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The industrial food production is currently caught between the increas-ing demands of numerous stakeholders, economic profitability and the challenges of digitization. A solution to face these various challenges can be seen in the aggregation of data into higher-value, independent data products that can be of-fered and sold on a buyer's market. Large amounts of heterogeneous data are already available in the value chain of the industrial food production, e.g. throughout the data-driven harvesting of primary products, further processing by interconnected production facilities and the information-intensive product distri-bution to end consumers. However, the data is usually only evaluated and used locally for the optimization of internal processes or, at the most, within compre-hensive partnerships. The purpose of this paper is to identify new revenue oppor-tunities for current and future players in the industrial food production by using data as an independent economic good (data products). For this purpose, scenar-ios for the development and use of data products via Industrial Internet of Things platforms are developed for a food technical reference process, the industrial chocolate production and its value chain. On this basis, examples for different types of data products and their value propositions are derived. The results can not only serve food producers and relevant stakeholders but all industrial produc-ers as an input for the future, yield-increasing orientation of their business models.
Remote services are services enabled by information and communication components and therefore do not require the physical presence of a service technician at the service object to provide a task. The impact of remote service on the capital goods industry has been increasingly significant over the recent yeas. Still many companies struggle with developing and implemenling successful business model, for remote service. This leads to a lot of unaccomplished benefits for the customer as well as for the companies themselves. A survey throughout companies in Ihe industrial machine and plant production sector was conducted in order to determine what successful companies do differently from those that cannot efficiently implement remote service business models.
The study presented in this chapter identifies key suceess factors of companies that effectively implemented remote services for their products. In order to identify the successful companies a scale for measuring remote service success was developed. Only by the use of this scale further findings regarding the success factors were possible. Key findings include the fact that successful companies actively market their remotle service to their customers. Generally they try to approach their remote service business from the operating company's perspective.
In order to cope with the challenges of an increased demand for flexibility, quality and availability of production, maintenance measures provide a major competiveness factor for manufacturing companies. Yet, interdependencies between maintenance and production activities as well as differing target systems within the functional units of an enterprise, especially production and maintenance, raise needs for extended coordination efforts. This paper aims to develop an innovative approach for the coordination between maintenance and production activities for industrial production companies. To achieve this, the novel coordination mechanism is used. It helps to achieve maximised operational availability— for a maximised output of the production system at optimal costs. Based on the developed model, the present paper identifies findings regarding the impact of different maintenance strategies on the medium-term economic efficiency of the production system.
Nowadays, providing purchasable goods is not enough for a company to survive on the global market. Because of competitive prices and a large range of products available, companies need to offer additional benefits to their customers in order to create a unique selling point. They add services to their product portfolio and offer clients the opportunity to acquire an additional service solution to go with it. The offered services need to fit to the customer's needs, resulting in a variety of available services, great complexity of the service range and decreasing transparency of the resource utilization. This paper addresses the problem by identifying variant-creating factors in product service systems, transferring them into an organizational framework and verifying their significance.
In order to achieve a holistic cost management approach, the maintenance and service costs should already be assessed during the development of machines and equipment. The required information in the company, like PLM, process and test data, are commonly not available or vague, especially in early development phases. This paper introduces a feasible method for an early assessment of maintenance and service costs during product development. In doing so, appropriate cost assessment methods are selected, based on the availability and quality of the existing information in the individual development phases. The evaluations of these methods are aggregated in a software tool, so that the respective cost information is displayed with a maximum, minimum and most probable value. The developed software tool was validated in cooperation with a new electric vehicle manufacturer.
Today, machine manufacturers generate a significant share of their revenues with the provision of services. At the same time, they are confronted with the challenge of adopting of Industrie 4.0.
One of the most important Industrie 4.0 concepts is the idea of the digital shadow, which contributes to the comprehensive structuring of different kinds of data from different data sources. It can be defined as the sufficiently precise, digital representation of reality in real-time.
Thus, it also functions as a database of the considered area of a company that can be used for numerous applications. It serves as a central platform for the aggregation and distribution of data. Thereby, it helps to open isolated data silos. A system architecture that enables extraction of data from various sources and the aggregation of that data is an important prerequisite for the digital shadow.
In addition, the merger of data from different sources requires a model of the part of the company to be mapped digitally. In this paper, we focus on maintenance, repair and overhaul (MRO) services of machine manufacturers. The scope comprises the whole order processing of a service including the utilized resources and the obtained results.
MRO services and their single elements are mapped and structured using a case study research in a first step. Those elements provide a basis for designing the digital shadow. A second contribution of this paper is a data model for the digital shadow of MRO services that entails a comprehensive representation of that department.
This paper presents a simulation approach for service production processes on the basis of which an optimal operating point for service systems can be identified. The approach specifically takes into account the characteristics of human behavior. The simulation is based on a system theory approach to the service delivery process. A specific use case of the simulation approach is presented in detail to illustrate how characteristic curves are deduced and an optimal operating point is obtained.
