# Reference Model for Product-Service Systems with an Use Case from the Plating Industry

Christian Schiller, Mike Freitag, Alexander Leiden, Christoph Herrmann, Alexander Gorovoj, Patric Hering, Sascha Hering

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Christian Schiller, Mike Freitag, Alexander Leiden, Christoph Herrmann, Alexander Gorovoj, et al. Reference Model for Product-Service Systems with an Use Case from the Plating Industry. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2022, Gyeongju, South Korea. pp.335-342, 10.1007/978-3-031-16407-1_40. hal-05386069

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# Reference Model for Product-Service Systems with an Use Case from the Plating Industry

Christian Schiller<fnref n="1" />(✉), Mike Freitag<fnref n="1" />(✉), Alexander Leiden<fnref n="3" />(✉), Christoph Herrmann<fnref n="3" />(✉), Alexander Gorovoj<fnref n="2" />, Patric Hering<fnref n="4" />, and Sascha Hering<fnref n="4" />

**Abstract.** In recent years, digitalization has affected more and more industries to an increasing extent. As a result, new approaches to develop innovative service offers are becoming increasingly relevant. In the article at hand, a reference framework for the development of product-service systems is presented and validated by way of an application example. The reference framework has five levels, which cover both the cyber-physical production system and smart service. Each of the five levels is made up of six development steps, going from the early development phase of target group definition through to the integration of the finished solution. The reference framework thus combines elements of Smart Service Lifecycle Management and the CRISP DM data mining model.

**Keywords:** Product-service systems · Smart service · Service business model · Cyber-physical production system · Service lifecycle management · Service engineering · SME

## 1 Introduction

For years, advances in digitalization have provided more and more opportunities for the further development of physical products into cyber-physical systems that can communicate with other products and with the internet, and enable the provision of new services [1]. The smart Product Service Systems (sPSS) created in this way offer a whole new range of potential in terms of value creation, such as the provision of data-based and intelligent services, which are also known as smart services [2]. Characteristic for such systems is their customer-oriented solution approach aimed at generating genuine added value for individual users [3]. They are also characterized by a high degree of complexity, dynamism and their multi-dimensional nature [4].

<footnote n="1">¹ Fraunhofer Institute for Industrial Engineering IAO, Nobelstr. 12, 70569 Stuttgart, Germany
christian.schiller@iao.fraunhofer.de</footnote>

<footnote n="2">² Institut für Arbeitswirtschaft und Technologiemanagement IAT, Universität Stuttgart,
Nobelstraße 12, 70569 Stuttgart, Germany</footnote>

<footnote n="3">³ Chair of Sustainable Manufacturing and Life Cycle Engineering, Institut of Machine Tools and Production Technology (IWF), Technische Universität Braunschweig, Langer Kamp 19b,
38106 Braunschweig, Germany</footnote>

<footnote n="4">⁴ Airtec Mueku GmbH, Im Ganzacker 1, 56479 Elsoff-Mittelhofen, Germany</footnote>
One of the key benefits of smart services is that they enable a significant improvement in customer engagement. This allows for much better anticipation of customer requirements and more targeted and efficient use of the company's own resources [5]. Smart services also give providers the opportunity to expand their service portfolio and create new business models [6].

However, the development of smart services still poses significant challenges for companies. For instance, in a recent business survey, 55% of companies indicated a need for support in developing new smart services [7]. 53% needed support in developing appropriate business models. Well-defined development processes to help develop smart systems are also desired by many companies, but are not commonplace as yet [8]. As a potential solution approach, this publication presents a six-stage reference framework for the development and configuration of new smart services. After a theoretical derivation and presentation of the approach, it is validated by means of an application example and put into practice. The approach presented was developed as part of a research project on electroplating and therefore focuses on this topic.

## 2 Procedure Model for the Product-Service System

To support the development and configuration of product-service systems, a six-level reference framework was developed, which in turn was broken down into five individual layers (Fig. 1). The inner four layers describe the cyber-physical production system (CPPS) of the electroplating plant (introduced in [9] and [10]) and the outer layer describes the surrounding service by way of service engineering [11–13]. The layers also indicate the degree or the state of the digital transformation of a product-service system. The dots here show the layers affected in the current development step. The reference framework combines elements of Smart Service Life Cycle Management and the CRISP DM model [14], thus bringing together the two spheres of service and CPPS in one reference framework. A detailed presentation of this reference framework can be found in Leiden et al. [15]. Only a brief description is provided in this paper.

The physical system, i.e. the corresponding elements of the electroplating plant, constitutes the core of the system. From this, data are collected in the second layer by means of sensors. These data are analyzed in the next layer of the cyber system, in either a data-based or model-based manner. The decision-support layer represents the transition to service: at this point, interaction between people and IT systems begins. These systems must be made appealing to users through appropriate forms of visualization, so as to achieve a high level of acceptance. The final layer is the service, which builds on the previous layers and incorporates the requirements from operations into the service.

