Introducing a methodology for smartification of products in manufacturing industry

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Procedia CIRP 00 (2017) 000–000 Procedia CIRP 81 (2019) 228–233

52nd CIRP Conference on Manufacturing Systems 52nd CIRP Conference on Manufacturing Systems

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Introducing a methodology for smartification of products in manufacturing 28th CIRP Design May 2018, Francein manufacturing Introducing a methodology forConference, smartification ofNantes, products industry industry a a a, a Günther Schuh , Violett Zeller , Jan Hickingand *, Anne Bernardy A new methodology to analyze the functional physical architecture of a a, a Günther Schuh Violett Zeller , University, Jan Hicking *, Anne Bernardy for Industrial Management, FIR at RWTH Aachen Campus-Boulveard 55, Aachen 52074, Germany existing Institute products for ana,assembly oriented product family identification a

a * Corresponding author. Tel.: for +49-241-47705-513 ; fax: +49-241-47705-199. E-mail address:Campus-Boulveard [email protected] Institute Industrial Management, FIR at RWTH Aachen University, 55, Aachen 52074, Germany

Paul Stief *, Jean-Yves Dantan, Alain Etienne, Ali Siadat

* Corresponding author. Tel.: +49-241-47705-513 ; fax: +49-241-47705-199. E-mail address: [email protected]

Abstract

École Nationale Supérieure d’Arts et Métiers, Arts et Métiers ParisTech, LCFC EA 4495, 4 Rue Augustin Fresnel, Metz 57078, France

*Abstract Corresponding author. Tel.: +33 3 87 37 54 30; E-mail address: [email protected]

Smartification and digital refinement of products to enable the design of smart ones is a pivotal challenge in the manufacturing industry. Companies fail to design smart products due to missing knowledge of digital technologies and their integral part in product development Smartification digital refinement of products enable the the derivation design of smart onesfunctions is a pivotal challenge in thethrough manufacturing processes. Thisand paper presents a methodology thattoenables of digital for smart products selected industry. cases in Companies fail to design smart products due to missing knowledge of digital technologies and their integral part in product development manufacturing usage. We develop a morphology that consists of digital functions for smartification. In this context, we explained and derived Abstract processes. Thisbypaper presents a methodology thatproducts enables in thethederivation of digital functions for smart products cases ina characteristics a set of examples regarding smart manufacturing industry. Our methodology reduces through the time selected spent initiating manufacturingproject usage.with We the develop aonmorphology that consists of digital functions for smartification. In this context, we explained and derived focus smartification. Indevelopment today’s business theregarding trend towards product and customization is unbroken. Due reduces to this development, need ofa characteristics by aenvironment, set of examples smartmore products in thevariety manufacturing industry. Our methodology the time spentthe initiating agile and reconfigurable systems emerged to cope with various products and product families. To design and optimize production development project withproduction the focus on smartification. © 2019as The Authors. Published Elsevier Ltd. This is an open access articlemethods under the BY-NC-ND systems well as to choose the by optimal product matches, product analysis areCC needed. Indeed,license most of the known methods aim to © 2019 The Authors. Published by Elsevier Ltd. (http://creativecommons.org/licenses/by-nc-nd/3.0/) analyze a product or one product family on the physical level. Different product families, however, may differ largely in terms of the number and © 2019 The Authors. Published by Ltd. This is license an open access article the CC license This is an open access article under the BY-NC-ND (http://creativecommons.org/licenses/by-nc-nd/3.0/) Peer-review under responsibility of Elsevier the CC scientific committee of the 52nd CIRP under Conference onBY-NC-ND Manufacturing Systems. nature of components. This fact impedes an efficient comparison and choice of appropriate product family combinations for the production (http://creativecommons.org/licenses/by-nc-nd/3.0/) Peer-review under responsibility of the scientific committee of the 52nd CIRP Conference on Manufacturing Systems. system. A newunder methodology is proposed to analyze existing products in view ofConference their functional and physical Systems. architecture. The aim is to cluster Peer-review responsibility of the scientific committee of the 52nd CIRP on Manufacturing Keywords: Smart products; digital technologies; smartification; product development process these products in new assembly oriented product families for the optimization of existing assembly lines and the creation of future reconfigurable assembly Based on Datum Flow Chain, the physical structure of theprocess products is analyzed. Functional subassemblies are identified, and Keywords:systems. Smart products; digital technologies; smartification; product development a functional analysis is performed. Moreover, a hybrid functional and physical architecture graph (HyFPAG) is the output which depicts the similarity between product families by providing design support to both, production system planners and product designers. An illustrative 1. Introduction models are applicable, such as subscription or product-as-aexample of a nail-clipper is used to explain the proposed methodology. An industrial case study on two product families of steering columns of service [7]. approach. As new domains form and diffuse, new thyssenkrupp Presta France is then carried out to give a first industrial evaluation of models the proposed 1. Introduction models are applicable, such as subscription or product-as-aDeveloping smart products is a big challenge, especially for requirements, new customer demands and new technologies © 2017 The Authors. Published by Elsevier B.V. service models [7]. As new domains form and diffuse, new small and medium-sized companies (SME), who find must be faced during a product’s development process. While Peer-review undersmart responsibility scientific committee of the 28th Design Conference 2018. Developing productsofisthe a big challenge, especially for CIRP requirements, new customer demands and new technologies

