Refine
Year of publication
Document Type
- Article (9)
- Book (4)
- Part of a Book (25)
- Conference Proceeding (86)
- Contribution to a Periodical (17)
- Doctoral Thesis (1)
- Lecture (4)
- Internet Paper (4)
- Preprint (1)
- Report (2)
Language
- German (63)
- English (95)
- Multiple languages (2)
Is part of the Bibliography
- no (160)
Keywords
- 02 (19)
- 03 (3)
- 3GPP (1)
- 5G (5)
- 5G mobile communication (2)
- 5G use case (1)
- 5G-Mobilfunk (1)
- 5G-Technology (1)
- AI (2)
- Aachener PPS-Modell (1)
- Abschlussbericht (1)
- Adaptability (1)
- Additive Fertigung (1)
- Adherence To Delivery Dates (1)
- After-Sales-Service (1)
- Agile management Systems (1)
- Agriculture (1)
- Anlaufmanagement (1)
- Arbeit 4.0 (2)
- Arbeitsgestaltung (2)
- Artificial intelligence (1)
- Assembly (1)
- Asset Management (1)
- Assistance Systems (1)
- Augmented Reality (1)
- Automobilindustrie (1)
- B2B customer service (1)
- BITKOM (1)
- Beratung (1)
- Big Data (2)
- BigPro (1)
- Blockchain (1)
- Business analytics (2)
- Business ecosystems (1)
- Business model innovation (1)
- Business-Ecosystems (1)
- CPS (4)
- CPSL (1)
- Capacity Utilization (1)
- Carrier (1)
- Case study research (1)
- Change Management (1)
- Change Request (2)
- Changeability (1)
- Chatbot (1)
- Circular economy (1)
- Cloud (1)
- Cluster Smart Logistik (1)
- Co-Creation (2)
- Competencies (1)
- Crisis management (1)
- Cross-Industry Innovation (1)
- Customer Perspective (1)
- Customer Success Management (1)
- Customer success managementl (1)
- Customer-Success-Management (1)
- Cyber Security (1)
- Cyber physical production control (1)
- DMS (1)
- Data Analytics (1)
- Data Products (1)
- Data Quality (1)
- Data analytics (1)
- Data-Centric Platform (1)
- Data-based pricings (1)
- Data-driven Services (1)
- Data-driven decision (1)
- Data-driven services (1)
- Datenaustausch (2)
- Datenmanagement (1)
- Datenpotenziale (1)
- Datensouveränität (1)
- Decision Support (2)
- Decision Support System (1)
- Decision support (1)
- Demand Forecasting (1)
- Design of Experiments (1)
- Deviation Detection (1)
- Dienstleistung (1)
- Dienstleistungssektor (1)
- Dienstleistungswende (1)
- Digital Office (1)
- Digital Transformation (1)
- Digital architecture management (1)
- Digital platform design (1)
- Digital transformation (1)
- Digital-Architecture-Management (1)
- Digital-Business-Model (1)
- Digitale Infrastrukturen (1)
- Digitale Steuerung (1)
- Digitale Transformation (2)
- Digitales Zeitalter (1)
- Digitalisation (1)
- Digitalisierung (10)
- Digitalization (1)
- Digitization (2)
- Digitization of SMEs (1)
- Discrete Event Simulation (1)
- Disruption Management (1)
- Disruptions (1)
- Distribution (1)
- Distribution management (1)
- Distributionsplanung (1)
- Disturbance Management (1)
- Do-it-together (1)
- E-Learning (1)
- ECM (1)
- EPCIS (1)
- ERP (2)
- ERP-System (1)
- Echtzeitfähige Systeme (1)
- Echtzeitfähigkeit (1)
- Ecosystem-Design (1)
- Efficiency Improvement (1)
- Employee qualification (1)
- End-2-End-Transparenz (1)
- Energiemanagement (2)
- Enterprise-Resource-Planning (1)
- Entscheidungsunterstützung (3)
- Ersatzteillogistik (1)
- Evaluation (2)
- Event Data (1)
- Expertise (1)
- Fallstudien (1)
- Feedback data (1)
- Finanzkrise (1)
- Flexibilität (1)
- Flexible manufacturing system (1)
- Food Production (1)
- Footprint design (1)
- Forecasting capability (1)
- Forschung (1)
- Forschungsbeirat (1)
- Freight forwarder (1)
- Furniture Production Process (1)
- Führungskraft (1)
- Geschäftsmodell (2)
- Geschäftsmodelle (1)
- Global production (1)
- Heterogene Netze (1)
- Heterogeneous networks (1)
- Human-centered work design (1)
- Humanitarian logistics (1)
- IT complexity (1)
- IT-Architektur (2)
- IT-Komplexität (1)
- IT-Unterstützung (1)
- Implementation barriers (1)
- Implementation success factors (1)
- Incorrect Data (1)
- Industrial Internet of Things (1)
- Industrial communication (1)
- Industrial sustainability (1)
- Industrie (1)
- Industrie 4.0 (18)
- Industrielle Kommunikationstechnik (1)
- Industry 4.0 (1)
- Information Logistics (1)
- Information Transparency (1)
- Information management (1)
- Informationslogistik (1)
- Informationsmanagement (1)
- Innovation (1)
- Innovative Furniture (1)
- Instandhaltung (1)
- Insufficient Data (1)
- Integration management (1)
- Integrationsmangement (1)
- Intelligent Product (1)
- Interface definition (1)
- Internet der Dinge (2)
- Internet of Production (4)
- Internet of Production (IoP) (1)
- Internet of Things (3)
- IoP (1)
- IoT (1)
- IoT platform (1)
- IoTPlattform (1)
- KI (5)
- KMAT (1)
- KMU (2)
- KPI (2)
- Kennzahlen (1)
- Key Performance Indicators (1)
- Key-Performance-Indicator (1)
- Knowledge representation (1)
- Kommunikation (1)
- Kompetenzentwicklung (2)
- Kompetenzmanagement (3)
- Konferenz (2)
- Konfigurierbare Materialien (1)
- Kongress (1)
- Konzepte (1)
- Krise (1)
- Kundendienst (1)
- Kundenprobleme (1)
- Kybernetik (1)
- Künstliche Intelligenz (5)
- Lean Manufacturing (1)
- Learning Game (1)
- Lebensmittelindustrie (1)
- Leistungsfähigkeit (2)
- Lernen (1)
- Lernen und Arbeiten (2)
- Letzte-Meile-Logistik (1)
- Lieferketten (1)
- Logistik (5)
- Logistikdienstleister (1)
- MES (1)
- Machine Learning (1)
- Machine learning (1)
- Machine-to-machine communications (1)
- Manufacturing (2)
- Manufacturing Companies (2)
- Manufacturing Execution System (1)
- Manufacturing firms (1)
- Manufacturing industry (1)
- Maschinen- und Anlagenbau (1)
- Matching (2)
- Maturity Index (1)
- Maturity Model, Maturity Index (1)
- Maturity model (1)
- Mechanical and Plant Engineering (1)
- Mittelstand (1)
- Mixed-Model Assembly (1)
- Modellierung (1)
- Morphology (2)
- Multi-RAT (1)
- Nachhaltigkeit (1)
- Natural-Language-Processing (1)
- Network (1)
- Network architecture (1)
- Network configuration (1)
- Network function virtualization (1)
- Network slicing (1)
- Networked (1)
- Netzwerk (1)
- Netzwerkarchitektur (1)
