Smart Services Conditions and Preferences: An Analysis of Chinese and German Manufacturing Markets

Smart Services are individually configurable bundles of physically delivered services and digital services, based on data collected in the Internet of Things. Due to the increasing equipment of products with sensing technologies and communication modules, Smart Services become more and more important to manufacturing companies. Since German and Chinese manufacturing firms possess a strong trading relationship, it is important to understand the market conditions and customer requirements of the two country markets in order to develop and provide Smart Services successfully. In this context, our paper provides a first overview about these aspects, based on literature analysis and a small qualitative survey among four Chinese and four German experts

A Framework to Support Industry 4.0: Chemical Company Case Study

Part 11: Industry 4.0 Support FrameworksInternational audienceThe concept of Industry 4.0 corresponds to a new way of organizing the production of goods, taking smarter decisions based on environmental variables and optimizing available resources. However, there is still a journey to carry out the implementation of this concept with current technologies. To make this transformation of the industry, it is necessary to characterize the Industry 4.0 concept, adopt a strategic thinking, and acquire skills, aptitudes, and attitudes. Enterprise reference models can help in orchestrating the change, however, the relationship between existing reference models and Industry 4.0 needs further clarification. Thus, this paper proposes a framework that links a reference model with the Industry 4.0 concept. Furthermore, a tool for the instantiation of the framework is proposed to provide practical approach. And the results of implementing the proposed framework are presented in a case study

Basis for an Approach to Design Collaborative Cyber-Physical Systems

Part 6: Smart EnvironmentsInternational audienceNowadays Cyber-Physical Systems gain more and more attention in regard to the Industry 4.0 or Digital Transformation in general. These systems imply the tight integration of physical and software components and are becoming more complex, forming highly inter-connected systems-of-systems. Furthermore, as components and subsystems are becoming more intelligent, there is a need for a paradigm shift towards considering them as ecosystems of collaborative entities with growing levels of autonomy. There is, however, the lack of proper methodologies and support frameworks for the design of such systems. In this context a contribution to an approach for the development of Collaborative Cyber-Physical Systems is proposed. It introduces some core definitions, organizational and architectural aspects. The proposed approach is in line with the design science research methodology and is illustrated with some examples

Human-Machine Cooperation in Self-organized Production Systems: A Point of View

International audienceIn the context of Industry 4.0, numerous technologies are developed as well as new paradigms, causing a rupture with historical production control models. This highlights the needs for new approaches aiming to deploy efficiently these new technologies and paradigms within future industrial systems. On the other hand, human-machine system approaches encourage the cooperation between humans and complex artificial systems to react to unexpected events and to ensure an efficient supervision of these artificial systems. The paper focuses on the design of self-organized production systems cooperating with the humans. A literature review is provided based on two views dealing with such a design: a technical and a human-machine system one. Limits and advantages of both views are presented. A merged view, based on the use of the cognitive work analysis (CWA) approach, is then proposed to ensure an efficient cooperation between the human and a self-organized production system. The proposals will be applied to different systems, namely a cobot, a swarm of autonomous AGV and a set of intelligent products

Goal-Oriented Approach to Enable New Business Models for SME Using Smart Products

Part 2: Collaborative Environments and New Product DevelopmentInternational audienceThe manufacturing industry has to exploit trends like “Industrie 4.0” and digitization not only to design production more efficiently, but also to create and develop new and innovative business models [1, p. 2]. New business models ensure that even SMEs are able to open up new markets and canvass new customers [2, p. 82ff.]. This means that in order to stay competitive, SMEs must transform their existing business models [3, p. 2ff.]. The creation of new business models require smart products [4, p. 1, 5, p. 235, 6, p. 13, 7, p. 2, 8, p. 322, 9, p. 7]. The required data base for new business models cannot be provided by SMEs alone, whereas smart products are able to provide a foundation, given the creation of smart data and smart services they enable [5, p. 235]. These services then expand functions and functionality of smart products and define new business models [10, 6f.]. However, the development of smart products by small and medium-sized enterprises is still lined with obstacles [11, p. 640]. Regarding the product development process the inclusion of smart products means that new and SME-unknown domains diffuse during the process [12, p. 2]. Although there are many models regarding this process there appears to be a substantial lack of taking into account the competencies enabled by the implementation of digital technologies. Hence, several SME-supporting approaches fail to address the two major challenges these enterprises are faced with [13, p. 8]. This paper generally describes valid objectives containing relevant stakeholders and their allocation to the phases of the product life cycle. Within each objective the potential benefit for customers and producers is analyzed. The model given in this paper helps SMEs in defining the initiation of a product development project more precisely and hence also eases project scoping and targeting for the smartification of an already existing product

Understanding the Transformation Towards Industry 4.0

The ongoing process of digital transformation in manufacturing – known as Industry 4.0 - hauls fundamental change. The whole value chain of enterprises is affected. As the digital transformation of businesses is still ongoing, many enterprises struggle with the challenges arising. This paper aims to show these struggles but also to contribute by analyzing how enterprises are transforming. We take a phenomenological view of the ongoing transformation. To get in-depth insights, we conducted and analyzed 18 interviews with 10 companies. For most companies, the digital transformation starts in operations with the vision of building a smart factory. Other primary and support activities also need to transform. These essential changes lead to restructuring and extensions of the strategy of manufacturing companies. Following these changes, companies will not need to choose either cost advantage or differentiation as a strategy but instead can do both