themselves at a substantial lack in approaches and methods [1]. mechanical engineers are specialized in technologies such as small and medium-sized companies (SME), who find must be faced during a product’s development process. While domains sensors and Human-machine-interfaces, data processing and themselves at a substantial lack in approaches and methods [1]. mechanical engineers are specialized in technologies such as diffused in product development processes. Domains such as IT-infrastructure are unknown fields of expertise. Taking into In the last decades new and SME-unknown technical domains sensors and Human-machine-interfaces, data processing and mechanics, informatics and electronics are not sufficient to consideration today’s smart products and future ones, entirely diffused in product development processes. Domains such as IT-infrastructure are unknown fields of expertise. Taking into create competitive products for discerning customers [2]. new characteristics will be important, as Rijsdijk and Hultink mechanics, informatics and electronics are not sufficient to consideration today’s smart products andmanufactured future ones, entirely 1.Digital Introduction of the that product range and characteristics and/or noted characteristics like a certain level of autonomy, protechnologies enable smartness in products and increase create competitive products for discerning customers [2]. assembled new characteristics will be important, as Rijsdijk and Hultink in this system. In this context, the main challenge activity, humanlike interaction and personality are crucial in to the capabilities and value of physical components [3]. Digital enable smartness in products and increase noted that and characteristics like a certain level autonomy, proDue technologies to these, the smart fast development the domain of modelling analysis now not only to of cope with in single create a successful andiscustomersatisfying product the Alongside products allowina better information the capabilitiesand andanvalue of physical [3]. activity, humanlike interaction personality are crucial to communication ongoing trend of components digitization and products, limited rangeand or existing product families, future [8].a The firstproduct big challenge is that manufacturers have to flow of customer’s behavior [2]. For the first time, a company Alongside these, smart products allow a better information create a successful and customersatisfying product in the digitalization, enterprises are facing important but also tothese be able to analyze to compare to define consider influences onand products whileproducts at the same time is able to learnmanufacturing something about their customer’s behavior and flow of customer’s behavior [2].environments: For the first time, a company future [8]. The first bigIt challenge is that manufacturers have to challenges in today’s market a continuing new product families. can be observed that classical there is rarely any fundamental knowledge aboutexisting it in which product functions they really use or which ones they is able totowards learn something about their customer’s behavior and and considerfamilies these influences on products whileclients at theor same time tendency reduction of product development product regrouped in function companies. Thearesecond challenge is toof follow a features. specific avoid [4]. Using field information collected by smarttimes products which product functions they really use or which ones they there is rarely any fundamental knowledge about it in shortened lifecycles. In addition, there is[4, an increasing However, product hardly to find. objective assembly which isoriented determined in families the veryarebeginning of a improve product a company’s product development 5], which avoid [4]. Using field information collected by smart products companies. The second challenge is to follow a specific demand of customization, being at the by same timefunctions in a global On the product family level, products differ mainly in two development project. means that smart products are extended digital that improve a with company’s product development [4,This 5], trend, which objective which is (i) determined in of thecomponents very beginning competition competitors all over the world. main characteristics: number andproducts (ii)ofthea In this paper we firstthe describe how to define smart combine physical elements with service-oriented ones to means that smart products are extended by digital functions that development project. which inducing the development from[6]. macro micro type (e.g.process. mechanical, and of thecomponents smartification Afterelectrical, explainingelectronical). our research achieveis maximum customer satisfaction Newtobusiness combine results physical elements with service-oriented ones to In this paper we first describe how tomainly definesingle smart products products markets, in diminished lot sizes due to augmenting Classical methodologies considering achieve maximum customer satisfaction [6]. New business and the smartification process. After explaining our research product varieties (high-volume to low-volume production) [1]. or solitary, already existing product families analyze the 2212-8271 © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license To cope with this augmenting variety as well as to be able to product structure on a physical level (components level) which (http://creativecommons.org/licenses/by-nc-nd/3.0/) 2212-8271 ©under 2019responsibility The optimization Authors. of Published by Elsevier Ltd. an open access article under the CC BY-NC-ND licensean efficient definition and identify potentials in This existing causes regarding Peer-reviewpossible the scientific committee ofthe theis52nd CIRP Conference on difficulties Manufacturing Systems. (http://creativecommons.org/licenses/by-nc-nd/3.0/) production system, it is important to have a precise knowledge comparison of different product families. Addressing this Keywords: Assembly; Family identification In the last decadesDesign new method; and SME-unknown technical