- New Industrial Work (2)
- New Work (2)
- New learning (1)
- Online retail (1)
- Onlinehandel (1)
- Ontology (1)
- Operating models (1)
- Operations planning (1)
- Optimized capacity utilization (1)
- Order Quantity (1)
- PPC (1)
- PPS (3)
- PPS-Buch (1)
- Performance-Management (1)
- Plastics industry (1)
- Platform (1)
- Platform economy (1)
- Plattform Industrie 4.0 (1)
- Potential Benefits (1)
- Practical experience (1)
- Predictive Maintenance (1)
- Prescriptive Maintenance (2)
- Pricing Models (1)
- Procurement Strategy (1)
- Product Characteristics (1)
- Product-as-a-service business (1)
- Production (1)
- Production Control (3)
- Production Management System (1)
- Production Planning (1)
- Production facilities (1)
- Production management (2)
- Production networks (1)
- Produktdatenmanagement (1)
- Produktentwicklung (1)
- Produktionsabläufe (1)
- Produktionsmanagement (2)
- Produktionsplanung (6)
- Produktionsplanung und -steuerung (2)
- Produktionssteuerung (6)
- Produktionssystem (2)
- Quarrying Industry (1)
- Quarrying industry (1)
- Re- & upskilling (1)
- Reaktionsfähigkeit (1)
- Realisierung (1)
- Reference data model (1)
- Reference model (1)
- Regulatory framework (1)
- Relay traffic (1)
- Reliability (1)
- Replenishment Time (1)
- Requirements (1)
- Resource deployment (1)
- Return on Investment (1)
- Rezepte (1)
- Risikomanagement (2)
- Risk assessment (1)
- Risks (1)
- Route sectioning algorithm (1)
- SCEM (1)
- SCM (2)
- SME (1)
- SV7067 (1)
- SV7088 (1)
- SV7113 (1)
- SV7126 (1)
- SV7131 (1)
- SV7136 (1)
- SV7169 (1)
- SV7190 (1)
- SV7213 (1)
- SV7240 (1)
- SV7242 (1)
- SV7261 (1)
- SV7266 (1)
- SV7276 (1)
- SV7289 (1)
- SV7344 (1)
- SV7371 (1)
- SV7404 (1)
- SV7420 (1)
- SV7427 (1)
- SV7436 (1)
- SV7459 (1)
- Scenario pattern (1)
- Scenario technique (1)
- Selbstoptimierung (2)
- Sensors (1)
- Service (1)
- Service engineering (1)
- Service-Management (1)
- Setup time optimizing sequencing (1)
- Similarity Analysis (1)
- Simulation (1)
- Skills forecasting (1)
- Skills management (1)
- Smart Service (1)
- Smart Services (4)
- Smart farming (1)
- Smart product service system (1)
- Smart services (1)
- Smartification (1)
- Social Manufacturing (1)
- Socio-technical analysis (1)
- Sociotechnical (1)
- Software defined networking (1)
- Software defined platform (1)
- Softwaretool (1)
- Strategie (1)
- Strategy (1)
- Studie (3)
- Störungsmanagement (2)
- Subscription (2)
- Subscription Business (1)
- Subscription Business Models (1)
- Subscription business (2)
- Subscription-Economy (1)
- Subscription-Modelle (1)
- Suchmaschine (1)
- Supply Chain Event Management (2)
- Supply Risks (1)
- Supply chain (1)
- Supply-Chain (1)
- Supply-Chain-Design (2)
- Supply-Chain-Management (10)
- Supply-Chain-Networks (1)
- Supply-Chain-Resilienz (1)
- Sustainability (4)
- Swarm robotics (1)
- Systemplattform (1)
- Task View (1)
- Task-oriented Reference Model (1)
- Taxonomy (1)
- Technischer Wandel (1)
- Training (1)
- Transformation (1)
- Transport order (1)
- Trends (1)
- Twin transition (1)
- Type-specific (1)
- Typification (2)
- Typology (1)
- U1021 (1)
- Unternehmensberatung (1)
- Urbane Logistik (1)
- User-Story (1)
- Value capture (1)
- Value creation (1)
- Value-based Pricing (1)
- Value-in-Use (1)
- Value-in-use (2)
- Variantenfließfertigung (1)
- Vernetzung (1)
- Viable System Model (2)
- Visual Analytics (1)
- Vorgabezeit (1)
- Vorgehensmodell (1)
- Weiterbildung (1)
- Whitepaper (1)
- Wireless communication (1)
- Wirtschaft (1)
- Wirtschaftskrise (1)
- Wissenschaft (2)
- Wissensmanagement (1)
- Zeitwirtschaft (1)
- Zertifikatskurs (1)
- acatech industrie 4.0 Maturity Index (1)
- acquisition cycle (1)
- agile company (1)
- air mobility (1)
- analysis of potential (1)
- artificial intelligence (1)
- artificial neural networks (1)
- asset management (1)
- attribute and data harmonization (1)
- autonomous technology scouting (1)
- blockchain (1)
- blockchain-based services (1)
- bullwhip effect (1)
- business ecosystems (1)
- business model (3)
- case study research (3)
- classification systems (1)
- condition monitoring (2)
- control theory (1)
- counter measures (1)
- criticality analysis (1)
- cyber-physische Systeme (1)
- cybernetics (1)
- data democratization (1)
- data valuation framework (2)
- data value (3)
- data value assessment (1)
- datenbasierte Entscheidungen (1)
- decision making (1)
- decision support (2)
- deep learning (1)
- design (1)
- deviation detection (1)
- digital services (1)
- digital shadow (3)
- digitale Technologien (2)
- digitale Transformation (1)
- digitalization (1)
- disruption management (1)
- disruptions (1)
- disturbance management (2)
- ecosystem design (1)
- energy consumption (1)
- energy efficiency (1)
- energy revolution (1)
- engineering valley (1)
- enterprise resource planning system (1)
- flight demand (1)
- fourth industrial revolution (1)
- human-robot collaboration (1)
- hybride Systeme (1)
- hype cycle (1)
- i4.0 (1)
- iIntangible assets (1)
- industrial pilots (1)
- industry (1)
- industry 4.0 (1)
- information logistics model (1)
- information management (1)
- infrared sensor (1)
- innovation processes (1)
- intangible assets (1)
- intelligent maintenance systems (1)
- intelligent support system (1)
- internet of production (1)
- inventory management (2)
- it-architecture (1)
- logistics (1)
- machine learning (3)
- machine tools (1)
- machinery and plant engineering industry (1)
- maintenance engineering (1)
- maintenance services (1)
- maintenance value contribution (1)
- manufacturing (1)
- manufacturing companies (2)
- microgrids (1)
- milling (1)
- natural language processing (1)
- nonlinear optimization (1)
- order (1)
- order processing (1)
- peak flattening (1)
- predictive maintenance (1)
- process mining (1)
- procurement (1)
- procurement strategy (1)
- production control (1)
- production management (1)
- production network (1)
- production networks (1)
- production planning and control (1)
