Refine
Year of publication
Document Type
- Conference Proceeding (85)
- Part of a Book (25)
- Contribution to a Periodical (18)
- Article (10)
- Working Paper (7)
- Lecture (4)
- Internet Paper (4)
- Book (3)
- Report (2)
- doctorallecture (1)
Language
- English (97)
- German (62)
- Multiple languages (2)
Is part of the Bibliography
- no (161)
Keywords
- 2 (7)
- 3GPP (1)
- 5G (4)
- 5G mobile communication (2)
- 5G use case (1)
- 5G-Technology (1)
- AI (2)
- Aachener PPS-Modell (1)
- Abschlussbericht (1)
- Adaptability (1)
Institute
- FIR e. V. an der RWTH Aachen (161)
- Produktionsmanagement (73)
- Informationsmanagement (41)
- Dienstleistungsmanagement (35)
- Business Transformation (14)
It is crucial today that economies harness renewable energies and integrate them into the existing grid. Conventionally, energy has been generated based on forecasts of peak and low demands. Renewable energy can neither be produced on demand nor stored efficiently. Thus, the aim of this paper is to evaluate Deep Learning-based forecasts of energy consumption to align energy consumption with renewable energy production. Using a dataset from a use-case related to landfill leachate management, multiple prediction models were used to forecast energy demand.The results were validated based on the same dataset from the recycling industry. Shallow models showed the lowest Mean Absolute Percentage Error (MAPE), significantly outperforming a persistence baseline for both, long-term (30 days), mid-term (7 days) and short-term (1 day) forecasts. A potential decrease of up to 23% in peak energy demand was found that could lead to a reduction of 3,091 kg in CO2-emissions per year. Our approach requires low finanacial investments for energy-management hardware, making it suitable for usage in Small and Medium sized Enterprises (SMEs).
Understanding the Organizational Impact of Robotic Process Automation: A Socio-Technical Perspective
(2022)
Interest in AI-driven automation software is growing constantly across
all industries, as these technologies enable companies to almost automate administrative processes completely and significantly increase operational efficiency.
However, many implementation attempts fail due to a lack of understanding of how these technologies affect the various socio-technical aspects that are intertwined in an organisation. This leads to a widening gap between value propositions of automation software and the ability of companies to exploit them. For long-term
success, collaboration between humans and software robots in the organization must be optimised. Therefore, the social, technical, and organizational impact of Robotic Process Automation was investigated. Following a socio-technical systems approach, a model was developed and validated in a use case of a company in the mechanical engineering sector. Knowing the influencing factors before launching large-scale automation initiatives will help practitioners to better exploit
efficiency potentials and increase the long-term success.
Data-driven transparency in end-to-end operations in real-time is seen as a key benefit of the fourth industrial revolution. In the context of a factory, it enables fast and precise diagnoses and corrections of deviations and, thus, contributes to the idea of an agile enterprise. Since a factory is a complex socio-technical system, multiple technical, organizational and cultural capabilities need
to be established and aligned. In recent studies, the underlying broad accessibility of data and corresponding analytics tools are called “data democratization”. In this study, we examine the status quo of the relevant capabilities for data democratization in the manufacturing industry.
(1) and outline the way forward.
(2) The insights are based on 259 studies on the digital maturity of factories from multiple industries and regions of the world using the acatech Industrie 4.0 Maturity Index as a framework. For this work, a subset of the data was selected.
(3) As a result, the examined factories show a lack of capabilities across all dimensions of the framework (IT systems, resources, organizational structure, culture).
(4) Thus, we conclude that the outlined implementation approach needs to comprise the technical backbone for a data pipeline as well as capability building and an organizational transformation.
Erfolgreiche Serviceinnovation im Zeitalter industrieller, datenbasierter Dienstleistungen unterscheidet sich deutlich von bisherigen Ansätzen der klassischen Dienstleistungsentwicklung. Diese Erkenntnis konnte aus einem breit angelegten Benchmarking in der deutschen Industrie gewonnen werden. Die Benchmarking-Studie identifizierte besonders erfolgreiche Unternehmen, deren Methoden und Ansätze zur Gestaltung innovativer Dienstleistungen in Form von Fallstudien im Detail untersucht wurden. Als Kernergebnis ergeben sich sechs Prinzipien, die erfolgreiche Serviceinnovation für datenbasierte Dienstleistungen auszeichnen.