Peer-review under responsibility of the scientific committee of the 52nd CIRP Conference on Manufacturing Systems.

2212-8271 © 2019 The Authors. Published by Elsevier Ltd. This is an©open article Published under theby CC BY-NC-ND 2212-8271 2017access The Authors. Elsevier B.V. license (http://creativecommons.org/licenses/by-nc-nd/3.0/) Peer-review under responsibility of scientific the scientific committee theCIRP 52ndDesign CIRPConference Conference2018. on Manufacturing Systems. Peer-review under responsibility of the committee of the of 28th 10.1016/j.procir.2019.03.040

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method, we will line out how objectives for smart products can be selected. Furthermore, we point out our developed morphology of digital functions for smart products. In conclusion, we will describe how objectives and digital functions are used to specify a smartification project’s goal and design user stories for a successful smartification process. In order to evaluate the method’s fitness for purpose, we describe an application in detail. Applying the presented objectives and functions, a smartification project can be initiated more precisely and accurately. 2. Background The designation smart is common to describe a product that is extended with digital functions and customer-oriented services. But, there are much more designations for smart products in literature. We analyzed and clustered few more designations to find out whether there are content-related differences or not. We found more than eleven various designations of smart products [9]. Besides smart product, there also exist designations like cyber physical or digital products. These are mentioned less than intelligent [10] or digitized products [11]. Comparing definitions of smart, intelligent and digitized products we noted that they are basically similar. Referring Gutierrez et al.’s research work we can state, that even most characteristics of smart or intelligent products are similar [12]. Therefore intelligent product is a synonym for a smart product [13]. Based on Porter and Heppelman’s definition which define smart products as a still physical product with smart and connecting compontens [3], Abramovici’s [14] and Schuh’s [5] definition we understand smart products as follows: smart products are based on digitized (or cyber-physical) products, which consist of physical, intelligent and connected components and are capable of a digital upgrading through internet-based services [6]. Also, we describe the definition of smartification process. Most frameworks for product development address the development of new products. Pahl and Beitz defined four types of product development cases: New design, adaptable design, variant design and repetitive design. The first design case refers to a very new design concept. The second design case represents a design that freezes the original product function. The third design case is about redefining new assemblies. The fourth design case creates a new way of producing the original product [15]. The closest approach to a digital refinement of an existing product is the case of adaptable design. However, there is no further description of realizing this effort. Smartification refers to the digital refinement of an existing product by embedding digital technologies and smart services. Primary product-determining factors still must be accounted for and a product’s primary function must remain in place. When new technologies are embedded, completely new digital performances are offered. Further, we describe how to model digital features and functions. In scientific literature, several models which describe typical characteristics or architectures of smart products can be found. There are basically two different views