- reaction strategy (1)
- real-time systems (1)
- realtime capability (1)
- recursion level (1)
- resilience (1)
- rev (31)
- risk analysis system (1)
- risk management (1)
- science (1)
- service engineering (1)
- smart product service systems (2)
- smart services (1)
- subscription business (1)
- subscription business models (1)
- supply chain (3)
- supply chain event management (1)
- supply chain management (2)
- supply risks (1)
- switchgear (1)
- system dynamics (3)
- task model (1)
- technology management (1)
- technology scouting (1)
- text mining (1)
- textile supply chain (1)
- thermal monitoring (1)
- thin-haul (1)
- transport demand (1)
- viable system model (2)
- Änderungsmanagement (2)
- übergreifende Koordination (1)
Institute
- FIR e. V. an der RWTH Aachen (160) (remove)
Die Globalisierung und der steigende Wettbewerbsdruck erfordern, dass Supply Chains heutzutage komplexe Anforderungen erfüllen. Dabei müssen sie gleichzeitig flexibel genug sein, um an kurzfristige Veränderungen angepasst werden zu können. Ein unternehmensübergreifender Datenaustausch ermöglicht den Akteuren durch schnelle Informationsweitergabe über auftretende Ereignisse entlang der Supply Chain, dynamisch auf aktuelle Gegebenheiten zu reagieren und dadurch hervorgerufene mögliche Schäden zu minimieren. Auch wenn viele Unternehmen mit der Bereitstellung von Daten noch zurückhaltend sind, gehen die Vorteile des Datenaustauschs weit über die Verkürzung der Reaktionszeit hinaus.
Das Gegenteil von Theorie ist die Praxis. So sagt man landläufig und unterstellt damit oft, dass wissenschaftiche Erkenntnisse nicht immer für den Alltag taugen. Dass Theorie aber nicht gleich Theorie ist und Wissenschaft und Praxis trotz aller Unterschiedlichkeit aufeinander angewiesen sind, darauf weist das
FIR an der RWTH Aachen schon mit der Auflösung seines Akronyms hin: „Forschung. Innovation. Realisierung."
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.
Companies operate in an increasingly volatile environment where different developments like shorter product lifecycles, the demand for customized products and globalization increase the complexity and interconnectivity in supply chains. Current events like Brexit, the COVID-19 pandemic or the blockade of the Suez canal have caused major disruptions in supply chains. This demonstrates that many companies are insufficiently prepared for disruptions. As disruptions in supply chains are expected to occur even more frequently in the future, the need for sufficient preparation increases. Increasing resilience provides one way of dealing with disruptions. Resilience can be understood as the ability of a system to cope with disruptions and to ensure the competitiveness of a company. In particular, it enables the preparation for unexpected disruptions. The level of resilience is thereby significantly influenced by actions initiated prior to a disruption. Although companies recognize the need to increase their resilience, it is not systematically implemented. One major challenge is the multidimensionality and complexity of the resilience construct. To systematically design resilience an understanding of the components of resilience is required. However, a common understanding of constituent parts of resilience is currently lacking. This paper, therefore, proposes a general framework for structuring resilience by decomposing the multidimensional concept into its individual components. The framework contributes to an understanding of the interrelationships between the individual components and identifies resilience principles as target directions for the design of resilience. It thus sets the basis for a qualitative assessment of resilience and enables the analysis of resilience-building measures in terms of their impact on resilience. Moreover, an approach for applying the framework to different contexts is presented and then used to detail the framework for the context of procurement.
The environment in which companies operate is increasingly volatile and complex. This results in an increased exposure to disruptions. Past disruptions have especially affected procurement. Thus, companies need to prepare for disruptions. The preparedness for disruptions in the context of procurement is significantly influenced by the design of the procurement strategy. However, a high number of purchased articles and a variety of influencing factors lead to high complexity in procurement. The systematic design of the procurement strategy should therefore take into account the criticality of the purchased articles. This enables to focus on the purchased articles that have a high impact on the disruption preparedness. Existing approaches regarding the design of the procurement strategy in uncertain environments either lack practical applicability and objective evaluation or focus on the criticality of raw materials rather than of purchased articles. Therefore, a data-based approach for the systematic design of the procurement strategy in the context of the Internet of Production has been proposed. One central aspect of this approach is the identification of success-critical purchased articles. Thus, this paper proposes a framework for characterizing purchased articles regarding supply risks by combining two systematic analyses. First, a systematic literature review is performed to answer the question of what factors can be used to describe the supply risks of purchased articles. The results are analyzed regarding sources and impacts of risks and thus contribute to a structured characterization of supply risks. Second, existing criticality assessment approaches for raw materials are analyzed to identify categories and indicators that describe purchased articles. The results of both reviews provide the basis for linking product characteristics with supply risks and assessing product criticality which will be integrated into an app prototype.