Driven by different trends, such as digitalization, the number of companies aiming for successful business transformation is increasing, while new structures and systems are paving the way. Strategic agile management systems offer significant potential benefits given the increasing speed of the evolving environment in which organizations find themselves these days. To select and implement the appropriate strategic agile management system, companies need to understand the underlying theoretical principles to be able to select the most suitable for the respective company and to introduce it based on individual adaption. Within this paper, a morphology is presented to improve theoretical knowledge about strategic agile management systems. Creating a common understanding of strategic agile management systems and their current areas of application creates a suitable frame of reference for future research projects.
Objectives and Key Results (OKR) is an approach that focuses on the company's goals through trust-based agreements between leaders and employees. With the OKR framework in its original form, strategic business goals are aligned with the employees' active involvement, which promotes intrinsic motivation, transparency, commitment, and alignment. Inspired by the successes at Google and Intel and shaped by its use in the tech industry, the use of OKR increased across industries. Although companies within all sectors use the OKR framework, numerous implementation efforts fail. The challenges of practitioners are not fully addressed in the development of implementation concepts for OKR. One main reason is that these challenges are not taken into account in scientific publications. The paper aims to investigate to what extent existing OKR frameworks need to be adapted to provide companies with suiting implementation guidance. Firstly, OKR is placed in the context of academically widely discussed Performance Management Systems (PMS).
Secondly, criteria for successful PMS implementation are identified and used as a baseline for analyzing existing OKR implementation concepts. A systematic literature review shows the current state of research, identifying existing OKR implementation concepts from practice and theory. The OKR implementation concepts identified are systematically mapped to the series of identified criteria for PMS implementation. It is shown that the existing OKR frameworks do not address the described criteria necessary for a successful implementation of PMS, thus the adaptation of existing OKR implementation concepts is required.
The development of renewable energies and smart mobility has profoundly impacted the future of the distribution grid. An increasing bidirectional energy flow stresses the assets of the distribution grid, especially medium voltage switchgear. This calls for improved maintenance strategies to prevent critical failures. Predictive maintenance, a maintenance strategy relying on current condition data of assets, serves as a guideline. Novel sensors covering thermal, mechanical, and partial discharge aspects of switchgear, enable continuous condition monitoring of some of the most critical assets of the distribution grid. Combined with machine learning algorithms, the demands put on the distribution grid by the energy and mobility revolutions can be handled. In this paper, we review the current state-of-the-art of all aspects of condition monitoring for medium voltage switchgear. Furthermore, we present an approach to develop a predictive maintenance system based on novel sensors and machine learning. We show how the existing medium voltage grid infrastructure can adapt these new needs on an economic scale.
Towards a Methodology to Determine Intersubjective Data Values in Industrial Business Activities
(2021)
This paper contributes to a valuation framework for valuing data as an intangible asset. Especially those industrial manufacturers developing and delivering holistic digital solutions are limited in calculating the true business value of data initiatives. Since the value of data is strongly dependent on the respective use case, a completely objective valuation is not possible. This complicates decision-making on the internal side regarding investments in digital transformation, and on the external side to communicate existing benefits to third parties via financial reporting. Therefore, the target is to design a valuation framework that allows industrial manufacturers to determine an intersubjective, i.e., traceable and transparent, data value. In order to develop a framework that can be applied in practice, the approach is based on industrial case study research.
Competitive differentiation in the manufacturing sector is no longer based on product and service innovations alone but on the ability to monetize the usage phase of products and services. To this end, manufacturers are increasingly looking at so-called subscription business models as a way of supplementing the traditional sale of products and services. Since supplier success in the subscription business is directly dependent on customer success, the setup and expansion of a so-called Customer Success Management (CSM) is required. While CSM has already been established in the software industry for several years, companies in the manufacturing sector are often still in the conceptual phase of a CSM, parallel to the setup and expansion of their subscription business. Therefore, this paper aims to support the set-up of a CSM by providing a reference data model, based on case study research, that can be used to support the organizational or daily CSM tasks and to serve as a blueprint for conceptualizing CSM-specific IT systems.
Manufacturing companies are constantly increasing their efforts in the subscription business, also known as product-as-a-service business, offering usage and outcome based solutions (value-in-use) instead of transactional services and products (value-in-exchange). Customers are becoming contractual subscribers of the solution in return for recurring, performance-related payments. To address arising, inevitable challenges like (1) reducing customer churn, (2) increasing usage intensity and outcome quality, (3) ensuring the adoption of product and software releases as well as (4) fostering customer loyalty, leading manufacturing companies are setting up a new organizational, customer-facing unit, called Customer Success Management (CSM). This unit has its origins in the software-as-a-service business, operating next to established entities like sales, key account management and customer service. Since there are currently no holistic models for an end-to-end description of CSM-tasks in the manufacturing industry, this paper contributes to a taskoriented reference model, using a grounded theory approach, examining both manufacturing and software companies. Containing a reference framework with 8 main tasks, 17 basic tasks and 76 elementary tasks, the reference model supports manufacturing companies in adapting and customizing a company-specific CSM concept.