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on smart products: 1) Characteristic’s view and 2) Technology’s view. Characteristic descriptions try to picture a customer’s implicit expectation of smart products and what must be taken into account when transforming an ordinary product to personalized and pro-active one which employs customer-satisfying functions [8, 16]. These descriptions fundamentally lack in detailing each characteristic at a highergrade specification level. Such a specification level must be reached as it is necessary to transform a certain customer need into useful and solution- neutral requirements [17]. If one looks at technology’s view, one notices that many research projects attempt to develop application-oriented architectures for smart products, sometimes independent of each other. The focus of these architectures is to consider basic and trend technologies [3, 10, 11, 18–20]. These architectures fail at taking into account various maturity levels of smartness and the associated influences on architecture’s variants. However, existing models of characteristic descriptions or product architectures do not cover a holistic view on necessary features and functions as a goal-oriented contribution for designing smart products. We address this research gap in this paper by answering the research question: How can a methodology for the smartification of products be designed? 3. Research Methodology In order to solve the previously introduced question, we chose Eisenhardt’s methodology of case study research. This methodology can be appropriately applied when a phenomenon is to be studied in its real context [21]. Table 1. Overview of selected cases. Nr.

Type of Smart Product

Focus

Degree of intelligence

Employees

1

Smart Container in Supply Chains

B2B

Medium

36

2

Smart Container in Supply Chains

B2B

Low

2,100

3

Smart Agriculture machine

B2B

High

5,300

4

Smart Container in Supply Chains

B2C

Medium

2,300

5

Smart Television

B2C

Medium

550

6

Smart Forklift Truck

B2B

Medium

8,103

7

Smart Small Robots

B2B

High

2,600

8

Smart Power Tool in Assembly

B2B

Medium

16,500

9

Smart Materials

B2B

Low

210

10

Smart Car

B2C

Medium

210

11

Smart Truck

B2C

Medium

210

12

Smart lawn mower

B2C

Low

12,700

13

Smart AGV

B2B

High

60

Originated research has development management

in empirical social sciences [22], case study gained attention in the domain of product [23] as well as technology and innovation and business science [21]. Considering

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visualizing how companies can use a shortlist of objectives for smart products to determine their development objective. First, a person using the approach must analyze his company’s initial situation and select a strategy type. There are various generic strategy types in the manufacturing industry [25].  Differentiation: Realizing customer needs in a unique way through high quality, novelty or value-added services [26].  Cost leadership: lowest unit costs in assigned branches of industry [26].  Lateral strategy: customer-individual solutions through broad technological understanding [25].

30 20

Case 13

Digital features

Case 12

Case 11

Case 10

Case 9

Case 8

Case 7

Digital function

Case 6

Case 5

Case 4

Case 3

Case 2

0

Start

10 Case 1

Number of features and functions

Eisenhardt’s recommendation, we applied a theoretic sampling approach to identify and select cases for this paper. This approach aims to identify case studies based on theoretical reasoning, which support and enlarge the model under development [24]. First, we structured the selection of cases by choosing different types of smart products with different customer focuses (Business-to-Business “B2B” or Businessto-Customer “B2C”). Secondly, we chose a various size of manufacturing companies which can be assigned to different industries. This structure guarantees that we represented all kinds of businesses in this study and achieve a holistic view.

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Fig. 1. Saturation in data collection.

We applied the approach of triangulation to collect data which means that there is more than one single source for data collection [24]. The primary data we used were description documents and data sheets of each product. In addition to this, we interviewed users of the smart products which are used in our Demonstration Factory (DFA) (see Table 1). Two interview partners documented various digital functions immediately. While primary data represents the provider’s perspective, secondary data shows the user’s perspective on a product. We finished our data collection phase according to Eisenhardt’s theoretical saturation. This saturation is reached when possible new cases bring no new cognition, which can be regarded as a criterion to stop adding more cases [24]. Fig. 1 shows the number of digital features (grey line) and digital functions (black line) of smart products we extracted from thirteen use cases. It is evident that saturation of digital features already occurs after the 5th use case. Comparing features to functions it is shown, that the number of use cases required to reach saturation is higher, exacting at the 9 th case. According to a different specification level, which differentiates between features and detailed functions, the specific saturation behavior can be explained. In the end, we agreed that a saturation’s adequateness was reached and no further use cases were necessary. 4. Description of Methodology 4.1. Objectives of smart products We described in our introduction, that companies find themselves at a substantial lack tying to define their objectives for smartification. Fig. 2 shows a three-step approach,

Fig. 2. Cause-effect relationships between strategy, CSF and objectives.