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.
In the food industry, a very large potential of data ecosystems is seen, in which data is understood, exchanged and monetized as an economic asset. However, despite the enormous economic potential, companies in the food industry continue to rely on traditional, product-oriented business models. Existing data in the value chain of industrial food production, e.g., in harvesting, logistics, and production processes, is primarily used for internal optimization and is not monetized in the form of data products. Especially the pricing of data products is a key challenge for data-based business models due to their special characteristics compared to conventional, analog offerings and multiple design options. The goal of this work is therefore to solve this issue by developing a framework that allows the identification of pricing models for data products in the industrial food production. For this purpose, following the procedure of typology formation, essential design parameters and the respective characteristics are derived. Furthermore, three types for pricing models of data products are shown. The results will serve not only stakeholders in the food industry but also manufacturing companies in general as input for an orientation of their databased business models.
Eine wesentliche Bedingung zur Optimierung der Wertschöpfungsprozesse ist die Transparenz über die leistungsbestimmenden Faktoren eines Unternehmens. Die Ermittlung dieser Faktoren stellt für viele Industriebetriebe eine Herausforderung dar. Im Rahmen der Veröffentlichung wird daher eine Vorgehensweise zur systematischen Identifikation von Einflussfaktoren der Unternehmenskennzahlen vorgestellt, welche die Grundlage zur Ableitung von individuellen Stellhebeln zur Steigerung der Unternehmensleistungsfähigkeit darstellt.
Der vorliegende Beitrag beschreibt eine Vorgehensweise zur kurzfristigen Umstellung von Blended-Learning- oder Präsenzangeboten. Hierbei werden neben möglichst schnell umsetzbaren technischen Lösungen auch notwendige organisatorische Anpassungen thematisiert und anhand des E-Mas-Weiterbildungsprogramms illustriert.
Recent developments have demonstrated the challenges and impacts of disruptions in supply chains. Current disruptions especially affected procurement and have indicated a lack of resilience. Resilience aims at being prepared, decreasing the impact, and enabling fast reactions and adaption in case of disruptions. The systematic design of resilience in procurement is significantly influenced by proactive and strategic actions before disruptions occur. Thus, the procurement strategy plays a major role when increasing resilience. The procurement strategy is influenced by various factors. Thus, a data-based approach for its systematic design is required. Based on the vision of the Internet of Production (IoP), this paper presents a data-based approach for designing procurement strategies. The IoP is a framework that enables cross-domain collaboration by providing semantically adequate and contextual data from production, development, and usage in real-time at an appropriate granularity. The paper aims at analyzing the state of the art regarding the design of procurement strategy in uncertain environments and the identification of success-critical purchased articles. Based on this, an approach is developed that is structured along the action research cycle and uses CRISP-DM to further detail the different steps. Through the use of these frameworks, both practical applicability and objective evaluation are ensured. The proposed approach thus allows the systematic evaluation of purchased articles regarding supply risks and lies the foundation for the adaption of the procurement strategy. The resulting approach is the foundation for future practical application of different use cases. As one central use case for the presented approach, the paper introduces the textile industry and its supply chains.
Als Beispiel einer globalen Krisensituation zeigt die COVID-19-Pandemie eindrucksvoll die Schwachstellen heutiger Wertschöpfungsnetzwerke. Vor dem Hintergrund zunehmend komplexer und vernetzter Wertschöpfungsnetzwerke steigt für Unternehmen die Bedeutung einer resilienten Gestaltung derselben. Dabei wird davon ausgegangen, dass ähnliche Krisensituationen in Zukunft häufiger auftreten werden. Ziel dieser Expertise ist es, Unternehmen bei der Identifikation von Potenzialen und Maßnahmen für die resiliente Gestaltung ihrer Wertschöpfungsnetzwerke zu unterstützen.
Glück per Abo
(2019)
Was charakterisiert einen Menschen jenseits seines offensichtlichen Verhaltens und seiner äußeren Gestalt? Wohl nichts so sehr wie seine Bedürfnisse und Wünsche. „Am Ende existiert der Mensch nur durch seine Bedürfnisse“, bringt es der Dichter Friedrich Hebbel überspitzt auf den Punkt. Doch wie sehen diese Bedürfnisse aus?
In the age of digitalization, manufacturing companies are under increased pressure to change due to product complexity, growing customer requirements and digital business models. The increasing digitization of processes and products is opening up numerous opportunities for mechanical engineering companies to exploit the resulting potential for value creation. Subscription business is a new form of business model in the mechanical engineering industry, which aims to continuously increase customer benefit to align the interests of both companies and customers. Characterized by a permanent data exchange, databased learning about customer behavior, and the transfer into continuous innovations to increase customer value, subscription business helps to make Industry 4.0 profitable. The fact that machines and plants are connected to the internet and exchange large amounts of data results in critical information security risks. In addition, the loss of knowledge and control, data misuse and espionage, as well as the manipulation of transaction or production data in the context of subscription transactions are particularly high risks. Complementary to direct and obvious consequences such as loss of production, the attacks are increasingly shifting to non-transparent and creeping impairments of production or product quality, which are only apparent at a late stage, or the influencing of payment flows. A transparent presentation of possible risks and their scope, as well as their interrelationships, does not exist. This paper shows a research approach in which the structure of subscription models and their different manifestations based on their risks and vulnerabilities are characterized. This allows suitable cyber security measures to be taken at an early stage. From this basis, companies can secure existing or planned subscription business models and thus strengthen the trust of business partners and customers.
Die Zukunftspotenziale der digitalen Technologie könnten den Dienstleistungssektor entscheidend transformieren und damit der schrumpfenden Wettbewerbsfähigkeit der deutschen Wirtschaft neuen Schwung verleihen.
