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Institute
Numerous traditional, agile and hybrid development approaches have been proposed for the development of CPS. As the choice of development process is crucial to the success of development projects, it has become a major challenge to identify the best-suited process. This paper introduces a methodology for identifying the best-suited CPS development process, based on the individual boundary conditions for a certain development project within a company. The authors used a set of eight indicators to assess a CPS-development project. The results of the assessment were matched with CPS-development approaches. Based on the matching results a best-suited development process was selected. The application is shown for a use case in the German manufacturing industry. The developed method aims to reduce the risk of project failure due to the wrong choice of development process.
Task-Specific Decision Support Systems in Multi-Level Production Systems based on the digital shadow
(2019)
Due to the increasing spread of Information and Communication Technologies (ICT) suitable for shop floors, the production environment can more easily be digitally connected to the various decision making levels of a production system. This connectivity as well as an increasing availability of high-resolution feedback data, can be used for decision support for all levels of the company and supply chain. To enable data driven decision support, different data sources were structured and linked. The data was combined in task-specific digital shadows, selecting clustering and aggregation rules to gain information. Visual interfaces for task-specific decision support systems (DSS) were developed and evaluated positively by domain experts. The complexity of decision making on different levels was successfully reduced as an effect of the processed amounts of data. These interfaces support decision making, but can additionally be improved if DSS are extended with smart agents as proposed in the Internet of Production.
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.
Blockchain as Middleware+
(2019)
In supporting decision making of manufacturing companies, the added value of cross-domain data exchange for aggregating information is well established in enterprise organization research and is represented, for example, in the reference model “Internet of Production” (IoP). Currently, there is little research regarding the role of Blockchain technology in such a reference model and how specifically the IoP needs to be expanded to address cross-company data exchange. This paper presents a proposal for such an extension to outline the use of Blockchain technology and to elaborate the open research demands for implementation. In particular, desk research and the development of concrete use cases for cross-company data exchange between business application systems were carried out. The results are, on the one hand, extending the IoP by a third dimension, which corresponds to the supply chain, and, on the other hand clarification of the role Blockchain technology can take in this context.
This paper won the John Burbidge Best Paper Award (see Attachment 2).
[CIRP Encyclopedia of Production Engineering:]
This high quality reference work has been written and reviewed by members of The International Academy for Production Engineering, also known as CIRP. This Academy is recognized worldwide to represent the highest standards in research on production engineering, which includes design, optimization, control, management of processes, machines, and systems. One key concept behind this Encyclopedia is that apart from covering fundamental concepts in the field of production engineering, it also closely follows recent developments and emerging concepts. In particular this renewed print edition covers a wide range of new topical entries such as Hybrid Processes, High Performance Grinding, Biomimetic Design, Cold Spray, Sheet-bulk Metal Forming, Ecodesign, Cyber Physical System, Nano Technology, or Geometrical Product Specification. The second edition also comprises reviewed entries from the first version, which have been updated to reflect new standards or developments. The target audience primarily comprises researchers, engineers, managers, graduate students, and many others whose day-to-day work gravitates around production engineering technologies in the global market.
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.
Management of information and the IT systems it is stored in becomes a crucial capability for the industry. However, companies are struggling with the management of the various requirements and frequent changes of technology. Thus, IT complexity has become a major challenge for companies. At the same time, especially manufacturing companies are striving to implement Industrie 4.0 concepts. Many of these even have developed an Industrie 4.0 roadmap including various projects to change the company. Companies can develop such roadmaps by applying the Industrie 4.0 Maturity Index that gives a broad view on necessary capabilities for Industrie 4.0.
In our research, we analyzed data sets from over 10 manufacturing companies that have performed an Industrie 4.0 maturity assessment. Our hypothesis was that IT complexity challenges are hindering the implementation of Industrie 4.0 roadmaps significantly. We could prove this hypothesis at least for the companies analyzed and give insights on the specific challenges. Based on our analysis, we conclude our article by giving concrete recommendations on how to tackle IT complexity.
Nowadays, the market for information and communication technologies used for IOT-applications grows daily. Since companies need technologies to transform their business processes corresponding to the digital revolution, they need to know which technologies are available, and fit the best for their use case. Their inertial issue is the lacking overview of technologies suitable to connect their production or logistics. Hence, this paper presents a methodology to select technologies (and combinations) based on their functions. It differentiates between information and communication technologies, digital technologies and connecting technologies by the physical function and its role in a cyber-physical system. Depending on the use case, the applicability of every technology varies. Due to that reason, the paper illustrates a ranked qualification of the technologies for typical use cases, focussing tracking and tracing issues in the intralogistics of producing companies. The evaluation is performed upon a literature research, a market study to identify suitable technologies, and various expert interviews to assess the applicability of the technologies.
Discrete Event Simulation (DES) is a well-known approach to simulate production environments. However it was rarely used for operative planning processes and to our knowledge never in terms of multiple disposition levels.In this paper we develop the necessary adjustments to use DES for this purpose and show some theoretical advantages.