Second, various critical success factors underlie individual types of strategies. According to Caralli, critical success factors influence and enable a company’s strategy as well as functioning as a layer between strategic and operative perspectives [27]. The third step pictures logical connections between critical success factors and typical objectives when developing a smart product. Some objectives for smart products can be found in Meyer et al. [28], Cronin [29], Porter and Heppelmann [3] and Hicking et al. [6]. In order to use the methodology straightforwardly we described two exemplary objectives. First, “Enable new business models” realizes a constant cash flow by offering product functions as a service. Only the frequency of customer’s usage is factored in. The business model changes from a product-centered view towards a user-centered one. Second, “Optimize internal service processes” is about using field data to monitor a product’s condition and predict downtime through data analytics. By preemptively realizing that a product failure will occur, producers are able to calculate resources for maintenance activities more precisely. For customers, this means that downtimes of the used product, e.g. a machinery tool, can be prevented. 4.2. Morphology of digital features and functions For smartification projects with focus on digital refinement of existing products an expanded understanding of possible supplier-neutral solutions is important. In the following, we describe a morphology of digital functions that already exist in smart products today. In total, we are able to identify nine different digital features. We aggregated two nearly similar features, leaving eight features in total. Furthermore, we extracted 33 digital functions and condensed them to 26 different ones. Both summarization steps were necessary in order to guarantee the elimination of any functional overlapping. Fig. 3 shows the morphology consisting of 26 digital functions which were found in thirteen

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cases. We note that not every single function must be implemented in a smart product. On the contrary, a smart product is characterized by the fact that it contains at least one function in each feature. Some products will contain more than one function, which is an indicator for a higher degree of product intelligence. As an example, a use case representing a smart power tool used in assembly (see Table 1) which is connected to a planning system and directly adjusts the correct torque at a workstation. Digital Feature

Digital Function

Type of data collection

Identification capture

Condition capture

Position capture

Place of product intelligence

Embedded

Combined

Outsourced

Place of data retention

Embedded

Combined

Outsourced

Degree of product intelligence

Identification

Data aggregation

Information creation

Decision making

Bidirectional user interaction

Physical action

None

Unidirectional user interaction

Type of interconnectedness

None

Object Information system Platform interconnectedness interconnectedness interconnectedness

Type of connectivity

None

Degree of independence

Semi-autonomous

Type of interaction

Wired

Wireless Autonomous

Fig. 3. Morphology of digital features and functions.

A smart product is often referred to as the ability of data collection. We distinguish three different types of data collection. Identification refers to the ability of smart products to recognize the identity of other products and systems. This is a necessary requirement for smart products. Additionally, a smart product can capture data on its own condition, of the environment or of the process it is related to. Examples for this are the production status and the ambient temperature. Another type of data collection is position capture, which is the capability of a smart product to locate itself, e.g. in a geographical manner or related to a production process. The gathered data needs to be processed, which can happen at different places of product intelligence. The place of product intelligence is independent from the degree of product intelligence. Intelligence is embedded, when the data is exclusively processed locally. In contrast to that a product’s intelligence is outsourced when all data processing is executed externally. A mixture of both embedded and outsourced product intelligence results in a combined version of product intelligence. The place of data retention can be embedded, outsourced or combined the same way as the place of product intelligence. When gathered data is only stored locally on the product itself without communication to external elements, data retention is embedded. An outsourced data retention is applied when gathered data is directly sent to external components for exclusive storage such as information systems or platforms, without being stored locally. A mix of both embedded and outsourced data retention can be classified as ‘combined’. Smart products’ intelligence ranges from a basic identification function to data aggregation and information creation to decision making, which can be clustered as degree of product intelligence. A product that shows the degree of

