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In the pursuit of a sustainable economy, several transitions are initiated which affect the way of doing business. The most prominent transitions, the energy transition and the transition towards a circular economy, are exemplary for the way companies are impacted. By the analysis of the differences and similarities between the two transitions, the challenges for companies are identified. The value chain needs to implement the demanded adaptations to be competitive. Therefore, the environmental performance and capacity to make the required adaptation of all value chain partners are of relevance for business continuation. A future tool should support companies in the assessment of the value chain partners to be adaptive. The paper describes the design brief for the development of the tool that should incentivize companies to focus on and provide guidance for a multi-capital approach for value creation and to transition to a sustainable value chain.

The Business Model Canvas as a template for strategic management serves the development of new or the documentation of existing linear business models. However, the change towards a Circular Economy requires new value creation structures and thus changed business models. To develop business models for circular economies, it is necessary to adapt the existing template, since the actors involved along the value chain take on changed roles. In the context of this paper, a template is presented, based on the existing Business Model Canvas, which allows to develop and document business models for a Circular Economy.

Visual inspection-based quality control systems are deployed to meet the growing demand of high-quality products. In this paper, an inexpensive RFID (Radio-Frequency Identification) technology and a machine vision system have been integrated within an existing learning factory. RFID technology is used to trace a product/part from its origin, enabling the visibility of the product/part’s entire movement in the value chain. The goals of the paper are to track the workpieces in real time (i) to provide immediate feedback, through visibility, to operators and floor managers and (ii) to develop a database to trace parts, in future, backward through value chain. The system can be used to predict the probability of defective parts in the value chain using machine learning algorithms. This will help the manufacturers to trace the parts in value chain at any point of time including aftersales. Traceability has been a pain point for manufacturers during product recalls.

Transport systems significantly impact our environment, accounting for 29% and 25% of the global energy consumption and greenhouse gas (GHG) emissions, respectively. Therefore, international efforts promote the use of electric vehicles (EVs) to reduce overall GHG emissions with the aim of achieving the energy transition from fossil fuels to renewable energy sources. As a result, the world’s demand for EVs is expected to increase exponentially, leading to increase in using lithium-ion batteries (LIBs). Therefore, the battery is considered the most important component of an EV, and a vital industry with increasing importance for the economy and environment. Based on secondary data, this study aims to underline the most relevant factors for developing a circular design system of LIBs across the value chain of EVs. Due to the dynamic nature of LIBs and EVs market over time and complex interrelationship among processes and stages of their value chain, this study adopts a system dynamics approach. The results of the study reveal the impacts of different factors and their interrelations in the value chain of EVs. The findings of this study would contribute to the decision making and management at different stages in the EVs’ value chain to accelerate a sustainable mobility and energy transition in line with eight relevant sustainable development goals (SDGs).

A digital twin is a digital representation of an unique product or product service system that is sufficient to meet the requirements of a set of use cases. Following this definition, the implementation of a digital twin must be derived from concrete use cases along the life cycle of a product. However, the involvement of a variety of different stakeholders and frequent changes of ownership in the value chain complicate the identification of use cases as well as the specification of the digital twin and its governance. This leads to a need for a systematic approach that enables various partners to implement the digital twins needed for their specific use cases. This paper presents a specification technique that combines aspects from Model-Based Systems Engineering with Product Lifecycle Management to support a collaborative front-end planning and specification of digital twins. It integrates the different views of various digital twin stakeholders (product manager, systems engineer, developer, data scientist etc.) in a collaborative model across the value chain. As part of the systematic approach, a digital twin specification grid that structures guidelines for the aspects of a digital twin (e.g. the data sources) across the product life cycle is provided. The presented approach also supports the derivation of a digital twin by integrating different use cases. This specification technique is the first step towards a holistic, Model-Based Digital Twin Design Framework.

Along the value chain of lithium-ion battery production, there are several process-related changes in the batch structure which are associated with technical challenges for cell-specific traceability. A holistic approach is needed to eliminate the information gaps between the processes and to ensure the traceability of components and process steps up to the finished product. Thus, a solution morphology for the integration of traceability concepts with focus on identification technologies in battery production was developed. This paper presents the developed morphology and its implementation examples. The presented research is carried out together with VARTA in the German research project DigiBattPro 4.0.