As well as providing methodological support for the development of smart services, the reference framework can measure the current extent of their digital transformation. Upon assessment, the more layers a user can cover with their systems, the more advanced the current status of their digital transformation.

In the following, the individual steps of the reference framework are explained in detail from both a service and CPPS perspective, and the special features are presented.

**Definition of the target group (1)** During the first step, the customer target group is defined. Who will the new smart service and the corresponding business model address?
<figure><img src="image_3.png" /><figcaption>Fig. 1. Reference framework for the development of product-service systems (based on [15]).</figcaption></figure>

According to Osterwalder and Pigneur [16], it is necessary to differentiate between target groups if their needs require and justify an individual offer. Can they be reached through different distribution channels, do they require different relationship types, do they have significantly different levels of profitability, or are they willing to pay for different aspects of an offer? In electroplating, depending on the service concept, a distinction can be made, for example, between in-house and contract electroplating or between small, medium and large companies. Further target group definitions can be made in terms of the respective company's liquidity or in the differentiation between “makers” and “outsourcers” (make-or-buy decision). The physical system in question is derived from the target group, as it is highly dependent on it. For example, larger companies with series production require completely different equipment than small, highly flexible contract electroplating shops. While in the case of the former, the focus is on integration into the production system that is as efficient as possible and fits into the cycle time, contract electroplating requires adaptable systems that can easily adapt to meet current needs with the least possible effort.

**Development of the use case (2)** The second step requires the establishment of a specific use case for the previously defined target group. It should outline how the service has been provided to date (if already in place), how often it has been provided, and what the targets are. In addition, one or more unique selling points of the existing business model idea need to be clarified. This step also involves defining the specific value proposition. The benefits to the customer of the new or enhanced smart service are clarified, along with the specific customer problems that can be solved. The use case and the value proposition also result in the requirements for decision support and thus the interface with the CPPS. At this early stage, the requirements from the service can be translated very easily into the CPPS environment. In particular, if mixed reality approaches are to
be used for decision support in view of a smart augmented reality service, the specific features of these technologies [17] must be given appropriate consideration during this step.

**Definition of requirements (3)** Based on the previous steps, the requirements from the service and CPPS point of view are finalized in order to develop the prototype. The methods to be used in the cyber system are determined and, if necessary, different variants for the prototypes are proposed. The decision to use a data-based or model-based approach significantly affects the requirements for data collection systems. Thus, the data collection system must be designed accordingly and its integration within existing IT systems must be ensured. This is particularly important with regard to the final integration step, as the IT systems can differ enormously. In electroplating, the plant technology and related IT are highly operator-specific compared to other industries (e.g. machine tools).

**Business modeling (4)** A well-developed business model is an important part of complete service engineering, and the starting point for the subsequent integration process [18]. Thanks to its easy-to-follow structure, Osterwalder & Pigneur's business model canvas [16] is of particular interest, especially for start-ups and smaller companies. An added advantage is that a defined business model canvas can be further developed into a service business model canvas at any time, if required, and if sufficient data are available.

**Development of a prototype (5)** The aim is to develop the smart service. A smart service like this is designed and developed step by step using service engineering [2]. During the process, the product, process and resource model of a smart service are first designed and prototyped. The prototype is then tested in a test environment at a Technical Readiness Level (TRL) [19] of four to five [20]. To this end, the CPPS is fully set up as a prototype in an appropriate test environment, e.g. on a research partner's site. Either the same test environment can be used for the service, or a separate one, allowing the services to be evaluated in a particularly simple way. However, when using different test environments, it must be ensured that the environments are appropriately compatible and that the interfaces between the CPPS and service sphere can be tested intensively. If no test environment is available, productive systems at customer sites may also be used. However, it should be noted that the systems to be tested are still in development and if they are used by the customer directly, they risk jeopardizing acceptance among potential customers given that the systems are not yet functional.

**Integration of the Smart Service (6)** The final step in the procedure is the integration of the developed Smart Services within the operational systems. The service is integrated within the process landscape of the parties involved, and appropriate resources are provided. The basis is the business model developed to this end during the previous step. The CPPS is transferred from the prototype system to operational IT systems and installed at the customer's site. Any additional hardware that may be required will be introduced along with the corresponding software. The decisive factor compared to the prototype system is the achievement of a high TRL of between 8 and 9. This usually involves more testing of the hardware and software systems to be used, but ensures that the system is ready for use.
# 3 Use Case from the Electroplating Industry

In this chapter, part of the approach presented above is validated by means of a use case together with the German company Airtec Mueku GmbH. The company in the use case described is a supplier of exhaust air purification technologies, which are used, among other things, in electroplating. The aim is to add digital components to the classic service portfolio, thus enhancing value creation.