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‘identification’ can share its identity as well as stored or collected data. However, any further data processing is prohibited in this case. When a product is capable of basic data processing, such as aggregating collected data and creating information on current and past situations, its degree of intelligence is ‘data aggregation’. In contrast to that, the degree of ‘information creation’ requires the product to be able to execute more complex analytical processing and combination of collected data and context information. It is able to recognize cause-effect-relations and to draw conclusions. Thus, it can learn and improve its functionality during the usage period and it can inform about future events. A smart product with the highest degree of product intelligence ‘decision making’ is capable of autonomously making decisions based on several relevant data and information that are gathered on its own or received from other products, information systems or humans. Furthermore, it might be able to autonomously initiate actions, however, this also depends on the degree of independence. Smart products which show this degree of intelligence are not directly dependent on humans anymore. Nevertheless, smart products show four different types of interaction. The function ‘no interaction’ refers to a smart product that does not interact with or present information to humans and that does not initiate an action to change the environment. A smart product that shows unidirectional interactions is capable of presenting information. In addition to that, a smart product can be capable of receiving information and inputs from humans which can be classified as bidirectional user interaction. Apart from that, a smart product physically executing actions can change the environment or its own status or condition within the environment using active elements. Smart products often show some type of interconnectedness that we distinguish in four functions. Fully independent smart products exhibit no interconnectedness. In contrast to that, a smart product can exhibit direct interconnectedness with other objects to exchange data and information as well as to execute swarm behavior. Furthermore, a smart product can be connected to information systems of both the user and the manufacturer. In order to expand its functionality through web-based digital services, a smart product can be connected to cross-company platforms. In order to perform the previously described interconnectedness, the type of connectivity becomes relevant. Smart Products that are connected to neither internal objects and IT-systems (local) nor to external systems (global), provide no connectivity. For an internal and / or external connectivity that is not determined to be local or global, a smart product can have a wired or a wireless connectivity. However, a wired connectivity is limited to stationary use while a wireless connectivity facilitates mobile use but is limited to environments without interference. Depending on the ability to make decisions and the ability to perform physical actions, the degree of independence can be separated into two digital functions. Smart products that act semi-autonomously are partly capable of processing data independently, raising it to a higher aggregation level and

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making decisions. Products acting autonomously process data on their own, make decisions as described above, and initiate physical actions. However, there is no complete isolation from human beings as they are still the final decision instance. 4.3. Methodology for smartification In order to support smartification processes and to reduce the time to initiate such development projects we point out how to use the link between a smart product’s objective and its digital functions. First, a company must analyze its current strategy portfolio and find out which strategy type it can be allocated to. Therefore it is of utmost importance to analyze the strategy accurately to make sure that there is no “stuck-in-themiddle” problem [30]. Company‘s strategy & CSF

Select fitting objective

Choose feature / function to be specified

User Stories

Put together a team

Check design restrictions

Specify user stories Paper’s focus

Not focus

Fig. 4. Methodology for smartification of products in manufacturing industry.

This means that a company has no competitive advantages [26]. After analyzing and committing to a type of strategy, the most important and influencing strategic success factors must be selected. CSF’s are basically allocated to the respective type of strategy. Thirdly, a smart product’s objective can be selected. Selected strategy types and CSF lead to a preselection of a smart product’s objectives, see Fig. 2. In the next step, user stories are built by combining objectives and digital features. A user story follows a certain structure: As I want to achieve . There is a minimum of eight user stories to be built following the number of digital features in the morphology. When all these user stories are built it is guaranteed that every digital feature is considered for the development of smart products. After building user stories a company has to put together a team, which can be put together of individuals who are knowledgeable in considered features. To be more agile, DevOps’ approach can be adopted. This means that developers, implementers and users can staff the teams. Furthermore, restrictions of the existing product must be analyzed. Especially small installation space or shielding of communication frequencies must be taken into consideration. Finally, each user story must be specified. This represents a product development’s starting point. 5. Application of methodology In this section, we demonstrate the applicability of the methodology onto a smartification project. The SME produces pinching machines for textile industries. The company follows lateral strategy and focuses on the CSF productivity. In a first

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workshop with that company, we analyzed their current situation and selected the objective enable new business models for the smart product. In another workshop we defined a specific use case to reach the objective. We focused on a use case in which the SME does not offer a product but the product’s performance in the sense of a product-as-a-service (PaaS) model. We built several user stories to specify the scopes of smartification and name the important ones in the following.  As a producer, I want the machine to monitor its condition and position data for determining frequency of use to enable new business models.  As a developer, I want the intelligence and data retention to be outsourced due to a lack of construction space.  As a producer, I want the machine to create information about number of uses to realize a PaaS.  As a user, I want to interact with the machine in case of malfunction and to inform the producer.  As a producer, I want the machine to be interconnected with a platform for transmitting condition and usage data to enable new business models.  As a developer, I want the machine to be wired because customers do not have stable Wi-Fi to charge per use.  As a producer, I want the machine to provide information on status and usage amount, but not to decide on charge or maintenance activities. These user stories were created with a managing director, a development manager and a selected customer. Every user story represents at least one digital function and describes why this function in particular is needed to create a smart pinching machine. The machine must measure a product’s usage frequency for invoicing and maintenance activities. A platform concept guarantees that all data is stored centrally but not inside the machine. Implementing this concept meant that required data is always available. The machine needs stable internet connection to transmit usage data and the user’s feedback. In summary, the methodology supports the SME to specify their own smartification project. It was very helpful to focus on one objective which was aligned with a company’s strategy. All user stories were used to staff teams with competent and suitable members. More importantly, the time taken to launch such a smartification project has been reduced by more than half a year. In addition, no digital function was missed in the workshops. 6. Contribution and Discussion The contribution of this paper is a methodology for smartification of products in manufacturing industry. We described why smart products are necessary for smartification projects and that they have to fit into a company’s business strategy. Furthermore, we described a morphology of digital features and functions by using case study research. Thirteen various cases in the manufacturing industry were analyzed to extract 8 digital features and 26 digital features which are typical for smart products. We developed a methodology building upon objectives and a function’s morphology. It