Guangzhou is the commercial city with more than a thousand years of history. However, due to the high proportion of traditional industries and the weak innovation ability, Guangzhou’s overall service industry is in the downstream of the global value chain. Through the global innovation chain, Guangzhou can integrate global innovation resources and use global innovation factors to improve innovation service capabilities and industrial upgrading. This paper analyzes the advantages and disadvantages of Guangzhou’s innovative services. It proposes to change the traditional concept of commercial city, develop higher education in Guangzhou, absorb global talents and other innovative elements, accelerate the construction of global innovation chain, and integrate the value chain with the innovation chain. In addition, it is crucial for Guangzhou to improve the local science and technology market, build a support system for science and technology innovation in Guangzhou, build a science and technology innovation park in Guangzhou and a high-end industrial base, in order to turn Guangzhou into an international innovation city.

Battery technology is increasingly seen as an integral element for future energy and transportation systems. Current developments in industry show an increasing number and size of battery producing factories, thus leading to an immense energy demand not only during the production of battery cells but also raw material extraction. Determining the embodied energy of battery cells allows a comparison with alternative energy systems and assessing the overall energy demand that can contribute to define measures for the improvement of its environmental footprint. The present work provides an analysis of the production of battery cells regarding their embodied energy. In order to quantify the embodied energy, a material and energy flow analysis (MEFA) was adapted towards battery production. The methodology focuses on the manufacturing processes and considers indirect and direct energy consumers, different machine states and existing yield losses along the value chain. The approach was applied to the battery manufacturing in the Battery LabFactory Braunschweig (BLB).

The high dynamics of globalized markets and their increase in competition, as well as the demographic changes in western countries causing an increasing shortage of skilled personnel are resulting in major challenges for production companies today. These challenges relate in particular to the processes of assembly forming the last process step in the value chain due to its high share of manual labor. Collaborative assembly, which is characterized by immediate interaction of humans and robots, utilizes the strengths of both partners and is seen as an opportunity to achieve a higher level of flexibility in assembly just as well to support and relieve people of for instance non-ergonomic tasks through automation at work. Although almost every robot manufacturer already has collaborative systems in its product portfolio, these are not yet widely used in industrial production. This might have a variety of reasons, such as the fear of a risky investment or the lack of expertise within the company related to collaborative systems. This article shows a conceptual method that helps companies implementing human-robot-collaboration in their production more quickly and with less implied risk, thus addressing the forthcoming challenges. As a first step, companies must be qualified to make a suitable selection for a possible collaboration scenario. To achieve this, they need a tool to analyze and to evaluate their production processes according to their suitability for human-robot-collaboration. An important feature for an easy and effective use is that the process is formalized so that employees of companies can quickly and easily analyze different processes. The necessary criteria and procedures are developed accordingly and are integrated into the selection method. The main goal is to give the company a recommendation which of their processes are most suitable for human-robot-collaboration, so that they can be used effectively in their production.

Three types of re-design processes are described in the development of circular economy options in businesses: 1) Re-design of the provided services considering changes in the roles of products, users, service, infrastructure, etc.; 2) Re-design of the value chain relations up-stream to suppliers and down-stream to customers and users; 3) Redesign of internal business organization considering necessary changes in tasks, competences, structures and technologies. These redesign processes have been developed as methodology within a research project based on cooperation with businesses in Denmark about analyses of potentials and barriers to circular economy as part of their business strategies. Circular economy is understood as slowing, narrowing and closing resource flows in order to increase resource effectiveness. Before the re-design considerations, initial mappings are done of material relations of the business based on an environmental mapping in life cycle perspective and an organizational analysis mapping of value chain relations, competitive position, innovation practices, user practices and relations to regulation and civil society. The article shows that circular economy can be relevant to businesses within many product and service areas, to both start-ups and existing businesses and to businesses with different roles in value chains, including manufacturing, retail and service. The article develops the concept of ‘circular economy journey’, understood as the activities carried out as part of development and analyses of potentials and barriers to circular economy through slowing down, narrowing and closing resource flows in a specific business and its value chains.

In recent years manufacturing companies have been faced with various challenges related to volatile demand and changing requirements from customer as well as suppliers. This trend is now even accelerating with a direct impact on the value chain. New technological roadmaps and suggested interventions in manufacturing systems try to solve these challenges and solutions such as the German high tech strategy “Industrie 4.0” or the Italian cluster “Fabbrica Intelligente” which often aimed at enhancing the flexibility of manufacturing systems among many other competitive dimensions. However, these approaches often do not provide a detailed definition of flexibility and its different manifestations. Therefore, the question rises if different types of flexibility, that have an impact on the complete manufacturing system, can be better identified with the existing Manufacturing Value Modeling Methodology (MVMM). This question becomes even more important when considering the potential that smart machines interacting with humans, such as cyber-physical systems (CPS), and the possibility to increase connectivity and data access through technologies, such as the internet of things (IoT), offer for increasing flexibility. Especially due to the various possibilities it becomes even more important to understand, which kind of flexibility is needed for a given problem. Implementing flexibility into the MVMM requires a ‘catalog’ that makes use of the MVMM framework presenting an overview of internal and external influence factors in order to support the identification of correct solutions and improvements related to functional areas in the manufacturing environment. Starting from a qualitative literature review on manufacturing flexibility, a ‘flexibility catalog’ is designed, which provides a structural definition of existing flexibility types and their composition as well as providing decision support. In conclusion, the scope of the ‘flexibility catalog’ is to verify that the flexibility demand fits into the market trends and is aligned to the manufacturing and company strategy, in order to help firms to take decisions and delivering value.

