Refine
Year of publication
Document Type
- Conference Proceeding (86) (remove)
Is part of the Bibliography
- no (86)
Keywords
- 02 (14)
- 03 (2)
- 3GPP (1)
- 5G (3)
- 5G mobile communication (1)
- 5G use case (1)
- 5G-Technology (1)
- AI (2)
- Additive Fertigung (1)
- Adherence To Delivery Dates (1)
- Agile management Systems (1)
- Agriculture (1)
- Anlaufmanagement (1)
- Artificial intelligence (1)
- Assembly (1)
- Asset Management (1)
- Assistance Systems (1)
- Augmented Reality (1)
- B2B customer service (1)
- Big Data (1)
- BigPro (1)
- Business analytics (2)
- Business ecosystems (1)
- Business model innovation (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)
- Co-Creation (1)
- Competencies (1)
- Crisis management (1)
- Cross-Industry Innovation (1)
- Customer Perspective (1)
- Customer Success Management (1)
- Customer success managementl (1)
- Cyber Security (1)
- Data Analytics (1)
- Data Products (1)
- Data Quality (1)
- Data-Centric Platform (1)
- Data-based pricings (1)
- Data-driven services (1)
- Decision Support (2)
- Decision Support System (1)
- Demand Forecasting (1)
- Design of Experiments (1)
- Deviation Detection (1)
- Digital Transformation (1)
- Digital platform design (1)
- Digital transformation (1)
- Digitale Transformation (1)
- Digitalisation (1)
- Digitalisierung (1)
- Digitalization (1)
- Digitization (2)
- Digitization of SMEs (1)
- Discrete Event Simulation (1)
- Disruption Management (1)
- Disruptions (1)
- Distribution management (1)
- Disturbance Management (1)
- Do-it-together (1)
- EPCIS (1)
- ERP (1)
- Efficiency Improvement (1)
- Employee qualification (1)
- Energiemanagement (1)
- Entscheidungsunterstützung (2)
- Ersatzteillogistik (1)
- Evaluation (2)
- Event Data (1)
- Feedback data (1)
- Flexible manufacturing system (1)
- Food Production (1)
- Forecasting capability (1)
- Freight forwarder (1)
- Furniture Production Process (1)
- Human-centered work design (1)
- Humanitarian logistics (1)
- IT-Architektur (1)
- Implementation barriers (1)
- Implementation success factors (1)
- Incorrect Data (1)
- Industrial sustainability (1)
- Industrie 4.0 (10)
- Industry 4.0 (1)
- Information Logistics (1)
- Information Transparency (1)
- Informationslogistik (1)
- Innovative Furniture (1)
- Instandhaltung (1)
- Insufficient Data (1)
- Interface definition (1)
- Internet of Production (4)
- Internet of Things (1)
- IoP (1)
- IoT (1)
- KI (1)
- KMAT (1)
- KMU (2)
- KPI (1)
- Kennzahlen (1)
- Key Performance Indicators (1)
- Knowledge representation (1)
- Konferenz (1)
- Konfigurierbare Materialien (1)
- Künstliche Intelligenz (1)
- Lean Manufacturing (1)
- Learning Game (1)
- Lebensmittelindustrie (1)
- Leistungsfähigkeit (1)
- Logistikdienstleister (1)
- MES (1)
- Machine Learning (1)
- Machine learning (1)
- Manufacturing (2)
- Manufacturing Companies (2)
- Manufacturing Execution System (1)
- Manufacturing firms (1)
- Manufacturing industry (1)
- Matching (2)
- Maturity Index (1)
- Maturity Model, Maturity Index (1)
- Maturity model (1)
- Mixed-Model Assembly (1)
- Modellierung (1)
- Morphology (2)
- Networked (1)
- Online retail (1)
- Onlinehandel (1)
- Ontology (1)
- Operating models (1)
- Operations planning (1)
- Optimized capacity utilization (1)
- Order Quantity (1)
- PPC (1)
- Performance-Management (1)
- Plastics industry (1)
- Platform economy (1)
- Potential Benefits (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 (1)
- Produktentwicklung (1)
- Produktionsmanagement (1)
- Produktionsplanung (1)
- Produktionsplanung und -steuerung (1)
- Produktionssteuerung (1)
- Quarrying Industry (1)
- Quarrying industry (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)
- Risikomanagement (1)
- Risk assessment (1)
- Risks (1)
- Route sectioning algorithm (1)
- SCEM (1)
- SCM (1)
- SME (1)
- SV7126 (1)
- SV7136 (1)
- SV7169 (1)
- SV7190 (1)
- SV7213 (1)
- SV7242 (1)
- SV7266 (1)
- SV7276 (1)
- SV7289 (1)
- SV7427 (1)
- Scenario pattern (1)
- Scenario technique (1)
- Sensors (1)
- Service engineering (1)
- Setup time optimizing sequencing (1)
- Similarity Analysis (1)
- Skills forecasting (1)
- Skills management (1)
- Smart Services (1)
- Smart farming (1)
- Smart product service system (1)
- Smart services (1)
- Social Manufacturing (1)
- Socio-technical analysis (1)
- Sociotechnical (1)
- Softwaretool (1)
- Strategie (1)
- Strategy (1)
- Störungsmanagement (2)
- Subscription (1)
- Subscription Business (1)
- Subscription Business Models (1)
- Subscription business (2)
- Supply Chain Event Management (2)
- Supply Risks (1)
- Supply chain (1)
- Supply-Chain-Design (1)
- Supply-Chain-Management (4)
- Supply-Chain-Networks (1)
- Sustainability (3)
- Swarm robotics (1)
- Task View (1)
- Task-oriented Reference Model (1)
- Taxonomy (1)
- Training (1)
- Transport order (1)
- Twin transition (1)
- Type-specific (1)
- Typification (2)
- Typology (1)
- Value capture (1)
- Value creation (1)
- Value-based Pricing (1)
- Value-in-Use (1)
- Value-in-use (2)
- Viable System Model (2)
- Visual Analytics (1)
- Vorgehensmodell (1)
- Wireless communication (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)
- business model (2)
- case study research (3)
- classification systems (1)
- condition monitoring (1)