Monetizing Industry 4.0: Design Principles for Subscription Business in the Manufacturing Industry
(2019)
Subscription business models have a major role for monetizing products and services for manufacturing companies in the age of Industry 4.0. As the manufacturing industry has difficulties generating revenues through digitalization, the implementation of innovative business models are essential to remain successful. Physical assets are often capital-intensive and require a more complex manufacturing process than subscription business models. Moreover, subscription models can focus on the individual customer benefit and a consistent service transformation, constituting a unique selling proposition and a competitive advantage. Hence, the following paper provides a management model that enables manufacturing companies to successfully realize the transformation towards a subscription business model. The management model presents four major fields of action, each matched with one design principle that must be considered when dealing with subscription models in the manufacturing industry. These principles were determined by an in-depth case study analysis among various manufacturing companies. Opportunities, challenges and recommendations for action were then systematically derived and integrated into the management model.
Increasing productivity in product-service systems is a vital success factor for industrialized economies and individual businesses. The service production is typically described as an integrated value chain setting, in which the provider and the customer are co-creators.
This paper embraces a characteristic curve model in order to illustrate the influence of the customer on the productivity of service production. The characteristic curves are derived from a system dynamics simulation model for a synchronized takt-based service production. In conclusion this research leads to designs recommendations for service production systems in order to reduce lead times and increase adherence to delivery dates.
Operation and Maintenance (O&M) is a key value driver for offshore wind farms. Consequently, reducing O&M costs improves their profitability. This paper introduces different typologies of dispositioning maintenance tasks in offshore wind farms, in order to help design the strategies and organization of maintenance. Based on the special requirements of offshore wind farms regarding planning and controlling the O&M activities, a morphological analysis was developed. With this different disposition strategies for offshore wind farms could be generated. The consequences of choosing different characteristics are allegorized in an exemplary fashion. The work presented in the following is the foundation for designing a software-based dispositioning tool for usage in offshore wind farms, which will help to increase the effectiveness of the disposition in offshore wind farms by maximizing the number of accomplished tasks per day and minimizing the time technicians stay on the wind turbine and the ships.
Many industrial companies face their digital transformation. In addition to an existing portfolio of products and services, new digital services are being developed to offer a portfolio of smart product service systems (Smart PSS). While the development of new digital services is rarely a problem for the companies, the organization of sales and distribution of Smart PSS in particular is a key issue. The sales of Smart PSS differs considerably from the sales of only products or services and must therefore be designed differently in order to meet customer requirements and successfully commercialize the developed Smart PSS. This paper therefore describes how the sales organization of Smart PSS should be designed successfully in various forms. The network thinking methodology is used in combination with a case study research approach to describe the connection between the offered portfolio, the customer requirements and the different elements of a sales organization. Furthermore, four different types of a sales organization for Smart PSS are described. This paper gives a recommendation for companies on a design of their sales organizations on which practical implications may be developed.
Industrial Smart Services - Types of Smart Service Business Models in the Digitalized Agriculture
(2018)
Due to lack of experience of companies with digital business models, agricultural machinery manufacturers and agricultural service companies are facing a positioning problem in their ecosystem. Smart services are getting more important for these companies and they have issues to define a matching business model for their newly developed smart services. The lack of a framework for smart service business models makes it even harder for companies to successfully develop new services.
This paper contributes to a better understanding of business models for smart services and establishes a common morphological framework to define different types of business models for smart services. Six types of business models of industrial smart services were identified during the research based, which was based on a literature review and interviews with leading experts in the field of smart services. The validation of the developed types and its practical application was carried out as part of the German research project Smart-Farming-World and its four developed use cases. This paper gives a detailed description of the application of the framework on the use case nPotato.
Method for a qualitative cost benefit evaluation of process standardisation for industrial services
(2018)
Industrial service providers deliver complex technical services (e.g. inspection, maintenance, repair, improvement, installation and turnarounds) for a wide range of technical assets in process industries such as the chemical industry. Due to the versatility of assets and industries, there is also a variety of the corresponding service offerings. The demand for a high service quality and the general cost pressure leads to the need of a more efficient and standardized design of the service processes. However, cost-benefit ratio related decisions regarding the questions where and how service processes should be standardized entail great challenges for small and medium-sized enterprises. This is because there is often a lack of understanding of cost savings through process standardization, which is caused by a lack of understanding of the correlations between process characteristics and process target values. Because of this, the goal of this paper is to develop a method for a quantitative evaluation of the cost-benefit ratio of process standardization measures. Within this method, the relevant service performance processes are selected first. Next, the process data will be recorded with the help of questionnaires. These are then analyzed by looking for correlations between the process characteristics and the process target values. Afterwards standardization measures are derived on the basis of these findings in order to improve deficit characteristics and thus target values. Finally, the method´s practical applicability is tested and validated by applying it to an industrial service in the chemical industry.