To stay competitive in a global market, companies strive to adjust their IT architectures to the characteristics of Industrie 4.0. This means the adaptation of a data-driven manufacturing model, which includes the horizontal and vertical integration of the value chain and the management of data across the whole product life cycle. Currently companies face two major problems in this transformation of their IT architectures: 1) There are multiple reference architectures for Industrie 4.0, whose suitability has not been evaluated in a straightforward way. 2) There are no maturity models to objectively assess data-driven IT architectures. In this work we address these problems by providing an overview of Industrie 4.0 features in multiple reference architectures and developing a maturity model for IT architectures for data-driven manufacturing. We first give an overview of the current maturity models with aspects of data-driven manufacturing. Based on this overview we survey three reference architectures for Industrie 4.0: the Industrial Internet Reference Architecture, the Reference Architecture Model Industrie 4.0, and the Stuttgart IT Architecture for Manufacturing. We analyze and assess each approach and define maturity levels for data-driven manufacturing to guide companies in the adaption process of Industrie 4.0, as well as criteria for meeting these levels.

Bicycle sharing is considered an effective supplement to urban transport. Nowadays, bicycle sharing has become more appealing to more users thanks to the updated application of information technology. In addition to technological support, innovative business model also make great differences. Bicycle sharing can be further facilitated through a circular value chain. PSS-EPR coupling model provides an insight to how to integrate such a value chain. The paper presents PSS-EPR coupling model, and discusses the integrated circular value chain for bicycle sharing based on this model. Case study research methodology is used. Three types of bicycle sharing coexisting in China are described, with Yong Jiu, Ofo and Mobike an example of each type. The paper contrasts their business models against PSS-EPR coupling model, and comes to the conclusion that Mobike is better able to achieve closed-loop value creation. Further suggestions are given to Mobike for more effective value chain management based on the model.

Strategies to improve the economic and environmental performance of companies are usually pursued from a local perspective, hardly considering interactions between different value chain actors. Thus global improvements are not necessarily reached. Against this background, the authors present an approach for an integrated improvement strategy covering both perspectives to reveal hidden resource saving potentials. Moreover, a “decision-making toolbox” has been developed, allowing for an identification of company-internal and cross-company improvements as well as resulting trade-offs. Applicability and benefits of the approach are underlined by a use case application from the metal mechanic industry.

A number of materials have been identified by the EU as being critical to their member's economies and manufacturing industries. A material has been defined by the EU as being critical if it is of “high economic importance combined with a high risk of supply shortage”. This criticality will become increasingly acute as the escalating use of finite resources continues, driven by growing populations and consumer demand. One group of materials that is listed top on the majority of these „critical‟ lists are rare earths, which include the elements neodymium and dysprosium. These are often used in high value, high technology products used in renewable energy, military and aerospace sectors. Whilst most manufactures would be aware of the direct use of rare earth elements in their products, many may not be aware of their indirect use such as in manufacturing equipment and bought-in components, or further down the value chain in inter-reliant products or consumables. This paper presents a framework for the resilient use of critical materials in sustainable manufacturing systems. The first phase of this three phase framework identifies where, in the value chain of this business, critical material are used. Once identified, the second phase assesses the level of risk to the business based upon the likelihood, frequency and severity of a supply disruption occurring for the critical material identified. The third phase supports the identification and development of suitable mitigation strategies to reduce this risk, including the consideration of factors specific to the business as well as more general ones associated with the type of rare earth and its application. The paper concludes with a case study, based on simulated data, that demonstrates the application of phase one of this framework in a typical manufacturing operation.