Das Schiff des Wirtschaftsstandorts Deutschland schwankt in rauer werdender See. Es schwankt weniger, weil die traditionellen deutschen Wertschöpfungssäulen (insbesondere die Flaggschiffe Automobil- und Maschinenbau sowie Chemie- und Logistikindustrie) hierzulande an Know how eingebüßt hätten; es sind vielmehr die großen Technologiedurchbrüche der letzten Jahrzehnte, die die deutschen Tugenden, welche mehr als ein Jahrhundert lang für einen Spitzenplatz unter den großen Wirtschaftsmächten gesorgt haben, drastisch an Bedeutung verlieren lassen. Perfektionismus, Verarbeitungsqualität, Zuverlässigkeit und Langlebigkeit von Produkten aller Art sicherten der deutschen Wirtschaft über viele Jahrzehnte hinweg internationales Ansehen. Das führte allerdings zu einer gewissen Selbstzufriedenheit, die die eigene Spitzenposition in der Welt als Selbstläufer ansah. Verliebt in die eigene Perfektion (der Strategieberater und Blogger Sascha Lobo spricht plakativ von einer „Spaltmaßfixierung“ ganzer Wirtschaftszweige) und an permanenter rein inkrementeller Innovation orientiert, hinkt Deutschland auf wichtigen Gebieten der künftigen Wertschöpfungsfelder dem Wettbewerb gefährlich hinterher – insbesondere auf dem für die Zukunft entscheidenden Technologiegebiet der Digitalisierung.
Industry 4.0 and Smart Maintenance represent a great opportunity to make manufacturing and maintenance more effective, safer, and reliable. However, they also represent massive change and corresponding challenges for industrial companies, as many different options and starting points have to be weighed and the individual right paths for achieving Smart Maintenance need to be identified. In our paper, we describe our approach to evaluating maintenance organizations in a case study for the oil and gas industry, developing a shared vision for the future, and deriving economical and effective measures. We will demonstrate our approach, by showcasing a specific example from the oil and gas industry, where a need for action on HSE-relevant critical flanges in the company's piping systems was identified. We describe the steps, that were taken to identify the need for action, the specifications of the project and the criticality analysis of the piping system. This resulted in the derivation of a digitalization measure for critical flanges, which was first commercially analyzed and then the flanges were equipped with a continuous monitoring solution. Finally, a conclusion is drawn on the performed procedure and the achieved improvements.
Subscription business transforms traditional business models of machinery and plant engineering. Many manufacturing companies struggle to pull out the potential created by Industry 4.0 and make it economically usable. In addition to technological innovations, it is necessary to transform the business model. This leads to a shift from ownership-based and product-centric business models to outcome-based business models, which focus on the customer's value and thus realize a unique value proposition and competitive advantage – the outcome economy. Based on a case study analysis among manufacturing companies, this paper provides further clarification including a definition and constituent characteristics of subscription business models in machinery and plant engineering.
Eine Herausforderung für produzierende Unternehmen in der Entwicklung intelligenter Produkte besteht darin, dass die Zielstellung, die mit einem intelligenten Produkt verfolgt wird, nicht expliziert ist. Zudem ist oftmals nicht spezifiziert, in welchem Anwendungsfall ein intelligentes Produkt agieren soll. Produzierende Unternehmen benötigen Unterstützung, um eine zielorientierte und folglich wirtschaftliche Melioration existierender Produkte zu gewährleisten. Ebendiese Melioration wird im Kontext von intelligenten Produkten als Smartifizierung bezeichnet und stellt damit einen Entwicklungsprozess dar, der ein bestehendes Produkt als Ausgangssituation im Sinne einer Anpassungskonstruktion expliziert. Die originäre Produktfunktion wird folglich nicht verändert, sondern das Produkt um digitale Funktionen und Dienstleistungen erweitert. Der Artikel befasst sich daher erstens mit der Beschreibung generischer Ziele für den Einsatz intelligenter Produkte im Maschinenbau. Eine Zusammenstellung und Erläuterung solcher Ziele unterstützt Unternehmen, eine Präzisierung der Zielfestlegung in der Initiierungsphase eines Smartifizierungsprojekts durchzuführen. Zweitens wird unter Anwendung der Ziel-Mittel-Beziehung ein Anwendungsfall intelligenter Produkte beschrieben. Abschließend werden beide Aspekte in einer Methode zusammengefasst, wie mittels Ziel- und Anwendungsfallbetrachtung Anforderungen abgeleitet und wie diese Elemente in Vorgehensmodelle der Produktentwicklung eingebettet werden können. Exemplarisch wird anhand einer Stanzmaschine aufgezeigt wie die Methode und die sich daraus ableitenden Ergebnisse im Smartifizierungsprozess zur Entwicklung einer intelligenten Stanzmaschine eingesetzt werden.
The efficient dealing with the dynamic environment of production industries is one of the most challenging tasks of Supply Chain Management in high-wage countries. Relevant and current information are still not used sufficiently, to handle the influence of the dynamic environment on intra- and inter-company order processing adequately. Among other things, the problem is caused by missing or delayed feedback of relevant data. As a consequence of that, planning results differ from the actual situation of production. High Resolution Supply Chain Management describes an approach aiming on high information transparency in supply chains in combination with decentralized, self-optimizing control loops for Production Planning and Control. The final objective is to enable manufacturing companies to produce efficiently and to be able to react to order-variations at any time, requiring process structures to be most flexible.
Electricity generated by wind turbines (WT) is a mainstay of the transition to renewable energy. In order to economically utilize WT is, operating and maintenance costs, which account for 25% of total electricity generation costs in onshore WT’s, are a focus of cost reduction activities. Implementing a data-driven prescriptive maintenance approach is one way to achieve this. So far, various approaches for prescriptive maintenance for onshore WT’s have been suggested.
However, little research has addressed the practical implementation considering sociotechnical aspects. The aim of this paper is therefore to identify success factors for the successful implementation of such a maintenance strategy with clear and holistic guidance on how existing knowledge on prescriptive maintenance from science can be transferred to business practice. These recommendations are developed through case study research and classified in the four structural areas of Acatech’s Industry 4.0 Maturity Index: Resources, Information Systems, Organizational Structure and Culture.
Ongoing digitalization and Industry 4.0 enable the development of new business models due to the increase in available data and digital connected products. A promising business model type for the machinery and plant engineering industry are subscription models, consisting of products and services offered in return for continuous payments. However, subscription-based business models are associated with extensive changes in the traditional machinery and plant engineering industry, in particular, for small and medium-sized companies (SMEs). Established concepts for the development of value propositions and business models neglect important aspects, such as the integrated development and optimization of products and services across the entire life cycle or the data infrastructure. This paper presents a concept for a methodology to support SMEs developing value propositions within subscription models. Therefore, the systematic identification of customer benefits, the determination and prioritization of subscription relevant functionalities as well as the design of product and service elements addressing those functionalities are the main aspects on which the focus is placed on. The result is a subscription value proposition canvas for SMEs to address the impact of subscription models on products and services.