Process Characteristics and Process Performance Indicators for Analysis of Process Standardization
(2018)
Industrial service companies deliver technically complex services (inspection, maintenance, repair, improvement, installation) for an enormous variety of technical assets in the chemical, steel, food and pharmaceutical industry. This variety of assets leads to a corresponding variety of service processes. To ensure competitiveness, the management of industrial service companies aims to increase the service process efficiency, especially through service process standardization. However, decision-makers struggle to make knowledge-based decisions on service process standardization because ex-ante the cost-benefit ratios of process standardization are unknown. The missing understanding of cost-benefit ratios of process standardization is caused by a missing understanding, which interdependencies exist between process characteristics and process performance indicators. Thus, the objective of this paper is to determine suitable characteristics and performance indicators to measure the way service provision processes are executed in the industrial service sector. The results represent the basis for executing an empirical questionnaire study focusing on the execution of service provision processes and identifying the cause-effect relations of process standardization.
Industrial Smart Services: Types of Smart Service Business Models in the Digitalized Agriculture
(2019)
Due to lack of experience of companies with digital business models, agricultural machinery manufacturers and agricultural service companies are facing a positioning problem in their ecosystem. Smart services are getting more important for these companies and they have issues to define a matching business model for their newly developed smart services. The lack of a framework for smart service business models makes it even harder for companies to successfully develop new services. This paper contributes to a better understanding of business models for smart services and establishes a common morphological framework to define different types of business models for smart services. Six types of business models of industrial smart services were identified during the research based, which was based on a literature review and interviews with leading experts in the field of smart services. The validation of the developed types and its practical application was carried out as part of the German research project Smart-Farming-World and its four developed use cases. This paper gives a detailed description of the application of the framework on the use case nPotato.
Traditional manufacturing companies increasingly launch data-driven services (DDS) to enhance their digital service portfolio. Nonetheless, data-driven services fail more often than traditional industrial services or products within the first year on the market. In terms of market launch, their digital characteristics differ from traditional industrial services and thus need specific structures and actions, which companies currently lack. Therefore, a process guideline for a six-month market launch phase of DDS is developed. The guideline relies on analogies from product, service and software launches based on the latest literature from service marketing and successful practices from various industries. Finally, the guideline is evaluated within five industrial case studies. Thus, the guideline provides scientific research insights regarding the market launch process of DDS and adds to the research of service marketing. It provides practical guidance for manufacturing companies by serving as a reference process for the market launch and offering a collection of successful practices within this area.
Traditional manufacturing companies increasingly launch data-driven services (DDS) to enhance their digital service portfolio. Nonetheless, data-driven services fail more often than traditional industrial services or products within the first year on the market. In terms of market launch, their digital characteristics differ from traditional industrial services and thus need specific structures and actions, which companies currently lack. Therefore, a process guideline for a six-month market launch phase of DDS is developed. The guideline relies on analogies from product, service and software launches based on the latest literature from service marketing and successful practices from various industries. Finally, the guideline is evaluated within five industrial case studies. Thus, the guideline provides scientific research insights regarding the market launch process of DDS and adds to the research of service marketing. It provides practical guidance for manufacturing companies by serving as a reference process for the market launch and offering a collection of successful practices within this area. [https://link.springer.com/chapter/10.1007/978-3-030-00713-3_14]
Data-driven services play an important role in
innovative business models of successful manufacturing
companies: They hold great potential for the creation of unique
selling points and improve the differentiation of manufacturing
companies in highly competitive markets. However, the large
number of newly invented digital services that fail shortly after
launching implies that companies struggle with the invention and
implementation of data-driven service solutions, which ends in a
waste of resources. The following paper introduces guideline
principles for successful innovation processes for data-driven
services. The principles were identified during in-depth case
studies with manufacturing companies. They contribute to a
necessary paradigm change for manufacturing companies in
terms of data-driven services for machines. The six identified
principles emphasize new aspects regarding the new dimension of
data-driven solutions and improve the life cycle management of
products and services. They demonstrate how the rules of agile
development can lead to successful and more efficient service
innovations in the industrial sector.
Industrial service is currently undergoing tremendous changes, largely driven by the development of new technologies, in particular the advancing digitalization. Never before have organizations had more comprehensive and insightful data assets - and never before have the opportunities to fully exploit this potential been better. However, most companies are unaware of how they can make use of this potential and which development steps are necessary to react to the current situation. To change this, a maturity-based approach was developed which describes four development stages of an industrial service company from a technological, organizational and cultural point of view. The maturity model makes it possible to develop a digital roadmap that is tailormade to each company, which helps to introduce Industrie 4.0 and transform industrial service companies into learning, agile organizations.
Smart Service Engineering
(2019)
Industry 4.0 has provided vast opportunities for manufacturing companies whilst simultaneously creating multiple challenges. In this new highly digitized globalized marketplace, manufacturing companies find themselves under pressure to become more service oriented and offer new innovative value offerings such as smart services. These are digital data-driven services that, generally, add value in conjunction with a physical product. However, classical methods of service engineering have not adapted sufficiently to the increasing digital components and requirements of smart services. This paper presents Smart Service Engineering as a novel service-engineering approach for industrial smart services. Smart Service Engineering draws from iterative development models and implements agile and customer-centric methods to decrease the overall development time and achieve an early market success. The paper focuses on the service development steps and presents the interaction and interconnection of different elements of smart services based on a case study research. Finally the paper illustrates the successful application of the Smart Service Engineering approach and its impact on a German medium-sized company in the textile machine industry.