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describes, in a few steps, how user stories for smart products can be built and what they can be used for. Finally, we validated the morphology and methodology in cases with SMEs. We noted that the methodology supports an SME’s initiation smartification projects. Firstly, they were able to specify development’s goal. Secondly, they were able to build user stories for staffing the right personnel. Third, they were able to reduce the time of project initiation significantly. However, the limitations of these results are given by Eisenhartd’s case study research method: Case study research does not ensure a validity of a theory. In the first place it is all about creating a very new theory. Nevertheless, we noticed a feature saturation after five use cases and a function saturation after use case nine. Fig. 2. shows that with the number of thirteen cases a significant level of saturation is reached. Subsequent research activities will focus on specifying the described morphology and extending it to other industries (e.g. medical equipment). We have found that the objectives of smart products and their digital features are insufficient, so a generic use case catalogue must also be developed to apply the methodology more precisely. Acknowledgements This article arose during the work of the authors, within the context of the research project “CyberKMU²” (IT-1-1-009a / EFRE-0800446) funded by the European Union and by the Government of North Rhine-Westphalia. The authors want to thank all donors, supporter and critics. References [1] A. Issa, D. Lucke, and T. Bauernhansl, “Mobilizing SMEs Towards Industrie 4.0-enabled Smart Products,” in Volume 63, Manufacturing Systems 4.0 – Proceedings of the 50th CIRP Conference on Manufacturing Systems, M. M. Tseng, H.-Y. Tsai, and Y. Wang, Eds., o.O.: Elsevier, 2017, pp. 670–674. [2] S. Chowdhury, D. Haftor, and N. Pashkevich, “Smart Product-Service Systems (Smart PSS) in Industrial Firms: A Literature Review,” Procedia CIRP, no. 73, pp. 26–31, 2018. [3] M. E. Porter and J. E. Heppelmann, “How Smart, Conntected Products Are Transforming Competition: Spotlight on managing the internet of things,” Harvard Business Review, November 2014, pp. 64–88, 2014. [4] T. Wuest, T. Schmidt, W. Wei, and D. Romero, “Towards (pro-)active intelligent products,” International Journal Product Lifecycle Management, no. Vol. 11, No. 2;, pp. 154–189, 2018. [5] G. Schuh, “Industrie 4.0 in der Produktentwicklung,” Aachen, Mar. 14 2017. [6] J. Hicking, V. Zeller, and G. Schuh, “Goal-Oriented Approach to Enable New Business Models for SME Using Smart Products,” in IFIP Advances in Information and Communication Technology, Product Lifecycle Management to Support Industry 4.0, P. Chiabert, A. Bouras, F. Noël, and J. Ríos, Eds., Cham: Springer International Publishing, 2018, pp. 147–158. [7] M. Barbian et al., “Digitale Chancen und Bedrohungen - Geschäftsmodelle für Industrie 4.0,” Statusreport, o.O., May. 2016. [8] S. A. Rijsdijk and E. J. Hultink, “How Today's Consumers Perceive Tomorrow's Smart Products *,” Journal of Product Innovation Management, vol. 26, no. 1, pp. 24–42, 2009. [9] M. Mühlhäuser, “Smart Products: An Introduction,” in Communications in Computer and Information Science, Constructing Ambient Intelligence, M. Mühlhäuser, A. Ferscha, and E. Aitenbichler, Eds., Berlin, Heidelberg: Springer Berlin Heidelberg, 2008, pp. 158–164.

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