With big data-technologies on the rise, new fields of application appear in terms of analyzing data to find new relationships for improving process under-standing and stability. Manufacturing companies oftentimes cope with a high number of deviations but struggle to solve them with less effort. The research project BigPro aims to develop a methodology for implementing counter measures to disturbances and deviations derived from big data. This paper proposes a methodology for practitioners to assess predefined counter measures. It consists of a morphology with several criterions that can have a certain characteristic. Those are then combined with a weighting factor to assess the feasibility of the counter measure for prioritization.
Failure management in the production area has been intensely analyzed in the research community. Although several efficient methods have been developed and partially successfully implemented, producing companies still face a lot of challenges. The resulting main question is how manufacturers can be assisted by a sustainable approach enabling them to proactively detect and prevent failures before they occur. A high-resolution production system based on analyzed real-time data enables manufacturers to find an answer to the main question. In this context, Big Data technologies have gained importance since the critical success factor is not only to collect real-time data in the production but also to structure the data. Therefore, we present in this paper the implementation of Big Data technologies in the production area using the example of an actual research project. After the literature review, we describe a Big Data based approach to prevent failures in the production area. This approach mainly includes a real-time capable platform including complex event processing algorithms to define appropriate improvement measures.
Datenbasierte Services rücken durch die Vernetzung zunehmend in den Fokus von Unternehmen. Für produzierende Unternehmen jeder Größe ist es immanent, die eigenen Daten stärker zu nutzen. Durch ein historisches Wachstum des Unternehmens sind IT-Lösungen oftmals über das Unternehmen verteilt und Daten werden mehrfach gehalten. Mithilfe des Konzepts eines digitalen Schattens können die aufgezeigten Herausforderungen gelöst werden. Dessen Umsetzung erfolgt über software-definierte Plattformen. Diese ermöglichen ein Abbild der relevanten Unternehmensdaten und schaffen Transparenz über aktuelle und vergangene Ereignisse. Unter Nutzung von Datenanalyseverfahren und Visualisierungssystemen tragen sie zur Entscheidungsunterstützung im Unternehmen bei. Dieser Beitrag enthält eine Definition dieses Plattformtyps und eine Morphologie zur Einordnung verschiedener Plattformen vor. Anhand des morphologischen Kastens werden die zentralen, notwendigen Merkmale einer software-definierten Plattform herausgearbeitet und beschrieben. Integrationsanforderungen zur Einführung in Unternehmen werden in den vier Dimensionen Technik, Organisation, Prozesse sowie Anforderungen zur Datenintegration dargestellt.
Ergänzt wird diese Betrachtung um Praxiserfahrungen bei der Umsetzung einer software-definierten Plattform. Damit liefert der Artikel einen Beitrag zur Diskussion um software-definierte Plattformen und unterstützt Unternehmen bei der Einführung einer solchen.
ECM im Mittelstand
(2017)
Mit der ganzheitlichen Strategie des Enterprise Content Management (ECM) werden alle Dokumente eines Unternehmens verwaltet und organisiert. Durch den Einsatz geeigneter ECM Werkzeuge erhalten Unternehmen zum Beispiel Unterstützung beim effizienten Erfassen, Ablegen und Wiederauffinden von Dokumenten, bei der Abwicklung dokumentenbasierter Prozesse sowie bei der Einhaltung rechtlicher Vorgaben, etwa zur revisionssicheren Archivierung. Damit können ECM-Lösungen einen maßgeblichen Beitrag zur Digitalisierung der Geschäfts- und Arbeitswelt im Sinne des »Digital Office« leisten.
Das Konzept des umfassenden ECM ist mittlerweile in großen Unternehmen etabliert. Wesentliche Treiber sind hier neben offensichtlichen Rationalisierungseffekten und hohen Anforderungen an die Rechtssicherheit im Umgang mit Dokumenten(Compliance) vor allem auch neue Formen der Zusammenarbeit in Teams sowie die Automatisierung und Integration von Geschäftsprozessen. Auch die voranschreitende Digitalisierung von Geschäftsmodellen benötigt eine komplett digitale Unterstützung, zum Beispiel die automatisierte Ablage und Weiterverarbeitung von Verträgen oder Bankgeschäften, die im Internet geschlossen werden. Um Medienbrüche zu vermeiden und damit ein Geschäftsvorfall schnell nach den Compliance-Gesichtspunkten verarbeitet werden kann, ist eine ECM-Strategie, die der Unternehmensstrategie folgt, angeraten.
Vor diesem Hintergrund bietet die Studie »ECM im Mittelstand 2017« anhand der Aussagen von über 600 mittelständischen Unternehmen eine Bestandsaufnahme der ECM-Praxis im Mittelstand. Im Vordergrund stehen Fragen zum Begriffsverständnis, zur Verbreitung, zu Nutzen und zu Kosten von ECM-Software ebenso wie zu zukünftigen Entwicklungen und Trends rund um ECM im Mittelstand. Aufgrund vergleichbarer Fragestellungen sind in weiten Teilen Aussagen zur Entwicklung seit 2013 möglich, die auf entsprechenden Studienergebnissen aus einer Vorgängerstudie basieren.
Nachhaltige Lieferketten
(2021)
Das Thema der Nachhaltigkeit ist nicht zuletzt aufgrund aktueller Entwicklungen zunehmend in den gesellschaftlichen und unternehmerischen Fokus gelangt. Pandemien, Naturkatastrophen, aber auch regulatorische Auflagen zur Erfüllung von Klimaschutzzielen haben zu einem Umdenken geführt. Im Rahmen des Thementags „Sustainable Supply-Chain-Management“ hat das FIR an der RWTH Aachen zusammen mit Expert:innen aus Wirtschaft und Forschung Thesen erarbeitet, die widerspiegeln, wie das Thema Nachhaltigkeit aktuell in deutschen Unternehmen wahrgenommen und umgesetzt wird und welche besondere Bedeutung dem Supply-Chain-Management dabei zukommt. Nachhfolgend werden diese und deren Implikationen für die Praxis vorgestellt.