- counter measures (1)
- criticality analysis (1)
- data valuation framework (2)
- data value (3)
- data value assessment (1)
- decision making (1)
- decision support (2)
- deep learning (1)
- design (1)
- deviation detection (1)
- digital services (1)
- digital shadow (3)
- digitale Technologien (1)
- digitale Transformation (1)
- digitalization (1)
- disruption management (1)
- disturbance management (2)
- energy consumption (1)
- energy efficiency (1)
- flight demand (1)
- hybride Systeme (1)
- hype cycle (1)
- i4.0 (1)
- iIntangible assets (1)
- industry 4.0 (1)
- information logistics model (1)
- information management (1)
- intangible assets (1)
- intelligent maintenance systems (1)
- intelligent support system (1)
- internet of production (1)
- inventory management (2)
- it-architecture (1)
- machine learning (1)
- 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)
- production control (1)
- production networks (1)
- reaction strategy (1)
- real-time systems (1)
- rev (31)
- risk analysis system (1)
- risk management (1)
- service engineering (1)
- smart product service systems (2)
- smart services (1)
- subscription business (1)
- subscription business models (1)
- supply chain (2)
- supply chain event management (1)
- supply chain management (1)
- system dynamics (2)
- task model (1)
- technology management (1)
- technology scouting (1)
- text mining (1)
- thin-haul (1)
- transport demand (1)
- Änderungsmanagement (1)
Institute
Generation of a Data Model For Quotation Costing Of Make To Order Manufacturers From Case Studies
(2022)
For contract or make to order manufacturers, quotation costing is a complex process that is mainly performed based on experience. Due to the high diversity of the product range of these mostly small or medium-sized companies (SMEs) and the poor data situation at the time of quotation preparation, the quality of the calculation is subject to strong variations and uncertainties. The gap between the initial quotation costing and the actual costs to be spent (pre- and post-calculation) is crucial to the existence of SMEs. Digitalization in general can help companies to get a better understanding of processes and to generate data. For improving these processes, an understanding of the important data for that specific process is crucial. Accurate quotation costing for customized products is time-consuming and resource-intensive, as there is a lack of an overview of data to be used within the process. This paper therefore derives a data model for supporting quotation costing in the company, based on literature-based costing procedures and recorded case studies for quotation and calculation. Based on the results, SMEs will have a first overview of the needed data for quotation costing to optimize their calculation process.
High Resolution Supply Chain Management aims to counteract the trend towards more and more centralised and rigid enterprises. Today, most companies strive to increase efficiency of business processes applying highly sophisticated, centralised planning approaches. These centralised approaches limit the companies’ ability to react flexibly and act adaptively due to external and internal turbulences. In today’s buyer’s markets companies usually try to bypass these turbulences keeping high levels of inventory resulting in a low overall efficiency. High Resolution Supply Chain Management tries to solve the problem at its root from a holistic perspective. Based on the Viable System Model developed by Stafford Beer a four-dimensional holistic production management system model, embedding an organisational structure view, an cause and action view, a control loop perspective and a decision making level has been elaborated. The basis of this model is the integration of all four perspectives into an interacting framework.
High Resolution Supply Chain Management (HRSCM) aims to stop the trend of continuously increasing planning complexity. Today, companies in high-wage countries mostly strive for further optimization of their processes with sophisticated, capital-intensive planning approaches. The capability to adapt flexibly to dynamically changing conditions is limited by the inflexible and centralized planning logic. Thus, flexibility is reached currently by expensive inventory stocks and overcapacities in order to cope with rescheduling of supply or delivery. HRSCM describes the establishment of a complete information transparency in supply chains with the goal of assuring the availability of goods through decentralized, self-optimizing control loops for Production Planning and Control (PPC). HRSCM pursues the idea of enabling organization structures and processes to adapt to dynamic conditions. The approach includes the strengths of the existing planning models as well as the process of decision making in organizations. A precondition for this decentralized adaptation is the synchronization of the objectives of the several units or process owners. The basis for this new PPC Model are information transparency, stable processes, consistent customer orientation, increased capacity flexibility and the understanding of the production system as a viable, socio-technical system.
