include ways of representing technological depth, the method proves to be partially overloaded with instruments and mapping possibilities when it comes to application in smaller production systems. In scenarios of this kind, the user tends to complicate and overthink what are actually simple processes. Despite the high level of methodological and technological detail provided, simple processes can also be displayed in a simple and full transparent manner. As in Sect. 6.1 described, the method is capable to display information flows in even poorly digitized shopfloors. However, as soon as information in a production system is not provided according to a rule communication, value streams and production processes do not follow a predefined logic, the method cannot be used properly. The method’s application in a micro-enterprises, which is characterized and dominated by manual non-automated processes, has raised these weaknesses. Leaner methods are clearly more appropriate in these cases. Though, the application in an extensive production system can be even more complex. Because the method was only tested in SMEs, it is not possible to assess whether more extensive production systems can be clearly represented. Therefore, the VSM 4.0 plus method should also be tested in large companies in further studies.

VSM 4.0 plus was tested exclusively in SMEs. This revealed that required competencies for implementation are potentially not available in this kind of application scenarios so that a sort of moderator with required competencies is needed. In summary, especially in its application, the method proves to be very challenging - both in its technical and methodological demands. In order to tackle this overarching weakness, it is necessary to determine whether the required technical and methodological content should be prepared and participants trained in a qualification event prior to use. A learning factory with an established exemplary value stream, as already described and used in this contribution for the initial tests, may be suitable as location for such a qualification event. In any case, it is recommended to initially focus on one product line or value stream in order to consolidate and compare the results across production in retrospect. With regard to the research question, it can be stated that the method is capable of representing the information and communication technologies used on the shopfloor in detail, also in terms of their synergies. However, the gain in information that this method makes possible is accompanied with a high level of implementation complexity which has to be managed.

8 Conclusion and outlook

Establishing the flow of data and information for enabling beneficial shopfloor services is one core topic of industry 4.0. Therefore, tools and methods that support domain and software engineers in developing and establishing a data and information flow are required. This contribution extends the VSM 4.0 due to identified shortcomings, especially for technical details. The method is independent of the underlying production process, as real-world applications within the domain of plastics processing and metal forming evidence.

In the case of planned technical implementation of various IIoT and industry 4.0 products and technologies available on the market, it is unavoidably necessary to previously identify the technical boundary conditions of the shopfloor as well as of the IT/OT backend infrastructure. Taking up previous results of applying the lean principle tool value stream analysis to industry 4.0, this approach is intended to add technological information depth.

Based from this intention, shortcomings from the previous results are identified and improved by appropriate additions. The real-world trial of the VSM 4.0 plus method in production environments dominated by SMEs showed its potentials in the intended use. VSM 4.0 plus provides a new holistic approach for the recording of information technology, machine, and process infrastructure. However, weaknesses in micro-enterprises and the method’s complexity also became apparent. The method lacks intuitiveness due to the extended scope, so that the user group must represent interdisciplinary and even expert knowledge Therefore, due to the high complexity of the application, a qualification concept may prove useful. In addition, it must be investigated to what extent the high complexity and scope can still be methodically controlled even in extensive production systems and companies.