This paper contributes to an assessment framework for valuing data as an asset. Particularly industrial manufacturers developing and delivering Smart Product Service Systems (Smart PSS) are comprehensively depended on the business value derived by processing data. However, there is a lack in a framework for capturing and comparing the Smart PSS data value with the purpose of increasing the accountability of data initiatives. Therefore a qualitative data value assessment approach was developed and specified on Smart PSS, based on an industrial case study research. [https://link.springer.com/chapter/10.1007/978-3-030-57997-5_39]
Organizations, of all sizes, in every domain and in all geographies, are facing growing challenges to comprehend the scope of social media based technologies for their internal process use and for their networks. To assist the CIO’s and executives, FIR has developed a tool based framework to evaluate the impact of social web based collaborative technologies to support knowledge intensive processes. The FSI framework extends organizational spectrum to three categories of Formal, Semi-formal and Informal. The FSI tool places the emphasis on both business process and IT level.
The FSI framework and approach are validated in conjunction with industrial and research clients as test cases. Initial finding, reflected in this article, show a dire mismatch between the process exploitable potential level and organizational ICT profile. At the end, a set of recommendations are included for the organizational management to consider for organizational transformation.
Due to shorter product life cycles and the increasing internationalization of competition, companies are confronted with increasing complexity in supply chain management. Event-based systems are used to reduce this complexity and to support employees' decisions. Such event-based systems include tracking & tracing systems on the one hand and supply chain event management on the other. Tracking & tracing systems only have the functions of monitoring and reporting deviations, whereas supply chain event management systems also function as simulation, control, and measurement. The central element connecting these systems is the event. It forms the information basis for mapping and matching the process sequences in the event-based systems. The events received from the supply chain partner form the basis for all downstream steps and must, therefore, contain the correct data. Since the data quality is insufficient in numerous use cases and incorrect data in supply chain event management is not considered in the literature, this paper deals with the description and typification of incorrect event data. Based on a systematic literature review, typical sources of errors in the acquisition and transmission of event data are discussed. The results are then applied to event data so that a typification of incorrect event types is possible. The results help to significantly improve event-based systems for use in practice by preventing incorrect reactions through the detection of incorrect event data.
This paper addresses the challenge of modelling individual cyber-physical systems (CPS) for small and medium-sized enterprises (SMEs) in manufacturing industries. CPS are key technology building blocks for the implementation of Industrie 4.0. Especially for SMEs the increase of production efficiency and reduction of manufacturing costs through CPS offer potential to maintain their competitiveness and innovation capacity. Although SMEs perceive the potential of CPS, they often lack financial and human resources to acquire the necessary CPS-competencies as well as an overview of all the currently available technological solutions. To overcome this issue a matching platform will offer SMEs support in finding suitable CPS-components by letting them express their functional and technical requirements. The matching logic is based on a set of morphologies that encompasses the functional and requirement spectrum of CPS-components. The matching algorithm analyses the input for congruence of requirements and available technologies and suggests suitable technology combinations. This paper describes the methodology of the matching platform, and introduces the research work to define and to develop the technology morphologies. The presented results facilitate the selection and configuration of CPS for SMEs.
The digitalization of manufacturing processes is expected to lead to a growing interconnection of production sites, as well as machines, tools and work pieces. In the course of this development, new use-cases arise which have challenging requirements from a communication technology point of view. In this paper we propose a communication network architecture for Industry 4.0 applications, which combines new 5G and non-cellular wireless network technologies with existing (wired) fieldbus technologies on the shop floor. This architecture includes the possibility to use private and public mobile networks together with local networking technologies to achieve a flexible setup that addresses many different industrial use cases. It is embedded into the Industrial Internet Reference Architecture and the RAMI4.0 reference architecture. The paper shows how the advancements introduced around the new 5G mobile technology can fulfill a wide range of industry requirements and thus enable new Industry 4.0 applications. Since 5G standardization is still ongoing, the proposed architecture is in a first step mainly focusing on new advanced features in the core network, but will be developed further later.