The first step in the reference framework is to define the target group. In the use case presented, there is a major interface with the second step, i.e. the development and scope of the use case. This is specifically due to the fact that there was no deviation in the target group from the existing product portfolio. Rather, the focus was on extending the business model, which ultimately characterizes the use case. Additional service offers for existing customers are intended to increase sales and enhance customer satisfaction. In addition, building customer loyalty is a key feature of the new digitally-supported offer. Extending the business model to include further target groups is not the main focus. Instead, increased and more targeted use of data, as well as the use of augmented reality and other remote solutions are intended to achieve, among other things, better planning capability and resource efficiency, optimized spare parts management and optimized error analysis. This affords the customer increased machine availability and a higher level of safety. In addition, positive effects can be expected in terms of CO2 emissions. Furthermore, the provider's performance becomes more transparent for the customer, bringing clear benefits for both parties.

During the third step of the reference framework, the requirements for the product-service system to be developed are defined. In the context of this publication, the focus is on eliciting the requirements for the business model. In principle, several approaches may be considered in order to back up the use case outlined above with a business model. For instance, performance-based payment, usage-based payment, subscription models, guaranteed availability or external condition monitoring could be considered. The corresponding business model approaches were reviewed and analyzed as part of a customer survey. The analysis revealed a clear preference among customers for external condition monitoring combined with predictive maintenance.

Once requirements have been elicited, business modeling is used to substantiate the use case. The four-step procedure to develop a business model for small and medium-sized enterprises (SMEs) from [21] was used as a guide. Unfortunately, the substantiated business model cannot be presented here.

At the time of writing, the use case has reached the fifth step of the reference framework, i.e. development of the prototype for the new product-service system and the associated smart service. To this end, three scenarios were developed and visualized with the aid of process models. The process models were created using the Service Blueprinting method, as the customer perspective is particularly emphasized here. The design of the processes was based closely on the results of the customer survey (see step three of the use case). In addition, several workshops were held with the managing director, the service director, representatives from marketing, and experts from service engineering to finalize the processes.
The respective scenarios address the different levels of willingness to pay among various customer groups. Thus, a distinction is made between cost-focused, standard-focused and quality-focused customers. Both the costs and the scope of service provision differ in each case. The first scenario addresses more cost-conscious customers and offers only a basic package of services and digital technologies. The second scenario is focused on standard customers and has extensive use of technologies for service delivery. In particular, the use of AR technology plays a role here. The third scenario is the most cost-intensive. In return, there is an even more intensive use of digital technologies and service delivery here. This also makes it possible to significantly extend the warranty of the machines compared with the first two scenarios (Fig. 2).

<table><caption>Fig. 2. Differentiation of the different scenarios.</caption><thead><tr><th></th><th>Scenario 1</th><th>Scenario 2</th><th>Scenario 3</th></tr></thead><tbody><tr><td>Low-priced for the customer</td><td>+++</td><td>++</td><td>+</td></tr><tr><td>Scope of service delivery</td><td>+</td><td>++</td><td>+++</td></tr><tr><td>Customer support</td><td>++</td><td>+++</td><td>+++</td></tr><tr><td>Warranty</td><td>++</td><td>++</td><td>+++</td></tr><tr><td>Digital technologies available</td><td>+</td><td>++</td><td>+++</td></tr></tbody></table>

The process models also form the basis for the development of the resource model. With its help, it is possible to calculate as accurately as possible the human, intangible and material resources required to successfully deliver the new solution.

The integration of the Smart Service as step six of the reference framework will occur at a later stage in the project.

## 4 Summary

In the context of this publication, a six-step reference framework for the development of new smart services was first presented. This comprises five layers, where the inner four layers represent the cyber-physical production system of an electroplating plant, and the outer layer represents the surrounding service. As such, this combines elements of Smart Service Lifecycle Management and the CRISP DM model. Not only does the reference framework provide methodological support to develop smart services, it also allows companies to measure the extent of their digital transformation. As the number of layers covered in the model increases, so does the system's degree of digitalization. When developing the reference framework, specific attention was also paid to practical applicability for SMEs.

In the second part of the publication, the reference framework is put into practice. The company from the use case produces peripheral systems for the electroplating industry, and would like to build better, more regular relationships with existing customers, perform remote diagnostics, intensify data usage, and optimize sales by means of a digitalized service offer. With the help of the reference framework, it was possible to develop
a promising solution concept that can be tailored to several customer types, each with different requirements in terms of quality and cost. This new solution has not yet been put into practice but the integration is planned in the near future. Consequently, a final assessment of the reference framework presented for the case at hand is still pending but is expected soon.

**Acknowledgements.** This work has been partly funded by the German Federal Minis-try of Education and Research (BMBF) through the Project "SmARtPlaS (No. 02K18D112). The authors wish to acknowledge the Commission, the Ministry and all the project partners for their contribution.

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