Ein ständig wachsender Preisdruck und immer individuellere Kundenaufträge sind nur zwei Kennzeichen der industriellen Produktion im europäischen Wirtschaftsraum. Gerade in Deutschland ansässige Unternehmen können im internationalen Wettbewerb in den wenigsten Fällen allein aufgrund des Produktpreises konkurrenzfähig bleiben. Stattdessen bauen diese Unternehmen ihre Wettbewerbsvorteile anderweitig aus und verfolgen vielmehr eine konsequente Kundenorientierung, hohe Logistikleistung oder Prozessbeherrschung. In diesem Umfeld setzten zahlreiche Unternehmen bereits frühzeitig auf eine Reduzierung ihrer Wertschöpfungstiefe und verlagerten verschiedene Entwicklungs- oder Produktionsschritte auf andere Unternehmen mit komplementären Kompetenzen. Damit rückte die überbetriebliche Zusammenarbeit bzw. Koordination der Auftragsabwicklung entlang einer mehrstufigen Lieferkette oder innerhalb eines polyzentrischen Unternehmensnetzwerks zunehmend in den Mittelpunkt betrieblicher Anstrengungen. So gilt es also heute, in Netzwerkstrukturen zu denken, diese ganzheitlich zu gestalten und effizient zu organisieren. Der Beitrag konkretisiert am Beispiel des Aachener PPS-Modells geeignete Referenzmodelle und zeigt Entwicklungspfade einer wertorientierten Logistikgestaltung auf.
In Germany’s transition to a more sustainable industrial landscape, electricity generated by wind turbines (WT) remains a mainstay of the energy mix. Operating and maintenance costs, which account for roughly 25% of electricity generation costs in onshore WTs make improvements of maintenance activities a key lever in the economic operation of WTs. Prescriptive maintenance is a possible approach for improved maintenance activities. It is a concept where asset condition data is used to recommend specific actions and has great potential for the operation of wind parks. However, especially small, but also large wind park operators, and maintenance service providers often struggle with the implementation of such a new maintenance approach. As a part of the research project ReStroK, a learning game has been developed to support the training and familiarization of maintenance technicians with the concepts and underlying principles of this maintenance approach. In this paper, the concept for the development of a learning game will be presented. Multiple scenarios for its usage and their corresponding requirements will be discussed and an overview over the game will be given.
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.
Influenced by the high dynamic of the markets the optimization of supply chains gains more importance. However, analyzing different procurement strategies and the influence of various production parameters is difficult to achieve in industrial practice. Therefore, simulations of supply chains are used in order to improve the production process. The objective of this research is to evaluate different procurement strategies in a four-stage supply chain. Besides, this research aims to identify main influencing factors on the supply chain’s performance. The performance of the supply chain is measured by means of back orders (backlog). A scenario analysis of different customer demands and a Design of Experiments analysis enhance the significance of the simulation results.
In immer komplexer werdenden Wertschöpfungsketten wird die Geschwindigkeit, mit der Informationen weitergegeben und entsprechende Maßnahmen umgesetzt werden können, zu einem entscheidenden Wettbewerbsvorteil. In der Realität kommt es jedoch auf dem Weg zwischen einem Ereignis und einer passenden Reaktion zu verschiedenen zeitlichen Verzögerungen, sogenannten Latenzen, die die Agilität eines Unternehmens erheblich hemmen. Insbesondere das Supply-Chain-Management mit seiner koordinierenden Funktion wird dadurch vor enorme Herausforderungen gestellt. Schlüsseltechnologien im Zeitalter von Digitalisierung und Industrie 4.0 bieten jedoch enorme Potenziale, die verschiedenen Formen von Latenzen zu reduzieren. Der Beitrag untersucht die unternehmensübergreifenden Effekte dieser Verzögerungen entlang der Supply-Chain und beleuchtet darüber hinaus die Potentiale konkreter digitaler Technologien auf selbige.
A large number of product-accompanying services in the machinery and plant engineering industry is based on the cross-company exchange of data and information. By providing services, additional sales potential on the manufacturer side as well as far-reaching product and process advantages for appliers can be reached. However, the necessary cross-company exchange of information is nowadays limited due to a lack of trust in the interacting partner and the applicable existing technologies, which results in significant losses in the terms of business potential. The uncovering of this potential now seems to be made possible by the use of the Blockchain technology. Through the key factors security, immutability, transparency and decentralisation, it serves as an enabler for cross-company communication and product-accompanying services. The technological implementation of a Blockchain can take on a broad spectrum of attributes, which can lead to decisive restrictions for the execution of services. This justifies the necessity for a qualified and context-related assessment of service-types-individual specifications and the resulting requirements on the system. Within the scope of this paper, different types of product-accompanying services are identified and analysed regarding their requirements for a Blockchain-based machinery and plant connection. This can serve as a basis for a qualified and goal-oriented configuration of the Blockchain.
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.
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.
Es ist davon auszugehen, dass einfache, repetitive Tätigkeiten in absehbarer Zeit in zunehmendem Maße automatisiert werden. Daher wird für Beschäftigte, die maßgeblich mit diesen Tätigkeiten betraut sind, Qualifizierung zu einem zentralen Faktor. Darüber hinaus wird es für einen großen Teil der Höherqualifizierten zu einer deutlichen Verschiebung der Qualifikationsanforderungen sowie zu einer zunehmenden Informatisierung der Arbeit kommen. Der Buchbeitrag von Volker Stich, Gerhard Gudergan und Roman Senderek verdeutlicht, dass angesichts dieser Herausforderungen für die Unternehmen, das arbeitsnahe Lernen eine Möglichkeit darstellt, Menschen und Unternehmen für den aktuellen industriellen Wandel zu befähigen. Hierbei sind nach Ansicht der Autoren jedoch zunächst Arbeits- und Produktionssysteme zu schaffen, die lernförderlich geplant und gestaltet sind. Um dies zu ermöglichen, bedarf es einer Kategorisierung der verfügbaren arbeitsorientierten Lernformen und insbesondere neuer technologiegestützter Lernformen. Darüber hinaus sind die Rahmenbedingungen und Voraussetzungen von Unternehmen zu prüfen und im Hinblick auf die Anwendung der verschiedenen Lernformen zu bewerten. Eine Systematik hierfür und die Erfahrungen bei der Implementierung von arbeitsorientierten Lernformen bei vier Unternehmenspartnern schließen diesen Beitrag ab.