In diesem Paper wird eine Architektur für Kommunikationsnetze für industrielle Anwendungen vorgestellt, die neue 5G-Technologien mit vorhandener Kommunikationstechnik auf der Feldbusebene kombiniert. Diese Architektur verbindet private und öffentliche Mobilfunknetze mit lokalen Funktechnologien, um einen flexiblen Aufbau zu ermöglichen, der in der Lage ist, viele industrielle Anwendungsfälle zu unterstützen. Es wird gezeigt, wie die Errungenschaften, die mit der neuen 5G-Technologie eingeführt werden, einen großen Bereich der industriellen Anforderungen erfüllen können. Weiterhin werden relevante Anwendungsfälle beschrieben und eine Gesamtsystemarchitektur vorgeschlagen, welche nicht nur die technischen, sondern auch die funktionalen Anforderungen, welche von den spezifischen Anwendungen heutiger und zukünftiger Herstellungsprozesse gestellt werden, erfüllen kann.
Schwerwiegende Gesundheits- und Wirtschaftskrisen wie die Weltfinanzkrise (ab 2007) oder die Covid-19-Pandemie im Jahr 2020 haben aufgezeigt, in welch turbulentem Umfeld sich die globalisierte Welt heutzutage befindet und wie schnell gewohnte Abläufe in Wertschöpfungsketten unterbrochen und angepasst werden müssen. Die alltäglichen Anforderungen in dem sich immer schneller wandelnden digitalen Zeitalter wachsen stetig und sind komplexer denn je.
Unternehmen sind angehalten, immer kurzzyklischer auf sich ändernde
Bedingungen und Störungen zu reagieren und strategische Entscheidüngen
zur Gestaltung von Wertschöpfungsketten zu treffen. Nur mithilfe
einer umfassenden Datengrundlage und -kommunikation kann die strategische Planung der Supply-Chain effektiv erfolgen und somit die benötigte Robustheit und Agilität ermöglicht werden.
The do-it-yourself mentality is particularly widespread in the furniture sector. Homemade furniture is very popular. The individualisation of furniture can be observed in internet forums, such as the online platform Pinterest. These creative ideas of potential customers show a need for individualized sustainable pieces of furniture. The current production structures, however, do not allow individual production according to the end customer's specifications. In addition, information logistics faces a major challenge: making the creative ideas of end consumers available to producers in parametric form. Topics such as customer requirements in relation to sustainable production, material specifications, industrial property rights, fair production conditions and traceability are the focus of this data interchange. An open and innovative European furniture ecosystem must be created to connect all stakeholders in the production process. This is made possible by a platform that channels the creativity of consumers and makes it designable and producible through the professional skills of designers. This requires the involvement of manufacturing specialists who can produce personalised products through sustainable intelligent production technologies. An exchange of information must also take place securely and quickly in order to protect the personal rights of the sources of ideas. This is being developed in the EU research project INEDIT - Open Innovation Ecosystem for do-it-together process. By connecting many different stakeholders along the entire value creation process, a change towards efficient collaborative collaboration is achieved. This paper presents a project insight for the development of an international co-creation platform by presenting the problem and linking it to a potential solution.
Industrial practice shows a strong trend towards digitalization. It is not only economic crises, such as those triggered by Covid-19, that are reinforcing this trend. It is also the entrepreneurial urge to fulfill customer wishes in the best possible way and to adapt to new requirements as quickly as possible. Due to the advancing digitalization, the role of business application systems in manufacturing companies is therefore becoming increasingly important. The data processed in IT-Systems represent a great potential, especially for the evaluation of change requests in production. Through efficient change management, companies can record and process changes quickly. However, the necessary data basis to decide on existing change requests is still hardly used. Existing IT-Systems for change management coordinate the processing of change requests, but do not relate to data of operational application systems such as Enterprise-Resource-Planning. Therefore, a conceptual approach is required for the evaluation of change requests. This approach is based on an objective recording system that enables the transformation from the change description to an evaluation space. The paper presents an approach for the systematic transfer of requirement characteristics into the world of operational IT-Systems.
Störungen und Änderungen des Produktionssystems führen zu Kosten und Aufwänden, bieten jedoch auch die Chance zur kontinuierlichen Verbesserung.
Um Änderungsanfragen zu erfassen, können etablierte Ansätze genutzt werden. Diese vernachlässigen jedoch die Anforderungen, denen sich ein Produktionssystem im Zeitalter der Digitalisierung ausgesetzt sieht. Der vorliegende Beitrag stellt einen Ansatz zur standardisierten Erfassung von Änderungsanfragen vor, welcher die Ausgangsbasis für die Bewertung von Änderungsanfragen in bestehenden IT-Systemen bietet.