The almost boundless possibilities of realizing saving potentials and innovations drive manufacturing companies to implement Business Analytics as part of the digitalization roadmap. The increasing research within the field of algorithm design and the wide range of user-friendly tools simplify generating first insights from data also for non-professionals. However, small and medium sized companies struggle implementing Business Analytics company-wide due to the lack of competencies. Especially the customization of a multitude of analytic methods in order to match a superordinate, business-relevant question is not done easily. This paper enables researchers as well as practitioners to close the gap between business relevant questions and algorithms. From a practical point of view, this paper helps shortening the search time for a suitable algorithm. Out of a research perspective, it aims to help positioning new algorithms within a structured framework in order to enhance the communication of algorithms’ capabilities.
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.
Assessment of IS Integration Efforts to Implement the Internet of Production Reference Architecture
(2018)
As part of a collaborative network, manufacturing companies are required to be agile and accelerate their decision making. To do so, a high amount of data is available and needs to be utilized. To enable this from a company internal information system perspective, the Internet of Production (IoP) describes a future information system (IS) architecture. Core element of the IoP is a digital platform building the basis for a network of cognitive systems. To implement and continuously further develop the IoP, manufacturing companies need to make architecture-related decisions concerning the accessibility of data, the processing of the data as well as the visualization of the information. The goal of this research is the development of a decision-support methodology to make those decisions, taking under consideration the evaluated IS integration effort. Therefore, this paper describes the allocation of IS functions and identifies the effort drivers for the respective IS integration by analyzing the integration possibilities. Conclusively this approach will be validated in a case study.
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.
Due to the drastically increasing amount of data, decision making in companies heavily relies on having the right data available. Also because of an increasing complexity of structures and processes, quick and precise flows of information become more important.
This paper introduces a new approach for modelling information flows, creating a basis for an efficient information management. It can be used to structure the information requirements and identify gaps within the information processing.
To display its benefits, the proposed Information Logistics Notation (ILN) is applied to the information logistics of todays and future energy market and grid stability management, both processes of increasing complexity.
The 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. New business models ensure that even SMEs are able to open up new markets and canvass new customers. This means that in order to stay competitive, SMEs must transform their existing business models.
The creation of new business models require smart products. 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. These services then expand functions and functionality of smart products and define new business models.
However, the development of smart products by small and medium-sized enterprises is still lined with obstacles. Regarding the product development process the inclusion of smart products means that new and SME-unknown domains diffuse during the process. 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. 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.
Growing information systems (IS) often come along with growing IT complexity, because of emerging rag rug landscapes. This development causes rising IT costs and dependencies, which hinder the maintenance and expansion of the IS landscape. This article outlines the current research on published and presented methods to manage the rising IT complexity in a literature review. Because definitions of “IT complexity” vary a lot in literature, this paper also includes a definition of the term. In addition to that, it delivers a presentation of the used research methodology. Subsequently, it presents the findings in literature, highlights the research gap and – based on the literature analysis – presents the steps that need to be taken. A discussion of the results and a summary complete the article.
In this paper, an approach towards energy management 4.0 will be presented. Energy management 4.0 is understood as an encompassing energy data based concept for manufacturing companies acting in an flexible energy grid of the future with the final goal of autonomous self-optimization Controlling, supervising and scheduling production and logistic steps based on a reliable communication infrastructure and real time data in accordance to achieve a maximum of profitability with regard to human factor is executed.
Guided by a four maturity levels of the "acatech Industrie 4.0 Maturity Index" developed by the German National Academy of Science and Engineering (acatech) different use cases are presented according to the steps of visibility, transparency, prognostic capacity and self-optimization. The basic idea of energy management 4.0 is described and an outlook of further steps that are needed to be evaluated for an implementation are presented.
Growing information systems (IS) often come along with growing IT complexity, because of emerging rag rug landscapes. This development causes rising IT costs and dependencies, which hinder the maintenance and expansion of the IS landscape. This article outlines the current research on published and presented methods to manage the rising IT complexity in a literature review. Because definitions of “IT complexity” vary a lot in literature, this paper also includes a definition of the term. In addition to that, it delivers a presentation of the used research methodology. Subsequently, it presents the findings in literature, highlights the research gap and – based on the literature analysis – presents, the steps that need to be taken. A discussion of the results and a summary complete the article.
Nowadays one of the most challenging tasks of producing companies is the growing complexity due to the globalization and digitalization. Especially in high wage countries, the ability to deliver fast and to a fixed date gets more and more important. To achieve this logistic target, it is necessary to optimize the Production Planning and Control (hereinafter PPC). This study investigates the effects of a change of the scheduling parameters on a target system. The focused research questions are: How can the effect of a scheduling parametersvariation on the target system of the PPC can be displayed efficiently? Is it possible to review the effect of the scheduling parameters-variation quantitatively and to derive action options?