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.
Auf Basis einer systematischen Literaturanalyse wurden insgesamt 11 Kennzahlen identifiziert, welche die Grundlage zur Beschreibung der operativen Leistungsfähigkeit von Unternehmen bilden. Die Kennzahlen wurden in die vier Leistungsdimensionen Effizienz, Qualität, Zeit und Flexibilität eingeteilt.
The use of chatbots has hardly been established in B2B companies to date and involves various challenges. The goal of this paper is to identify the biggest barriers to the successful implementation of chatbots in B2B customer service and to develop measures to overcome them. The barriers are identified by conducting expert interviews within the framework of Eisenhardt's case study research. These are examined through a socio-technical analysis focusing on people, technology, and organization. By means of systematic literature research and in-depth interviews with German chatbot providers and customers of chatbots, measures for overcoming the barriers are identified. Using interviews with experts from German chatbot providers, the responsible stakeholders of each measure according to the RASCI Responsibility Matrix are determined. A total of 46 implementation barriers and 100 measures to overcome these barriers are identified. The study shows that there are major barriers in the areas of people, technology, and organization of a socio-technical system that can cause the implementation of a chatbot to fail. A holistic view is therefore essential. The results provide firms with a guideline on how to overcome potential barriers during chatbot implementation in B2B customer service.
While digitization is a strategic advantage in numerous industries such as the automotive industry or mechanical engineering, other industries like the German quarrying industry have not yet established a transformation towards a digitized industry. This leads to inefficient work and inaccurate forecasting capabilities. To address these challenges, digital platforms can incentivize digitization
by supporting the capacity utilization and forecasting capability of these companies. In this paper, the quarrying industry is analyzed by a morphology and different types of companies are identified. Knowing the digital maturity of these companies and by determining the key factors to forecast demands and the capacity utilization, different operating models are derived. Combined with a morphology and the value creation system, different scenarios for the identification of platform services are examined. These scenarios are weighted in a utility analysis to get an operating model blueprint to develop and establish digital platforms in less digitized industries.
Manufacturing companies (MFRs) are increasingly extending their
portfolios with services and data-driven services (DDS) to differentiate themselves from competitors, tap new revenue potential, and gain competitive advantages through digitization and the subsequently generated data. Nonetheless, DDS fail more often than traditional industrial services and products within the first year on the market. Particularly, companies are failing to sell DDS successfully and efficiently with their existing (multi-level) distribution structures. Surprisingly, there is a lack of scientific research addressing this issue. Since there are currently no holistic models for an end-to-end description of distribution-tasks for DDS in the manufacturing industry, this paper contributes to a task-oriented reference model for mapping interactions in the multi-level distribution management. Therefore, a case study research approach is used, to identify and describe the interactions in the multi-level distribution management of DDS, as well as to develop a regulatory framework for MFRs and their multi-level distribution management. This research uses the established theoretical framework of Service-Dominant-Logic to address the co-creation in multi-level distribution management of DDS. As a result, this paper identifies different interaction variants as well as the need for a new management function with 4 main and 14 basic tasks.
Aufgrund kürzer werdender Produktzyklen und steigender Produktvielfalt werden produzierende Unternehmen mit einer zunehmenden Anzahl von Produktanläufen konfrontiert. Ziel aktueller Forschungsaktivitäten ist es daher, anlaufintensive Unternehmen zu befähigen, verlässliche Produktionsprogramme in kurzer Zeit zu erstellen. Lerneffekte sollen genutzt werden können ohne Diversifikationseffekte zu vernachlässigen. Zur Erreichung dieser Zielsetzung wird ein Modell für eine kybernetische PPP bei Produktanläufen entwickelt.
Changing customer demands lead to increasing product varieties and decreasing delivery times, which in turn pose great challenges for production companies. Combined with high market volatility, they lead to increasingly complex and diverse production processes. Thus, the susceptibility to disruptions in manufacturing rises, turning the task of Production Planning and Control (PPC) into a complex, dynamic and multidimensional problem. Addressing PPC challenges such as disruption management in an efficient and timely manner requires a high level of manual human intervention. In times of digitization and Industry 4.0, companies strive to find ways to guide their workers in this process of disruption management or automate it to eliminate human intervention altogether. This paper presents one possible application of Machine Learning (ML) in disruption management on a real-life use case in mixed model continuous production, specifically in the final assembly. The aim is to ensure high-quality online decision support for PPC tasks. This paper will therefore discuss the use of ML to anticipate production disruptions, solutions to efficiently highlight and convey the relevant information, as well as the generation of possible reaction strategies. Additionally, the necessary preparatory work and fundamentals are covered in the discussion, providing guidelines for production companies towards consistent and efficient disruption management.