In the globally competitive market landscape, companies, in order to remain sustainable, must shift their focus towards constantly improving their PSS offerings by incorporating lean thinking approaches. PSS are complex, dynamic, and multi-dimensional systems, which are supported by appropriate infrastructure and networks. At the same time, PSS require robust engineering methods and tools for their design, which allow multi-dimensional exchange of knowledge between the designers and the relevant stakeholders across the value chain. Currently, enabling technologies such as Cloud technology, social media and networking, knowledge management, and context sensitivity present new possibilities to enhance the knowledge exchange and the collaborative process of PSS design. These technologies allow the gathering and analysis of big volumes of data from scattered heterogeneous IT systems and, at the same time, allow PSS design improvements by processing the experiences of the business customers, consumers, designers, shop-floor, and provide feedback to the design phase. However, a number of challenges are encountered during the gathering, visualization, monitoring, and assessment of related data, such as the lack of context sensitivity. Simultaneously, PSS evaluation approaches are still immature and there is limited work that correlates the impact of the entire PSS lifecycle with the performance assessment of the PSS design. The present work includes a review of the aforementioned technologies from academic, market, and industrial perspectives. Based on an extensive literature review and on constructive discussions with three European SMEs, several barriers and limitations of adopting the aforementioned technologies in practice are identified. Finally, a conceptual eco-innovative framework for lean PSS design is presented, explaining how these technologies could be combined for the improvements of PSS design and evaluation procedures. © 2016 The Authors.

Ageing, occurrence of work-related musculoskeletal disorders, and rising sensitivity towards the disabled are paving the way for new, customized movement assisting devices enabling increased mobility independence, correction of user's kinesis and prevention of diseases, combined with a constant monitoring of kinematics conditions. This paper presents the digital double of the manufacturing, delivery and maintenance chain(s) developed for those devices, focusing on its data model, logics, services and optimization functionalities aimed at improving critical stakeholders experiences. The proposed discussion emphasizes how a proper combination of physical and digital twins could effectively support customized manufacturing experiences in socially valuable market segments.

Over the last years the sustainability issue has grown exponentially and it has involved several engineering areas, starting with the product sustainability, then to the factory sustainability, up to reach the entire Value Chain sustainability. Due to the continuous increasing of complex relations among factories, suppliers, and customers, a new method for investigating the entire Value Chain, considering its key partners, their requirements in terms of materials usage and energy consumption, and how these requirements influence the Value Chain sustainability is presented. This model will aim companies to define the criticalities inside the Value Chain relations and to develop possible improved scenarios.

During the past two decades, the trend towards globalisation and the continual downward pressure on operating costs to remain competitive has prompted numerous manufacturers to adopt a radical approach to analyse and realign their cost base. Nowhere has this trend has been more prominent than in the automotive industry whereby several manufacturers have switched production to countries with a lower cost base to benefit from FDI incentives from an enlarged EU. Although savings can quickly be realised on an operational level by switching production, more critical to the overall success is the adoption of a holistic approach which encompasses the entire automotive supply chain and considers the integrated and complex nature of the production process. The aim of this paper is to assess the case study of the Slovak automotive sector from a knowledge management perspective. The purpose is to identify the importance of implementing a robust knowledge sharing process as a means of identifying and integrating key component suppliers. Moreover the process will underline the crucial role of knowledge management as a core component for the success of Just-in-Time production and as a key driver to enable an organisation to fully capitalise upon all elements of the value chain.

Virtual market based supply chain operations solve product allocation problems by distributing scheduled resources according to market prices, which define the common scale of value across various products. We formulate the supply chain model as a discr ete resource allocation problem, and propose an economic negotiation mechanism with a market-oriented programming framework based on complex network information topology. Heterogeneous agents of three types are defined in the virtual market. Their interactions with micro-behaviour show a macro order of the virtual market via a complex network. The clearing price dynamism can be analysed in economic terms. The applicability of the framework to a resource allocation problem for supply chain management is also discussed.

The work presented in this paper is motivated by the differing supply chain characteristics of the automotive and the semiconductor industry. This paper will systematically identify and assess the weak points at the interfaces between these two industries. Based on this analysis, a reference model is presented intended as a toolkit of measures for collaborative value chain management in the automotive and semiconductor industry. The reference model defines a set of specific optimization measures relating to the categories of strategy, processes, technology and IT systems, designed to ensure a better alignment of planning and control processes between automotive and semiconductor industry. The model and the associated measures aim at a more efficient coordination of production capacity and a better response to market fluctuations between automotive and semiconductor industr y. Thus, a more stable supply and a significant reduction of logistics costs in the entire value chain can be achieved.

Increasing production and sales figures for electrically powered vehicles affect the medium term value chains of the automotive industry. Due to the importance to the automotive industry for national economies or economic areas, the issue of determining the medium-term effects arises as a result. To this end, a method for the determination and quantification of e-mobility-induced changes has been developed, using Austria as an example. The method presented in this paper has been developed in the course of a study assigned by the Austrian Federal Ministry of Economy, Family and Youth, the Austrian Economic Chambers and Federation of Austrian Industries.