The aim of the related research project eCloud is to enable small and medium sized enterprises (SMEs) to implement flexible energy management without in-depth energy knowledge and with little distraction from day-to-day business, which is prepared for current and future challenges in the field of energy use. The overall result is a validated prototype for a plug and automate capable (i.e. without implementation effort) operational energy management, which can be successively set up in SMEs based on a cloud platform. Through its gradual and modular implementation, energy management meets the individual needs of each company and contributes to energy system transformation and climate protection by reducing energy costs and greenhouse gas emissions by up to 25%. In total, three expansion stages are available with the levels of monitoring, load management and grid usage, which consist of various Software as a Service (SaaS) modules from the cloud that can be retrieved as required. Thus, the user only needs a minimal hardware intervention in his production and saves a complex IT infrastructure. The methodology developed has been successfully applied by two user companies so far. This proves the effectiveness of the method.
The technical development of the 5G mobile communication technology has been successfully completed. Now, vendor companies struggle with the analysis of industrial application and sales strategies as well as the development of business cases for their customers. Since this challenge is faced by many technology providers with innovative technologies in the “trough of disillusionment”, FIR’s information technology management has developed a methodology to bridge the gap, based on the example of 5G. This paper presents a methodology for identifying applications and defining business cases to select the most profitable ones. We also validate the methodology in the 5Gang research project.
Since 2016, the “Digital in NRW” Competence Centre has been supporting SMEs in the manufacturing industry in designing their individual digital transformation. With an Industry 4.0 maturity assessment, we define the status quo of SMEs, derive SME-specific measures from this, develop a digitalization roadmap and accompany the SME transformation. This paper presents the results of the four-year SME support. By analyzing the results of all maturity assessments, potential analysis and design workshops, we present the most frequent and most effective measures for a successful digital transformation of SMEs. The result of the paper is an action guideline for SMEs to initiate their own digital transformation based on formalized experience.
Eine Herausforderung für produzierende Unternehmen in der Entwicklung intelligenter Produkte besteht darin, dass die Zielstellung, die mit einem intelligenten Produkt verfolgt wird, nicht expliziert ist. Zudem ist oftmals nicht spezifiziert, in welchem Anwendungsfall ein intelligentes Produkt agieren soll. Produzierende Unternehmen benötigen Unterstützung, um eine zielorientierte und folglich wirtschaftliche Melioration existierender Produkte zu gewährleisten. Ebendiese Melioration wird im Kontext von intelligenten Produkten als Smartifizierung bezeichnet und stellt damit einen Entwicklungsprozess dar, der ein bestehendes Produkt als Ausgangssituation im Sinne einer Anpassungskonstruktion expliziert. Die originäre Produktfunktion wird folglich nicht verändert, sondern das Produkt um digitale Funktionen und Dienstleistungen erweitert. Der Artikel befasst sich daher erstens mit der Beschreibung generischer Ziele für den Einsatz intelligenter Produkte im Maschinenbau. Eine Zusammenstellung und Erläuterung solcher Ziele unterstützt Unternehmen, eine Präzisierung der Zielfestlegung in der Initiierungsphase eines Smartifizierungsprojekts durchzuführen. Zweitens wird unter Anwendung der Ziel-Mittel-Beziehung ein Anwendungsfall intelligenter Produkte beschrieben. Abschließend werden beide Aspekte in einer Methode zusammengefasst, wie mittels Ziel- und Anwendungsfallbetrachtung Anforderungen abgeleitet und wie diese Elemente in Vorgehensmodelle der Produktentwicklung eingebettet werden können. Exemplarisch wird anhand eines Energiekompensators aufzeigt, wie die Methode und die sich daraus ableitenden Ergebnisse im Smartifizierungsprozess zur Entwicklung eines intelligenten Energiekompensators eingesetzt werden.
Raus aus der Schockstarre!
(2019)
Nie war die Stellung von vermeintlichen Marktführern unsicherer als im Zeitalter der Digitalisierung. Die neuen technischen Möglichkeiten, in innovativen Geschäftsmodellen Wert aus der explodierenden Datenmenge zu schöpfen, wirbeln den Markt durcheinander. Wer mit dem technischen Wandel nicht mitgeht, riskiert, rasch abgehängt zu werden. Die gute Nachricht: Der Weg zur Industrie 4.0 ist ein Weg der kleinen Schritte. Überschaubare Maßnahmen heute sind allemal besser als der ganz große Wurf übermorgen.
Machine Learning
(2019)
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.
This paper addresses the challenge of a systematic requirement-oriented configuration and selection of cyber physical systems (CPS) for SMEs. As the key technologies of realizing the digitalization and interconnection of production processes, manufacturing companies have realized the potential benefits brought by CPS. However, due to the
complexity and fast development of CPS technology, it is difficult for SMEs, which lack expertise and financial resources, to select the appropriate CPS technologies meeting both functional and financial requirements. To overcome the issue, an online matching platform is developed to let SMEs express their needs and assist them onceptualize
the individual CPS. This paper presents the matching methodology of the matching platform, which can not only match technical characteristics but also evaluate economic potentials. Then, it was demonstrated by a tracking and tracing use case in the end-of-line assembly of a small-sized German electric automobile manufacturer.
Zeugnis der Reife
(2018)
Aktuell sehen sich deutsche Unternehmen damit konfrontiert, dass ihre bisherigen Produktionsabläufe und Arbeitsweisen immer weniger mit der Digitalisierung und den damit veränderten Maßstäben des 21. Jahrhunderts mithalten können. Neue innovative Lösungen werden benötigt, um produktiv voranzugehen und den Wandel für sich zu nutzen.
Die digitale Transformation hat mittlerweile alle Wertschöpfungsstufen im industriellen Sektor erfasst. So ist ein großer Teil aktuell produzierter Maschinen bereits mit Sensorik und Software ausgestattet und kommuniziert über digitale Infrastrukturen. Stetig sinkende Kosten für Sensorik , Vernetzungstechnologien, Rechen- und Speicherleistung erlauben Unternehmen die wirtschaftliche Erhebung und Verarbeitung von Daten in einem bisher nicht gekannten Ausmaß. Diese Veränderungen durch Digitalisierung und Industrie 4.0 müssen Unternehmen als Chance für den industriellen Service nutzen.
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).