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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.
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]
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.
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.
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.
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.
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.
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.
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.
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.